From a75200ab3390ca3e8eb2777d67ed9de589eba070 Mon Sep 17 00:00:00 2001 From: Weijia Chen Date: Mon, 6 Jul 2026 21:18:48 +0000 Subject: [PATCH 1/6] repro --- ray_actorpool_cascade_bug.ipynb | 122 ++++++++++++++++++++++++++++++++ 1 file changed, 122 insertions(+) create mode 100644 ray_actorpool_cascade_bug.ipynb diff --git a/ray_actorpool_cascade_bug.ipynb b/ray_actorpool_cascade_bug.ipynb new file mode 100644 index 0000000000..1d25c9bb96 --- /dev/null +++ b/ray_actorpool_cascade_bug.ipynb @@ -0,0 +1,122 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "0e1c4aa4-6fc1-43c2-831e-12d72d0935ba", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Ray version: 2.55.1\n" + } + ], + "source": "# Ray Data ActorPool Underutilization Reproducer\n# ================================================\n# Reproduces: https://github.com/ray-project/ray/issues/XXXXX\n#\n# Shows that ActorPoolStrategy(initial_size=N, min_size=1) underutilizes\n# the actor pool and delivers lower throughput than\n# ActorPoolStrategy(min_size=N, max_size=N), even though both configurations\n# have the same maximum number of actors.\n#\n# Tested on: Ray 2.55.1\n\nimport ray\nimport ray.data\nimport time, os, pprint, shutil, threading\nfrom collections import Counter\nfrom dataclasses import dataclass\n\nprint(f\"Ray version: {ray.__version__}\")\n" + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "922f29ed-5b0e-4e41-9f3a-4d9c12c040a9", + "metadata": {}, + "outputs": [], + "source": "# \u2500\u2500 Pipeline Configuration \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\nVIDEO_DIR = \"/raid/curator-team/datasets/openvid-1m/video\"\nOUTPUT_DIR = \"/raid/weijiac/tmp/raydata_transcode_test\"\nVIDEO_LIMIT = 1000 # number of videos to process\nTRANSCODE_CPUS = 6.0 # CPUs reserved per TranscodeActor\nMAX_TRANSCODE_OVERRIDE = 9 # set to reproduce the observed underutilization run\n" + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "c16ab467", + "metadata": {}, + "outputs": [], + "source": "import subprocess, tempfile, json as _json, uuid, shutil\nfrom pathlib import Path\nfrom concurrent.futures import ThreadPoolExecutor\n\nCLIP_LEN_S = 10.0\nMIN_CLIP_LEN_S = 2.0\nENCODE_BATCH_SIZE = 16\nENCODER = \"libopenh264\"\nENCODER_THREADS = 1\n# TRANSCODE_CPUS set in cell 1\nWRITE_CPUS = 0.25\nCLIPS_PER_CHUNK = 32\nCHUNK_SIZE_S = CLIPS_PER_CHUNK * 8 * CLIP_LEN_S\n\nVIDEO_EXTENSIONS = (\".mp4\", \".mov\", \".avi\", \".mkv\", \".webm\")\n\n\ndef ls_videos(batch):\n # Simulate slow upstream I/O (e.g. S3/NFS file listing, large dataset scan).\n import time as _time\n _time.sleep(15)\n paths = []\n for ext in VIDEO_EXTENSIONS:\n paths.extend(Path(VIDEO_DIR).rglob(f\"*{ext}\"))\n paths = sorted(str(p) for p in paths)[:VIDEO_LIMIT]\n return {\"path\": paths}\n\ndef read_and_probe(batch):\n out = {k: [] for k in [\"path\", \"bytes\", \"duration\", \"fps\", \"num_frames\",\n \"width\", \"height\", \"video_codec\", \"pixel_format\",\n \"audio_codec\", \"bit_rate_k\"]}\n for path in batch[\"path\"]:\n raw = Path(path).read_bytes()\n with tempfile.NamedTemporaryFile(suffix=\".mp4\", delete=False) as tmp:\n tmp.write(raw)\n tmp_path = tmp.name\n try:\n result = subprocess.run(\n [\"ffprobe\", \"-v\", \"error\", \"-show_format\", \"-show_streams\",\n \"-of\", \"json\", tmp_path],\n stdout=subprocess.PIPE, stderr=subprocess.PIPE, check=True,\n )\n finally:\n Path(tmp_path).unlink(missing_ok=True)\n info = _json.loads(result.stdout)\n vs = next(s for s in info[\"streams\"] if s[\"codec_type\"] == \"video\")\n audio_codec = next((s[\"codec_name\"] for s in info[\"streams\"]\n if s[\"codec_type\"] == \"audio\"), None)\n num, den = map(int, vs[\"avg_frame_rate\"].split(\"/\"))\n fps = num / den\n duration = float(vs[\"duration\"]) if \"duration\" in vs else float(info[\"format\"][\"duration\"])\n bit_rate_k = int(int(vs[\"bit_rate\"]) / 1024) if \"bit_rate\" in vs else 2000\n out[\"path\"].append(path)\n out[\"bytes\"].append(raw)\n out[\"duration\"].append(duration)\n out[\"fps\"].append(fps)\n out[\"num_frames\"].append(int(duration * fps))\n out[\"width\"].append(int(vs[\"width\"]))\n out[\"height\"].append(int(vs[\"height\"]))\n out[\"video_codec\"].append(vs[\"codec_name\"])\n out[\"pixel_format\"].append(vs[\"pix_fmt\"])\n out[\"audio_codec\"].append(audio_codec)\n out[\"bit_rate_k\"].append(bit_rate_k)\n return out\n\ndef split_fixed_stride(batch):\n out = {k: [] for k in list(batch.keys()) + [\"clips\"]}\n for i in range(len(batch[\"path\"])):\n duration = batch[\"duration\"][i]\n clips, t = [], 0.0\n while t < duration:\n end = min(t + CLIP_LEN_S, duration)\n if end - t >= MIN_CLIP_LEN_S:\n clips.append((t, end))\n t += CLIP_LEN_S\n for k in batch.keys():\n out[k].append(batch[k][i])\n out[\"clips\"].append(clips)\n return out\n\ndef _split_clips_into_chunks(clips_with_ids):\n chunks, cur_chunk, cur_dur = [], [], 0.0\n for item in clips_with_ids:\n (s, e), cid = item\n cur_chunk.append(item)\n cur_dur += e - s\n if cur_dur >= CHUNK_SIZE_S:\n chunks.append(cur_chunk)\n cur_chunk, cur_dur = [], 0.0\n if cur_chunk:\n chunks.append(cur_chunk)\n return chunks\n\ndef transcode(batch):\n out = {\"path\": [], \"clip_chunk_index\": [], \"num_total_clips\": [],\n \"num_clip_chunks\": [], \"clips\": [], \"clip_bytes_map\": [],\n \"width\": [], \"height\": [], \"fps\": [], \"num_frames\": [],\n \"video_codec\": [], \"pixel_format\": [], \"audio_codec\": [], \"bit_rate_k\": []}\n for i, path in enumerate(batch[\"path\"]):\n # Ray Data passes batch values as numpy arrays \u2014 convert to Python types\n clips = [(float(s), float(e)) for s, e in batch[\"clips\"][i]]\n if len(clips) == 0:\n continue\n pix_fmt = str(batch[\"pixel_format\"][i]) if batch[\"pixel_format\"][i] is not None else \"\"\n force_pix_fmt = \"10le\" in pix_fmt or \"10be\" in pix_fmt\n with tempfile.TemporaryDirectory() as tmp_dir:\n tmp = Path(tmp_dir)\n (tmp / \"input.mp4\").write_bytes(bytes(batch[\"bytes\"][i]))\n fps = float(batch[\"fps\"][i])\n clip_ids = [\n str(uuid.uuid5(uuid.NAMESPACE_URL, f\"{path}_{int(s*fps)}_{int(e*fps)}\"))\n for s, e in clips\n ]\n for b in range(0, len(clips), ENCODE_BATCH_SIZE):\n b_clips = clips[b:b+ENCODE_BATCH_SIZE]\n b_ids = clip_ids[b:b+ENCODE_BATCH_SIZE]\n cmd = [\"ffmpeg\", \"-hide_banner\", \"-loglevel\", \"error\"]\n for j, (start, end) in enumerate(b_clips):\n cmd += [\"-threads\", str(ENCODER_THREADS),\n \"-ss\", str(start), \"-to\", str(end), \"-i\", \"input.mp4\",\n \"-map\", f\"{j}:v:0\", \"-c:v\", ENCODER]\n if force_pix_fmt:\n cmd += [\"-pix_fmt\", \"yuv420p\"]\n cmd += [\"-threads\", str(ENCODER_THREADS),\n \"-map\", f\"{j}:a:0?\", \"-c:a\", \"copy\", f\"{b_ids[j]}.mp4\"]\n subprocess.check_output(cmd, cwd=tmp, stderr=subprocess.STDOUT)\n clip_bytes = {cid: (tmp / f\"{cid}.mp4\").read_bytes()\n for cid in clip_ids if (tmp / f\"{cid}.mp4\").exists()}\n clip_chunks = _split_clips_into_chunks(list(zip(clips, clip_ids))) # [(s,e), cid] pairs\n for chunk_idx, chunk in enumerate(clip_chunks):\n chunk_clips = [(s, e) for (s, e), _ in chunk]\n chunk_ids = [cid for _, cid in chunk]\n out[\"path\"].append(path)\n out[\"clip_chunk_index\"].append(chunk_idx)\n out[\"num_total_clips\"].append(len(clips))\n out[\"num_clip_chunks\"].append(len(clip_chunks))\n out[\"clips\"].append(list(zip(chunk_ids, chunk_clips)))\n out[\"clip_bytes_map\"].append({cid: clip_bytes[cid] for cid in chunk_ids if cid in clip_bytes})\n for k in [\"width\", \"height\", \"fps\", \"num_frames\", \"video_codec\",\n \"pixel_format\", \"audio_codec\", \"bit_rate_k\"]:\n out[k].append(batch[k][i])\n return out\n\ndef _probe_clip(clip_bytes):\n with tempfile.NamedTemporaryFile(suffix=\".mp4\", delete=False) as tmp:\n tmp.write(clip_bytes)\n tmp_path = tmp.name\n try:\n result = subprocess.run(\n [\"ffprobe\", \"-v\", \"error\", \"-show_streams\", \"-of\", \"json\", tmp_path],\n stdout=subprocess.PIPE, stderr=subprocess.PIPE, check=True,\n )\n finally:\n Path(tmp_path).unlink(missing_ok=True)\n vs = next(s for s in _json.loads(result.stdout)[\"streams\"] if s[\"codec_type\"] == \"video\")\n num, den = map(int, vs[\"avg_frame_rate\"].split(\"/\"))\n return {\"width\": int(vs[\"width\"]), \"height\": int(vs[\"height\"]),\n \"framerate\": num/den, \"num_frames\": int(vs.get(\"nb_frames\", 0)),\n \"video_codec\": vs[\"codec_name\"], \"num_bytes\": len(clip_bytes)}\n\ndef write_clips(batch):\n clips_dir = Path(OUTPUT_DIR) / \"clips\"\n metas_dir = Path(OUTPUT_DIR) / \"metas\" / \"v0\"\n videos_dir = Path(OUTPUT_DIR) / \"processed_videos\"\n chunks_dir = Path(OUTPUT_DIR) / \"processed_clip_chunks\"\n for d in [clips_dir, metas_dir, videos_dir, chunks_dir]:\n d.mkdir(parents=True, exist_ok=True)\n\n def write_one_chunk(i):\n path = batch[\"path\"][i]\n clip_bytes_map = batch[\"clip_bytes_map\"][i]\n chunk_clips = [(str(cid), (float(s), float(e))) for cid, (s, e) in batch[\"clips\"][i]]\n chunk_idx = int(batch[\"clip_chunk_index\"][i])\n vmeta = {\n \"width\": int(batch[\"width\"][i]),\n \"height\": int(batch[\"height\"][i]),\n \"fps\": float(batch[\"fps\"][i]),\n \"num_frames\": int(batch[\"num_frames\"][i]),\n \"video_codec\": str(batch[\"video_codec\"][i]),\n \"pixel_format\": str(batch[\"pixel_format\"][i]),\n \"audio_codec\": str(batch[\"audio_codec\"][i]) if batch[\"audio_codec\"][i] is not None else None,\n \"bit_rate_k\": int(batch[\"bit_rate_k\"][i]),\n }\n num_transcoded, total_dur, max_dur = 0, 0.0, 0.0\n with ThreadPoolExecutor(max_workers=6) as ex:\n futures = []\n for cid, (start, end) in chunk_clips:\n cb = clip_bytes_map.get(cid)\n if not cb:\n continue\n futures.append(ex.submit((clips_dir / f\"{cid}.mp4\").write_bytes, cb))\n span_dur = end - start\n clip_meta = {\n \"span_uuid\": cid, \"source_video\": path,\n \"duration_span\": [start, end],\n \"width_source\": vmeta[\"width\"], \"height_source\": vmeta[\"height\"],\n \"framerate_source\": vmeta[\"fps\"],\n \"clip_location\": str(clips_dir / f\"{cid}.mp4\"),\n \"windows\": [], \"valid\": True,\n }\n try:\n clip_meta.update(_probe_clip(cb))\n except Exception:\n pass\n futures.append(ex.submit(\n (metas_dir / f\"{cid}.json\").write_text, _json.dumps(clip_meta)))\n num_transcoded += 1\n total_dur += span_dur\n max_dur = max(max_dur, span_dur)\n for f in futures:\n f.result()\n if chunk_idx == 0:\n video_meta = {\n \"video\": path, \"height\": vmeta[\"height\"], \"width\": vmeta[\"width\"],\n \"framerate\": vmeta[\"fps\"], \"num_frames\": vmeta[\"num_frames\"],\n \"video_codec\": vmeta[\"video_codec\"], \"pixel_format\": vmeta[\"pixel_format\"],\n \"audio_format\": vmeta[\"audio_codec\"],\n \"num_total_clips\": int(batch[\"num_total_clips\"][i]),\n \"num_clip_chunks\": int(batch[\"num_clip_chunks\"][i]),\n }\n rel = path.removeprefix(VIDEO_DIR).lstrip(\"/\") + \".json\"\n vpath = videos_dir / rel\n vpath.parent.mkdir(parents=True, exist_ok=True)\n vpath.write_text(_json.dumps(video_meta))\n chunk_stats = {\n \"video\": path, \"clip_chunk_index\": chunk_idx,\n \"num_clips_transcoded\": num_transcoded, \"num_clips_passed\": num_transcoded,\n \"total_clip_duration\": total_dur, \"max_clip_duration\": max_dur,\n \"clips\": [cid for cid, _ in chunk_clips],\n }\n rel = path.removeprefix(VIDEO_DIR).lstrip(\"/\") + f\"_{chunk_idx}.json\"\n cpath = chunks_dir / rel\n cpath.parent.mkdir(parents=True, exist_ok=True)\n cpath.write_text(_json.dumps(chunk_stats))\n return {\"path\": path, \"clip_ids\": [cid for cid, _ in chunk_clips]}\n\n results = [write_one_chunk(i) for i in range(len(batch[\"path\"]))]\n return {\"path\": [r[\"path\"] for r in results],\n \"clip_ids\": [r[\"clip_ids\"] for r in results]}" + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "8119e8a0", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": "2026-07-06 19:16:41,821\tINFO worker.py:2003 -- Started a local Ray instance. View the dashboard at \u001b[1m\u001b[32mhttp://127.0.0.1:8268 \u001b[39m\u001b[22m\n/opt/venv/lib/python3.13/site-packages/ray/_private/worker.py:2051: FutureWarning: Tip: In future versions of Ray, Ray will no longer override accelerator visible devices env var if num_gpus=0 or num_gpus=None (default). To enable this behavior and turn off this error message, set RAY_ACCEL_ENV_VAR_OVERRIDE_ON_ZERO=0\n warnings.warn(\n" + }, + { + "name": "stdout", + "output_type": "stream", + "text": "Total CPUs: 64, max transcode workers: 9\nCPU pressure: 54/64 = 84%\n" + }, + { + "name": "stderr", + "output_type": "stream", + "text": "2026-07-06 19:16:44,644\tINFO logging.py:416 -- Registered dataset logger for dataset dataset_7_0\n2026-07-06 19:16:44,664\tINFO streaming_executor.py:166 -- Starting execution of Dataset dataset_7_0. Full logs are in /tmp/ray/session_2026-07-06_19-16-28_966894_3085811/logs/ray-data\n2026-07-06 19:16:44,665\tINFO streaming_executor.py:167 -- Execution plan of Dataset dataset_7_0: InputDataBuffer[Input] -> TaskPoolMapOperator[MapBatches(ls_videos)] -> AllToAllOperator[Repartition] -> TaskPoolMapOperator[MapBatches(read_and_probe)->MapBatches(split_fixed_stride)] -> ActorPoolMapOperator[MapBatches(TranscodeActor)] -> AllToAllOperator[Repartition] -> TaskPoolMapOperator[MapBatches(write_clips)]\n[2026-07-06 19:16:44,700 E 3085811 3085811] core_worker.cc:2194: Actor with class name: 'MapWorker(MapBatches(TranscodeActor))' and ID: '92944ed62242556e267e28ed01000000' has constructor arguments in the object store and max_restarts > 0. If the arguments in the object store go out of scope or are lost, the actor restart will fail. See https://github.com/ray-project/ray/issues/53727 for more details.\n2026-07-06 19:16:44,852\tWARNING resource_manager.py:169 -- \u26a0\ufe0f Ray's object store is configured to use only 9.1% of available memory (186.3GiB out of 2048.2GiB total). For optimal Ray Data performance, we recommend setting the object store to at least 50% of available memory. You can do this by setting the 'object_store_memory' parameter when calling ray.init() or by setting the RAY_DEFAULT_OBJECT_STORE_MEMORY_PROPORTION environment variable.\n2026-07-06 19:16:44,854\tINFO __init__.py:56 -- Progress will be logged because stdout is a non-interactive terminal.\n2026-07-06 19:16:45,572\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:16:45,574\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:16:45,577\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 0.0B/93.1GiB object store\n2026-07-06 19:16:45,578\tINFO logging_progress.py:181 -- \n2026-07-06 19:16:45,579\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 0/1\n2026-07-06 19:16:45,579\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store\n2026-07-06 19:16:45,580\tINFO logging_progress.py:231 -- Repartition: 0/1\n2026-07-06 19:16:45,580\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n2026-07-06 19:16:45,581\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:16:45,582\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 0/1\n2026-07-06 19:16:45,582\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:16:45,582\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 0/1\n2026-07-06 19:16:45,583\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 9; Queued blocks: 0 (0.0B); Resources: 54.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:16:45,583\tINFO logging_progress.py:231 -- Repartition: 0/1\n2026-07-06 19:16:45,583\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n2026-07-06 19:16:45,584\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:16:45,584\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:16:45,585\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:16:45,585\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:16:55,641\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:16:55,644\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:16:55,646\tINFO logging_progress.py:227 -- Active & requested resources: 55/64 CPU, 0.0B/93.1GiB object store\n2026-07-06 19:16:55,647\tINFO logging_progress.py:181 -- \n2026-07-06 19:16:55,648\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 0/1\n2026-07-06 19:16:55,648\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store\n2026-07-06 19:16:55,648\tINFO logging_progress.py:231 -- Repartition: 0/1\n2026-07-06 19:16:55,649\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n2026-07-06 19:16:55,649\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:16:55,649\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 0/1\n2026-07-06 19:16:55,650\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:16:55,651\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 0/1\n2026-07-06 19:16:55,651\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 9; Queued blocks: 0 (0.0B); Resources: 54.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:16:55,651\tINFO logging_progress.py:231 -- Repartition: 0/1\n2026-07-06 19:16:55,652\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n2026-07-06 19:16:55,652\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:16:55,652\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:16:55,653\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:16:55,653\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:17:05,668\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:17:05,670\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:17:05,671\tINFO logging_progress.py:227 -- Active & requested resources: 46/64 CPU, 137.2MiB/93.1GiB object store\n2026-07-06 19:17:05,672\tINFO logging_progress.py:181 -- \n2026-07-06 19:17:05,673\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:17:05,674\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:05,674\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:17:05,675\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 72.3KiB object store; 1000 rows output\n2026-07-06 19:17:05,676\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:17:05,677\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 2/1000\n2026-07-06 19:17:05,678\tINFO logging_progress.py:233 -- Tasks: 11; Actors: 0; Queued blocks: 987 (71.5KiB); Resources: 11.0 CPU, 148.6MiB object store\n2026-07-06 19:17:05,678\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 0/1\n2026-07-06 19:17:05,678\tINFO logging_progress.py:233 -- Tasks: 2; Actors: 6; Queued blocks: 0 (0.0B); Resources: 36.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:17:05,679\tINFO logging_progress.py:231 -- Repartition: 0/1\n2026-07-06 19:17:05,679\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n2026-07-06 19:17:05,679\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:17:05,680\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:17:05,680\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:05,680\tINFO logging_progress.py:192 -- ============================================\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m Failed to convert column 'clips' into pyarrow array due to: Error converting data to Arrow: [[('31461cd8-a73a-5ebd-a716-ea7fceda30ab', (0.0, 4.204204))]]; falling back to serialize as pickled python objects\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m Traceback (most recent call last):\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 398, in _convert_to_pyarrow_native_array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m return pa.array(column_values, type=pa_type)\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m ~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m File \"pyarrow/array.pxi\", line 375, in pyarrow.lib.array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m File \"pyarrow/array.pxi\", line 46, in pyarrow.lib._sequence_to_array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m chunked = GetResultValue(\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m File \"pyarrow/error.pxi\", line 155, in pyarrow.lib.pyarrow_internal_check_status\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m File \"pyarrow/error.pxi\", line 92, in pyarrow.lib.check_status\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m raise convert_status(status)\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m pyarrow.lib.ArrowTypeError: Expected bytes, got a 'tuple' object\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m The above exception was the direct cause of the following exception:\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m Traceback (most recent call last):\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 299, in convert_to_pyarrow_array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m return _convert_to_pyarrow_native_array(column_values, column_name)\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 400, in _convert_to_pyarrow_native_array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m raise ArrowConversionError(str(column_values)) from e\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m ray.data._internal.tensor_extensions.arrow.ArrowConversionError: Error converting data to Arrow: [[('31461cd8-a73a-5ebd-a716-ea7fceda30ab', (0.0, 4.204204))]]\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087266)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087266)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087273)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087273)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087283)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087283)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091587)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091587)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087280)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087280)\u001b[0m \n2026-07-06 19:17:15,754\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:17:15,755\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:17:15,756\tINFO logging_progress.py:227 -- Active & requested resources: 37/64 CPU, 9.1GiB/93.1GiB object store\n2026-07-06 19:17:15,757\tINFO logging_progress.py:181 -- \n2026-07-06 19:17:15,757\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:17:15,757\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:15,758\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:17:15,758\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 371.0B object store; 1000 rows output\n2026-07-06 19:17:15,758\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:17:15,758\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 995/1000\n2026-07-06 19:17:15,759\tINFO logging_progress.py:233 -- Tasks: 2; Actors: 0; Queued blocks: 3 (222.0B); Resources: 2.0 CPU, 9.0GiB object store\n2026-07-06 19:17:15,759\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 42/1000\n2026-07-06 19:17:15,759\tINFO logging_progress.py:233 -- Tasks: 12; Actors: 6; Queued blocks: 941 (8.7GiB); Resources: 36.0 CPU, 120.0MiB object store; [all objects local]\n2026-07-06 19:17:15,759\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:17:15,760\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 42 (105.0MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:17:15,760\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:17:15,760\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:17:15,760\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:15,761\tINFO logging_progress.py:192 -- ============================================\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m Failed to convert column 'clips' into pyarrow array due to: Error converting data to Arrow: [[('1d9fd32b-73fa-502a-8b35-f08077ca27e9', (0.0, 6.266667))]]; falling back to serialize as pickled python objects\u001b[32m [repeated 6x across cluster] (Ray deduplicates logs by default. Set RAY_DEDUP_LOGS=0 to disable log deduplication, or see https://docs.ray.io/en/master/ray-observability/user-guides/configure-logging.html#log-deduplication for more options.)\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m Traceback (most recent call last):\u001b[32m [repeated 12x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 400, in _convert_to_pyarrow_native_array\u001b[32m [repeated 12x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m return pa.array(column_values, type=pa_type)\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m ~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m File \"pyarrow/array.pxi\", line 375, in pyarrow.lib.array\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m File \"pyarrow/array.pxi\", line 46, in pyarrow.lib._sequence_to_array\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m chunked = GetResultValue(\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m File \"pyarrow/error.pxi\", line 155, in pyarrow.lib.pyarrow_internal_check_status\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m File \"pyarrow/error.pxi\", line 92, in pyarrow.lib.check_status\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m raise convert_status(status)\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m pyarrow.lib.ArrowTypeError: Expected bytes, got a 'tuple' object\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m The above exception was the direct cause of the following exception:\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 299, in convert_to_pyarrow_array\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m return _convert_to_pyarrow_native_array(column_values, column_name)\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m raise ArrowConversionError(str(column_values)) from e\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m ray.data._internal.tensor_extensions.arrow.ArrowConversionError: Error converting data to Arrow: [[('1d9fd32b-73fa-502a-8b35-f08077ca27e9', (0.0, 6.266667))]]\u001b[32m [repeated 6x across cluster]\u001b[0m\n2026-07-06 19:17:25,817\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:17:25,819\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:17:25,820\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 8.9GiB/93.1GiB object store\n2026-07-06 19:17:25,820\tINFO logging_progress.py:181 -- \n2026-07-06 19:17:25,821\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:17:25,821\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:25,821\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:17:25,822\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:17:25,822\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:17:25,822\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:17:25,823\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.6GiB object store\n2026-07-06 19:17:25,823\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 103/1000\n2026-07-06 19:17:25,823\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 883 (8.5GiB); Resources: 42.0 CPU, 276.2MiB object store; [all objects local]\n2026-07-06 19:17:25,824\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:17:25,824\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 103 (258.7MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:17:25,824\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:17:25,825\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:17:25,825\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:25,825\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:17:35,887\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:17:35,889\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:17:35,890\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 8.5GiB/93.1GiB object store\n2026-07-06 19:17:35,890\tINFO logging_progress.py:181 -- \n2026-07-06 19:17:35,890\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:17:35,891\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:35,891\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:17:35,891\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:17:35,892\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:17:35,892\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:17:35,893\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.1GiB object store\n2026-07-06 19:17:35,893\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 166/1000\n2026-07-06 19:17:35,893\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 820 (7.9GiB); Resources: 42.0 CPU, 418.1MiB object store; [all objects local]\n2026-07-06 19:17:35,894\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:17:35,894\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 166 (401.2MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:17:35,895\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:17:35,895\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:17:35,895\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:35,895\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:17:45,936\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:17:45,938\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:17:45,939\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 7.9GiB/93.1GiB object store\n2026-07-06 19:17:45,940\tINFO logging_progress.py:181 -- \n2026-07-06 19:17:45,940\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:17:45,941\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:45,941\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:17:45,942\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:17:45,942\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:17:45,942\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:17:45,943\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 7.4GiB object store\n2026-07-06 19:17:45,944\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 225/1000\n2026-07-06 19:17:45,944\tINFO logging_progress.py:233 -- Tasks: 12; Actors: 7; Queued blocks: 763 (7.2GiB); Resources: 42.0 CPU, 586.7MiB object store; [all objects local]\n2026-07-06 19:17:45,945\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:17:45,945\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 225 (569.0MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:17:45,945\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:17:45,945\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:17:45,946\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:45,946\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:17:55,936\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:17:55,937\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:17:55,938\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 7.6GiB/93.1GiB object store\n2026-07-06 19:17:55,938\tINFO logging_progress.py:181 -- \n2026-07-06 19:17:55,939\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:17:55,939\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:55,939\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:17:55,939\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:17:55,940\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:17:55,940\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:17:55,941\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 6.9GiB object store\n2026-07-06 19:17:55,941\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 289/1000\n2026-07-06 19:17:55,941\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 697 (6.7GiB); Resources: 42.0 CPU, 723.8MiB object store; [all objects local]\n2026-07-06 19:17:55,941\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:17:55,942\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 289 (706.7MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:17:55,942\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:17:55,942\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:17:55,942\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:55,943\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:18:06,045\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:18:06,047\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:18:06,049\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 7.0GiB/93.1GiB object store\n2026-07-06 19:18:06,049\tINFO logging_progress.py:181 -- \n2026-07-06 19:18:06,050\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:18:06,050\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:06,051\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:18:06,051\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:06,052\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:18:06,052\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:18:06,053\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 6.2GiB object store\n2026-07-06 19:18:06,053\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 354/1000\n2026-07-06 19:18:06,053\tINFO logging_progress.py:233 -- Tasks: 13; Actors: 7; Queued blocks: 633 (6.0GiB); Resources: 42.0 CPU, 875.1MiB object store; [all objects local]\n2026-07-06 19:18:06,054\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:18:06,054\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 354 (858.1MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:06,054\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:18:06,057\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:18:06,057\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:06,058\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:18:16,155\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:18:16,157\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:18:16,159\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 6.6GiB/93.1GiB object store\n2026-07-06 19:18:16,161\tINFO logging_progress.py:181 -- \n2026-07-06 19:18:16,162\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:18:16,163\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:16,164\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:18:16,164\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:16,166\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:18:16,167\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:18:16,168\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 5.6GiB object store\n2026-07-06 19:18:16,168\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 420/1000\n2026-07-06 19:18:16,170\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 566 (5.4GiB); Resources: 42.0 CPU, 1019.4MiB object store; [all objects local]\n2026-07-06 19:18:16,171\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:18:16,172\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 420 (1002.7MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:16,173\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:18:16,173\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:18:16,174\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:16,175\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:18:26,220\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:18:26,223\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:18:26,224\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 6.2GiB/93.1GiB object store\n2026-07-06 19:18:26,225\tINFO logging_progress.py:181 -- \n2026-07-06 19:18:26,226\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:18:26,226\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:26,227\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:18:26,227\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:26,228\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:18:26,228\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:18:26,229\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 5.1GiB object store\n2026-07-06 19:18:26,229\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 490/1000\n2026-07-06 19:18:26,229\tINFO logging_progress.py:233 -- Tasks: 13; Actors: 7; Queued blocks: 497 (5.0GiB); Resources: 42.0 CPU, 1.1GiB object store; [all objects local]\n2026-07-06 19:18:26,230\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:18:26,231\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 490 (1.1GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:26,232\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:18:26,232\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:18:26,232\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:26,233\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:18:36,238\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:18:36,239\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:18:36,240\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 5.8GiB/93.1GiB object store\n2026-07-06 19:18:36,241\tINFO logging_progress.py:181 -- \n2026-07-06 19:18:36,242\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:18:36,242\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:36,243\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:18:36,243\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:36,243\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:18:36,243\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:18:36,244\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 4.5GiB object store\n2026-07-06 19:18:36,244\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 547/1000\n2026-07-06 19:18:36,245\tINFO logging_progress.py:233 -- Tasks: 13; Actors: 7; Queued blocks: 440 (4.4GiB); Resources: 42.0 CPU, 1.3GiB object store; [all objects local]\n2026-07-06 19:18:36,245\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:18:36,245\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 547 (1.3GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:36,246\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:18:36,246\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:18:36,247\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:36,247\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:18:46,347\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:18:46,349\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:18:46,350\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 5.4GiB/93.1GiB object store\n2026-07-06 19:18:46,351\tINFO logging_progress.py:181 -- \n2026-07-06 19:18:46,352\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:18:46,353\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:46,354\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:18:46,355\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:46,356\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:18:46,356\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:18:46,356\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 3.9GiB object store\n2026-07-06 19:18:46,357\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 615/1000\n2026-07-06 19:18:46,357\tINFO logging_progress.py:233 -- Tasks: 12; Actors: 7; Queued blocks: 373 (3.8GiB); Resources: 42.0 CPU, 1.4GiB object store; [all objects local]\n2026-07-06 19:18:46,358\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:18:46,358\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 615 (1.4GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:46,359\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:18:46,360\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:18:46,361\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:46,361\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:18:56,375\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:18:56,377\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:18:56,378\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 4.7GiB/93.1GiB object store\n2026-07-06 19:18:56,379\tINFO logging_progress.py:181 -- \n2026-07-06 19:18:56,380\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:18:56,380\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:56,381\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:18:56,381\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:56,382\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:18:56,384\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:18:56,384\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 3.1GiB object store\n2026-07-06 19:18:56,385\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 673/1000\n2026-07-06 19:18:56,386\tINFO logging_progress.py:233 -- Tasks: 12; Actors: 7; Queued blocks: 315 (3.0GiB); Resources: 42.0 CPU, 1.6GiB object store; [all objects local]\n2026-07-06 19:18:56,386\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:18:56,387\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 673 (1.6GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:56,387\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:18:56,388\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:18:56,388\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:56,389\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:19:06,402\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:19:06,403\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:19:06,403\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 4.3GiB/93.1GiB object store\n2026-07-06 19:19:06,404\tINFO logging_progress.py:181 -- \n2026-07-06 19:19:06,404\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:19:06,404\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:06,405\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:19:06,405\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:06,405\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:19:06,405\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:19:06,405\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 2.6GiB object store\n2026-07-06 19:19:06,406\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 732/1000\n2026-07-06 19:19:06,406\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 254 (2.4GiB); Resources: 42.0 CPU, 1.7GiB object store; [all objects local]\n2026-07-06 19:19:06,406\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:19:06,407\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 732 (1.7GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:06,407\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:19:06,407\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:19:06,407\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:06,408\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:19:16,461\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:19:16,463\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:19:16,465\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 3.9GiB/93.1GiB object store\n2026-07-06 19:19:16,465\tINFO logging_progress.py:181 -- \n2026-07-06 19:19:16,466\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:19:16,467\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:16,467\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:19:16,467\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:16,468\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:19:16,468\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:19:16,468\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 2.0GiB object store\n2026-07-06 19:19:16,469\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 799/1000\n2026-07-06 19:19:16,469\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 187 (1.8GiB); Resources: 42.0 CPU, 1.9GiB object store; [all objects local]\n2026-07-06 19:19:16,469\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:19:16,470\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 799 (1.8GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:16,470\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:19:16,471\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:19:16,471\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:16,471\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:19:26,467\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:19:26,469\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:19:26,470\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 3.2GiB/93.1GiB object store\n2026-07-06 19:19:26,471\tINFO logging_progress.py:181 -- \n2026-07-06 19:19:26,471\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:19:26,472\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:26,472\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:19:26,473\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:26,473\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:19:26,473\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:19:26,474\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 1.2GiB object store\n2026-07-06 19:19:26,474\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 860/1000\n2026-07-06 19:19:26,475\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 126 (1.1GiB); Resources: 42.0 CPU, 2.0GiB object store; [all objects local]\n2026-07-06 19:19:26,475\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:19:26,475\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 860 (2.0GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:26,476\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:19:26,476\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:19:26,476\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:26,476\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:19:36,531\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:19:36,532\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:19:36,534\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 2.9GiB/93.1GiB object store\n2026-07-06 19:19:36,535\tINFO logging_progress.py:181 -- \n2026-07-06 19:19:36,536\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:19:36,536\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:36,537\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:19:36,537\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:36,537\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:19:36,538\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:19:36,538\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 781.3MiB object store\n2026-07-06 19:19:36,538\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 927/1000\n2026-07-06 19:19:36,539\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 59 (627.0MiB); Resources: 42.0 CPU, 2.1GiB object store; [all objects local]\n2026-07-06 19:19:36,539\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:19:36,539\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 927 (2.1GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:36,539\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:19:36,540\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:19:36,540\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:36,540\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:19:46,547\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:19:46,550\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:19:46,551\tINFO logging_progress.py:227 -- Active & requested resources: 36/64 CPU, 2.4GiB/93.1GiB object store\n2026-07-06 19:19:46,552\tINFO logging_progress.py:181 -- \n2026-07-06 19:19:46,553\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:19:46,553\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:46,555\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:19:46,555\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:46,556\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:19:46,557\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:19:46,557\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 158.8MiB object store\n2026-07-06 19:19:46,559\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 994/1000\n2026-07-06 19:19:46,560\tINFO logging_progress.py:233 -- Tasks: 6; Actors: 6; Queued blocks: 0 (0.0B); Resources: 36.0 CPU, 2.3GiB object store; [all objects local]\n2026-07-06 19:19:46,560\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:19:46,561\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 994 (2.3GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:46,561\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:19:46,562\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:19:46,562\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:46,562\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:19:56,601\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:19:56,603\tINFO logging_progress.py:225 -- Total Progress: 12/20000\n2026-07-06 19:19:56,605\tINFO logging_progress.py:227 -- Active & requested resources: 64/64 CPU, 2.3GiB/93.1GiB object store\n2026-07-06 19:19:56,605\tINFO logging_progress.py:181 -- \n2026-07-06 19:19:56,606\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:19:56,607\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:56,607\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:19:56,608\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:56,609\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:19:56,610\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:19:56,611\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:56,612\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:19:56,614\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:19:56,615\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:19:56,616\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 2.3GiB object store; 1000 rows output\n2026-07-06 19:19:56,618\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:19:56,619\tINFO logging_progress.py:231 -- MapBatches(write_clips): 15/20000\n2026-07-06 19:19:56,620\tINFO logging_progress.py:233 -- Tasks: 256 [backpressured:tasks(ResourceBudget)]; Actors: 0; Queued blocks: 19729 (1.6GiB); Resources: 64.0 CPU, 35.3KiB object store\n2026-07-06 19:19:56,621\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:20:06,604\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:20:06,607\tINFO logging_progress.py:225 -- Total Progress: 12/20000\n2026-07-06 19:20:06,608\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:20:06,609\tINFO logging_progress.py:181 -- \n2026-07-06 19:20:06,610\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:20:06,610\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:06,611\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:06,619\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:20:06,620\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:06,620\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:20:06,621\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:06,623\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:20:06,624\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:20:06,625\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:06,628\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:20:06,629\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:06,630\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:20:06,630\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 128.1KiB object store\n2026-07-06 19:20:06,631\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:20:16,607\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:20:16,610\tINFO logging_progress.py:225 -- Total Progress: 13/20000\n2026-07-06 19:20:16,611\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:20:16,612\tINFO logging_progress.py:181 -- \n2026-07-06 19:20:16,612\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:20:16,613\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:16,614\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:16,615\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:20:16,615\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:16,617\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:20:16,619\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:16,621\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:20:16,622\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:20:16,623\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:16,624\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:20:16,625\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:16,625\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:20:16,626\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 128.1KiB object store\n2026-07-06 19:20:16,627\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:20:26,610\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:20:26,614\tINFO logging_progress.py:225 -- Total Progress: 118/20000\n2026-07-06 19:20:26,615\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:20:26,616\tINFO logging_progress.py:181 -- \n2026-07-06 19:20:26,617\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:20:26,618\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:26,619\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:26,620\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:20:26,621\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:26,621\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:20:26,622\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:26,623\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:20:26,624\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:20:26,625\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:26,625\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:20:26,626\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:26,627\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:20:26,627\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 114.6KiB object store\n2026-07-06 19:20:26,627\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:20:36,610\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:20:36,613\tINFO logging_progress.py:225 -- Total Progress: 131/20000\n2026-07-06 19:20:36,615\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:20:36,616\tINFO logging_progress.py:181 -- \n2026-07-06 19:20:36,617\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:20:36,618\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:36,619\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:36,620\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:20:36,620\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:36,621\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:20:36,622\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:36,623\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:20:36,625\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:20:36,626\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:36,627\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:20:36,627\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:36,628\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:20:36,630\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 112.9KiB object store\n2026-07-06 19:20:36,631\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:20:46,616\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:20:46,621\tINFO logging_progress.py:225 -- Total Progress: 132/20000\n2026-07-06 19:20:46,625\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:20:46,626\tINFO logging_progress.py:181 -- \n2026-07-06 19:20:46,627\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:20:46,628\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:46,629\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:46,630\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:20:46,630\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:46,631\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:20:46,632\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:46,633\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:20:46,634\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:20:46,635\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:46,636\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:20:46,636\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:46,637\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:20:46,638\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 112.8KiB object store\n2026-07-06 19:20:46,639\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:20:56,625\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:20:56,628\tINFO logging_progress.py:225 -- Total Progress: 137/20000\n2026-07-06 19:20:56,629\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:20:56,630\tINFO logging_progress.py:181 -- \n2026-07-06 19:20:56,631\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:20:56,632\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:56,633\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:56,634\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:20:56,635\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:56,636\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:20:56,636\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:56,637\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:20:56,639\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:20:56,639\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:56,640\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:20:56,640\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:56,641\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:20:56,642\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 112.2KiB object store\n2026-07-06 19:20:56,642\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:21:06,630\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:21:06,632\tINFO logging_progress.py:225 -- Total Progress: 165/20000\n2026-07-06 19:21:06,634\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:21:06,635\tINFO logging_progress.py:181 -- \n2026-07-06 19:21:06,637\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:21:06,638\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:06,639\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:06,639\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:21:06,640\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:06,642\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:21:06,642\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:06,644\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:21:06,645\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:21:06,646\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:06,647\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:21:06,648\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:06,649\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:21:06,650\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 108.4KiB object store\n2026-07-06 19:21:06,651\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:21:16,640\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:21:16,642\tINFO logging_progress.py:225 -- Total Progress: 229/20000\n2026-07-06 19:21:16,643\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:21:16,650\tINFO logging_progress.py:181 -- \n2026-07-06 19:21:16,650\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:21:16,652\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:16,653\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:16,654\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:21:16,655\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:16,657\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:21:16,658\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:16,660\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:21:16,663\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:21:16,668\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:16,668\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:21:16,670\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:16,670\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:21:16,671\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 99.7KiB object store\n2026-07-06 19:21:16,672\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:21:26,640\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:21:26,643\tINFO logging_progress.py:225 -- Total Progress: 323/20000\n2026-07-06 19:21:26,652\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:21:26,653\tINFO logging_progress.py:181 -- \n2026-07-06 19:21:26,654\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:21:26,655\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:26,656\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:26,657\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:21:26,657\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:26,659\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:21:26,660\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:26,660\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:21:26,661\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:21:26,662\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:26,662\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:21:26,663\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:26,663\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:21:26,663\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 87.4KiB object store\n2026-07-06 19:21:26,664\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:21:36,643\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:21:36,647\tINFO logging_progress.py:225 -- Total Progress: 358/20000\n2026-07-06 19:21:36,648\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:21:36,649\tINFO logging_progress.py:181 -- \n2026-07-06 19:21:36,649\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:21:36,650\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:36,652\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:36,653\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:21:36,654\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:36,654\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:21:36,655\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:36,656\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:21:36,656\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:21:36,657\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:36,657\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:21:36,657\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:36,658\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:21:36,659\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 82.8KiB object store\n2026-07-06 19:21:36,659\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:21:46,648\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:21:46,650\tINFO logging_progress.py:225 -- Total Progress: 360/20000\n2026-07-06 19:21:46,651\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:21:46,652\tINFO logging_progress.py:181 -- \n2026-07-06 19:21:46,652\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:21:46,653\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:46,653\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:46,654\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:21:46,655\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:46,655\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:21:46,656\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:46,656\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:21:46,657\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:21:46,657\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:46,658\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:21:46,658\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:46,659\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:21:46,659\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 82.6KiB object store\n2026-07-06 19:21:46,660\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:21:56,652\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:21:56,654\tINFO logging_progress.py:225 -- Total Progress: 362/20000\n2026-07-06 19:21:56,655\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:21:56,656\tINFO logging_progress.py:181 -- \n2026-07-06 19:21:56,656\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:21:56,657\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:56,657\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:56,658\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:21:56,659\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:56,660\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:21:56,660\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:56,661\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:21:56,661\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:21:56,662\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:56,663\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:21:56,663\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:56,664\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:21:56,664\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 82.3KiB object store\n2026-07-06 19:21:56,665\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:22:06,662\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:22:06,674\tINFO logging_progress.py:225 -- Total Progress: 366/20000\n2026-07-06 19:22:06,681\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:22:06,688\tINFO logging_progress.py:181 -- \n2026-07-06 19:22:06,692\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:22:06,696\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:06,701\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:22:06,703\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:22:06,705\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:22:06,706\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:22:06,708\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:06,712\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:22:06,716\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:22:06,718\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:22:06,719\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:22:06,720\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:22:06,724\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:22:06,725\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 82.2KiB object store\n2026-07-06 19:22:06,727\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:22:16,676\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:22:16,679\tINFO logging_progress.py:225 -- Total Progress: 473/20000\n2026-07-06 19:22:16,683\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:22:16,683\tINFO logging_progress.py:181 -- \n2026-07-06 19:22:16,684\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:22:16,684\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:16,685\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:22:16,688\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:22:16,697\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:22:16,703\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:22:16,711\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:16,715\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:22:16,715\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:22:16,716\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:22:16,717\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:22:16,720\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:22:16,723\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:22:16,725\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 68.1KiB object store\n2026-07-06 19:22:16,726\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:22:26,683\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:22:26,684\tINFO logging_progress.py:225 -- Total Progress: 552/20000\n2026-07-06 19:22:26,685\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:22:26,686\tINFO logging_progress.py:181 -- \n2026-07-06 19:22:26,686\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:22:26,687\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:26,687\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:22:26,688\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:22:26,688\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:22:26,689\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:22:26,689\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:26,689\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:22:26,690\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:22:26,691\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:22:26,691\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:22:26,692\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:22:26,693\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:22:26,694\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 57.9KiB object store\n2026-07-06 19:22:26,694\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:22:36,684\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:22:36,686\tINFO logging_progress.py:225 -- Total Progress: 571/20000\n2026-07-06 19:22:36,688\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:22:36,689\tINFO logging_progress.py:181 -- \n2026-07-06 19:22:36,690\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:22:36,691\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:36,691\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:22:36,692\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:22:36,694\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:22:36,695\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:22:36,695\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:36,696\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:22:36,696\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:22:36,697\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:22:36,698\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:22:36,698\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:22:36,698\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:22:36,699\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 55.6KiB object store\n2026-07-06 19:22:36,700\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:22:44,446\tINFO streaming_executor.py:294 -- \u2714\ufe0f Dataset dataset_7_0 execution finished in 359.76 seconds\n" + }, + { + "name": "stdout", + "output_type": "stream", + "text": "[ActorPool(min=1, max=N, initial=N)] 1000 videos, 1000 clip-chunks, 360.6s \u2014 2.77 vid/s\n" + }, + { + "name": "stderr", + "output_type": "stream", + "text": "2026-07-06 19:22:45,147\tINFO logging.py:416 -- Registered dataset logger for dataset dataset_15_0\n2026-07-06 19:22:45,156\tINFO streaming_executor.py:166 -- Starting execution of Dataset dataset_15_0. Full logs are in /tmp/ray/session_2026-07-06_19-16-28_966894_3085811/logs/ray-data\n2026-07-06 19:22:45,158\tINFO streaming_executor.py:167 -- Execution plan of Dataset dataset_15_0: InputDataBuffer[Input] -> TaskPoolMapOperator[MapBatches(ls_videos)] -> AllToAllOperator[Repartition] -> TaskPoolMapOperator[MapBatches(read_and_probe)->MapBatches(split_fixed_stride)] -> ActorPoolMapOperator[MapBatches(TranscodeActor)] -> AllToAllOperator[Repartition] -> TaskPoolMapOperator[MapBatches(write_clips)]\n2026-07-06 19:22:45,453\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:22:45,455\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:22:45,455\tINFO logging_progress.py:227 -- Active & requested resources: 0/64 CPU, 0.0B/93.1GiB object store (pending: 54 CPU)\n2026-07-06 19:22:45,456\tINFO logging_progress.py:181 -- \n2026-07-06 19:22:45,456\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 0/1\n2026-07-06 19:22:45,456\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store\n2026-07-06 19:22:45,457\tINFO logging_progress.py:231 -- Repartition: 0/1\n2026-07-06 19:22:45,457\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n2026-07-06 19:22:45,458\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:22:45,458\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 0/1\n2026-07-06 19:22:45,458\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:45,459\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 0/1\n2026-07-06 19:22:45,459\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 9 (running=0, restarting=0, pending=9); Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:22:45,460\tINFO logging_progress.py:231 -- Repartition: 0/1\n2026-07-06 19:22:45,460\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n2026-07-06 19:22:45,461\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:22:45,461\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:22:45,461\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:45,462\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:22:55,460\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:22:55,462\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:22:55,466\tINFO logging_progress.py:227 -- Active & requested resources: 55/64 CPU, 0.0B/93.1GiB object store\n2026-07-06 19:22:55,467\tINFO logging_progress.py:181 -- \n2026-07-06 19:22:55,468\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 0/1\n2026-07-06 19:22:55,468\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store\n2026-07-06 19:22:55,469\tINFO logging_progress.py:231 -- Repartition: 0/1\n2026-07-06 19:22:55,469\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n2026-07-06 19:22:55,470\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:22:55,471\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 0/1\n2026-07-06 19:22:55,473\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:55,473\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 0/1\n2026-07-06 19:22:55,474\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 9; Queued blocks: 0 (0.0B); Resources: 54.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:22:55,475\tINFO logging_progress.py:231 -- Repartition: 0/1\n2026-07-06 19:22:55,476\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n2026-07-06 19:22:55,476\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:22:55,477\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:22:55,477\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:55,478\tINFO logging_progress.py:192 -- =============================================\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m Failed to convert column 'clips' into pyarrow array due to: Error converting data to Arrow: [[('4dd9dc83-4c11-52b2-8123-e981a60d61f4', (0.0, 2.902903))]]; falling back to serialize as pickled python objects\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m Traceback (most recent call last):\u001b[32m [repeated 2x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 400, in _convert_to_pyarrow_native_array\u001b[32m [repeated 2x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m return pa.array(column_values, type=pa_type)\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m ~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m File \"pyarrow/array.pxi\", line 375, in pyarrow.lib.array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m File \"pyarrow/array.pxi\", line 46, in pyarrow.lib._sequence_to_array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m chunked = GetResultValue(\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m File \"pyarrow/error.pxi\", line 155, in pyarrow.lib.pyarrow_internal_check_status\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m File \"pyarrow/error.pxi\", line 92, in pyarrow.lib.check_status\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m raise convert_status(status)\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m pyarrow.lib.ArrowTypeError: Expected bytes, got a 'tuple' object\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m The above exception was the direct cause of the following exception:\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 299, in convert_to_pyarrow_array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m return _convert_to_pyarrow_native_array(column_values, column_name)\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m raise ArrowConversionError(str(column_values)) from e\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m ray.data._internal.tensor_extensions.arrow.ArrowConversionError: Error converting data to Arrow: [[('4dd9dc83-4c11-52b2-8123-e981a60d61f4', (0.0, 2.902903))]]\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m Failed to convert column 'clips' into pyarrow array due to: Error converting data to Arrow: [[('e58f0e20-a3ed-5a16-9c78-62c7acdb162f', (0.0, 3.76))]]; falling back to serialize as pickled python objects\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m return pa.array(column_values, type=pa_type)\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m ~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m File \"pyarrow/array.pxi\", line 375, in pyarrow.lib.array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m File \"pyarrow/array.pxi\", line 46, in pyarrow.lib._sequence_to_array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m chunked = GetResultValue(\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m File \"pyarrow/error.pxi\", line 155, in pyarrow.lib.pyarrow_internal_check_status\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m File \"pyarrow/error.pxi\", line 92, in pyarrow.lib.check_status\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m raise convert_status(status)\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m pyarrow.lib.ArrowTypeError: Expected bytes, got a 'tuple' object\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m The above exception was the direct cause of the following exception:\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 299, in convert_to_pyarrow_array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m return _convert_to_pyarrow_native_array(column_values, column_name)\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m raise ArrowConversionError(str(column_values)) from e\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m ray.data._internal.tensor_extensions.arrow.ArrowConversionError: Error converting data to Arrow: [[('e58f0e20-a3ed-5a16-9c78-62c7acdb162f', (0.0, 3.76))]]\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147839)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147839)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147836)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147836)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147835)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147835)\u001b[0m \n2026-07-06 19:23:05,483\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:23:05,485\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:23:05,487\tINFO logging_progress.py:227 -- Active & requested resources: 55/64 CPU, 1.5GiB/93.1GiB object store\n2026-07-06 19:23:05,488\tINFO logging_progress.py:181 -- \n2026-07-06 19:23:05,489\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:23:05,490\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:05,490\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:23:05,490\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 60.2KiB object store; 1000 rows output\n2026-07-06 19:23:05,491\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:23:05,491\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 169/1000\n2026-07-06 19:23:05,491\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 830 (60.1KiB); Resources: 1.0 CPU, 1.4GiB object store\n2026-07-06 19:23:05,492\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 5/1000\n2026-07-06 19:23:05,492\tINFO logging_progress.py:233 -- Tasks: 15; Actors: 9; Queued blocks: 149 (1.2GiB); Resources: 54.0 CPU, 21.3MiB object store; [all objects local]\n2026-07-06 19:23:05,492\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:23:05,493\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 5 (7.6MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:23:05,493\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:23:05,493\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:23:05,494\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:05,494\tINFO logging_progress.py:192 -- =============================================\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147832)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147832)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147831)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147831)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147838)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147838)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147833)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147833)\u001b[0m \n2026-07-06 19:23:15,585\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:23:15,587\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:23:15,589\tINFO logging_progress.py:227 -- Active & requested resources: 55/64 CPU, 8.2GiB/93.1GiB object store\n2026-07-06 19:23:15,589\tINFO logging_progress.py:181 -- \n2026-07-06 19:23:15,590\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:23:15,590\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:15,590\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:23:15,591\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 5.6KiB object store; 1000 rows output\n2026-07-06 19:23:15,591\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:23:15,591\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 922/1000\n2026-07-06 19:23:15,591\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 77 (5.6KiB); Resources: 1.0 CPU, 7.9GiB object store\n2026-07-06 19:23:15,592\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 86/1000\n2026-07-06 19:23:15,592\tINFO logging_progress.py:233 -- Tasks: 17; Actors: 9; Queued blocks: 819 (7.8GiB); Resources: 54.0 CPU, 247.8MiB object store; [all objects local]\n2026-07-06 19:23:15,592\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:23:15,592\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 86 (224.3MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:23:15,593\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:23:15,593\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:23:15,593\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:15,594\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:23:25,684\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:23:25,686\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:23:25,688\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 8.5GiB/93.1GiB object store\n2026-07-06 19:23:25,689\tINFO logging_progress.py:181 -- \n2026-07-06 19:23:25,690\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:23:25,691\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:25,691\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:23:25,692\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:23:25,692\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:23:25,692\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:23:25,693\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.1GiB object store\n2026-07-06 19:23:25,693\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 166/1000\n2026-07-06 19:23:25,693\tINFO logging_progress.py:233 -- Tasks: 17; Actors: 9; Queued blocks: 817 (7.9GiB); Resources: 54.0 CPU, 440.5MiB object store; [all objects local]\n2026-07-06 19:23:25,694\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:23:25,695\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 166 (417.9MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:23:25,695\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:23:25,695\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:23:25,696\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:25,696\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:23:35,765\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:23:35,768\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:23:35,770\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 7.8GiB/93.1GiB object store\n2026-07-06 19:23:35,771\tINFO logging_progress.py:181 -- \n2026-07-06 19:23:35,772\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:23:35,773\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:35,774\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:23:35,774\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:23:35,775\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:23:35,776\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:23:35,777\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 7.2GiB object store\n2026-07-06 19:23:35,777\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 243/1000\n2026-07-06 19:23:35,778\tINFO logging_progress.py:233 -- Tasks: 17; Actors: 9; Queued blocks: 740 (7.0GiB); Resources: 54.0 CPU, 641.2MiB object store; [all objects local]\n2026-07-06 19:23:35,778\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:23:35,779\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 243 (618.3MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:23:35,780\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:23:35,780\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:23:35,780\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:35,781\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:23:45,780\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:23:45,783\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:23:45,784\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 7.3GiB/93.1GiB object store\n2026-07-06 19:23:45,785\tINFO logging_progress.py:181 -- \n2026-07-06 19:23:45,786\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:23:45,787\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:45,788\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:23:45,789\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:23:45,790\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:23:45,791\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:23:45,791\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 6.5GiB object store\n2026-07-06 19:23:45,792\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 326/1000\n2026-07-06 19:23:45,792\tINFO logging_progress.py:233 -- Tasks: 17; Actors: 9; Queued blocks: 657 (6.2GiB); Resources: 54.0 CPU, 803.8MiB object store; [all objects local]\n2026-07-06 19:23:45,792\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:23:45,793\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 326 (782.2MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:23:45,793\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:23:45,793\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:23:45,794\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:45,794\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:23:55,854\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:23:55,856\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:23:55,858\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 6.6GiB/93.1GiB object store\n2026-07-06 19:23:55,859\tINFO logging_progress.py:181 -- \n2026-07-06 19:23:55,860\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:23:55,861\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:55,861\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:23:55,861\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:23:55,862\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:23:55,863\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:23:55,863\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 5.6GiB object store\n2026-07-06 19:23:55,863\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 411/1000\n2026-07-06 19:23:55,864\tINFO logging_progress.py:233 -- Tasks: 16; Actors: 9; Queued blocks: 573 (5.5GiB); Resources: 54.0 CPU, 1014.8MiB object store; [all objects local]\n2026-07-06 19:23:55,864\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:23:55,864\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 411 (993.0MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:23:55,865\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:23:55,865\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:23:55,866\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:55,866\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:24:05,859\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:24:05,860\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:24:05,861\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 6.2GiB/93.1GiB object store\n2026-07-06 19:24:05,861\tINFO logging_progress.py:181 -- \n2026-07-06 19:24:05,862\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:24:05,863\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:05,863\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:24:05,863\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:05,864\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:24:05,864\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:24:05,864\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 5.0GiB object store\n2026-07-06 19:24:05,864\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 500/1000\n2026-07-06 19:24:05,865\tINFO logging_progress.py:233 -- Tasks: 18; Actors: 9; Queued blocks: 482 (4.7GiB); Resources: 54.0 CPU, 1.2GiB object store; [all objects local]\n2026-07-06 19:24:05,865\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:24:05,866\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 500 (1.1GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:05,866\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:24:05,867\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:24:05,867\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:05,867\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:24:15,902\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:24:15,903\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:24:15,904\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 5.6GiB/93.1GiB object store\n2026-07-06 19:24:15,905\tINFO logging_progress.py:181 -- \n2026-07-06 19:24:15,905\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:24:15,906\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:15,906\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:24:15,907\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:15,907\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:24:15,908\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:24:15,908\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 4.2GiB object store\n2026-07-06 19:24:15,909\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 577/1000\n2026-07-06 19:24:15,909\tINFO logging_progress.py:233 -- Tasks: 18; Actors: 9; Queued blocks: 405 (4.1GiB); Resources: 54.0 CPU, 1.3GiB object store; [all objects local]\n2026-07-06 19:24:15,910\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:24:15,911\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 577 (1.3GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:15,911\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:24:15,912\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:24:15,913\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:15,913\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:24:25,905\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:24:25,907\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:24:25,909\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 4.9GiB/93.1GiB object store\n2026-07-06 19:24:25,910\tINFO logging_progress.py:181 -- \n2026-07-06 19:24:25,911\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:24:25,912\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:25,912\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:24:25,913\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:25,914\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:24:25,914\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:24:25,915\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 3.4GiB object store\n2026-07-06 19:24:25,916\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 655/1000\n2026-07-06 19:24:25,916\tINFO logging_progress.py:233 -- Tasks: 18; Actors: 9; Queued blocks: 327 (3.1GiB); Resources: 54.0 CPU, 1.5GiB object store; [all objects local]\n2026-07-06 19:24:25,917\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:24:25,919\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 655 (1.5GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:25,920\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:24:25,920\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:24:25,920\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:25,921\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:24:36,014\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:24:36,016\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:24:36,017\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 4.3GiB/93.1GiB object store\n2026-07-06 19:24:36,018\tINFO logging_progress.py:181 -- \n2026-07-06 19:24:36,019\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:24:36,020\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:36,021\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:24:36,021\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:36,022\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:24:36,023\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:24:36,023\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 2.5GiB object store\n2026-07-06 19:24:36,024\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 735/1000\n2026-07-06 19:24:36,025\tINFO logging_progress.py:233 -- Tasks: 17; Actors: 9; Queued blocks: 248 (2.3GiB); Resources: 54.0 CPU, 1.7GiB object store; [all objects local]\n2026-07-06 19:24:36,026\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:24:36,026\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 735 (1.7GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:36,027\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:24:36,028\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:24:36,028\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:36,029\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:24:46,121\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:24:46,123\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:24:46,125\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 3.7GiB/93.1GiB object store\n2026-07-06 19:24:46,126\tINFO logging_progress.py:181 -- \n2026-07-06 19:24:46,127\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:24:46,128\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:46,128\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:24:46,130\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:46,131\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:24:46,131\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:24:46,131\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 1.8GiB object store\n2026-07-06 19:24:46,132\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 823/1000\n2026-07-06 19:24:46,132\tINFO logging_progress.py:233 -- Tasks: 17; Actors: 9; Queued blocks: 160 (1.4GiB); Resources: 54.0 CPU, 1.9GiB object store; [all objects local]\n2026-07-06 19:24:46,132\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:24:46,132\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 823 (1.9GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:46,133\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:24:46,133\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:24:46,133\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:46,134\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:24:56,221\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:24:56,222\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:24:56,222\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 3.0GiB/93.1GiB object store\n2026-07-06 19:24:56,223\tINFO logging_progress.py:181 -- \n2026-07-06 19:24:56,224\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:24:56,225\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:56,225\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:24:56,225\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:56,226\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:24:56,226\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:24:56,226\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 958.7MiB object store\n2026-07-06 19:24:56,226\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 905/1000\n2026-07-06 19:24:56,227\tINFO logging_progress.py:233 -- Tasks: 17; Actors: 9; Queued blocks: 78 (801.3MiB); Resources: 54.0 CPU, 2.1GiB object store; [all objects local]\n2026-07-06 19:24:56,227\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:24:56,227\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 905 (2.1GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:56,227\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:24:56,228\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:24:56,228\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:56,228\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:25:06,333\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:25:06,334\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:25:06,335\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 2.5GiB/93.1GiB object store\n2026-07-06 19:25:06,335\tINFO logging_progress.py:181 -- \n2026-07-06 19:25:06,336\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:25:06,336\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:06,337\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:25:06,337\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:25:06,337\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:06,337\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:25:06,338\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 199.3MiB object store\n2026-07-06 19:25:06,338\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 991/1000\n2026-07-06 19:25:06,338\tINFO logging_progress.py:233 -- Tasks: 9; Actors: 9; Queued blocks: 0 (0.0B); Resources: 54.0 CPU, 2.3GiB object store; [all objects local]\n2026-07-06 19:25:06,338\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:25:06,339\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 991 (2.2GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:25:06,340\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:25:06,340\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:25:06,340\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:06,340\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:25:19,206\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:25:19,208\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:25:19,209\tINFO logging_progress.py:227 -- Active & requested resources: 6/64 CPU, 2.3GiB/93.1GiB object store\n2026-07-06 19:25:19,209\tINFO logging_progress.py:181 -- \n2026-07-06 19:25:19,210\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:25:19,211\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:19,211\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:25:19,213\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:25:19,214\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:19,215\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:25:19,216\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:19,217\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:25:19,217\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 6.0 CPU, 2.3GiB object store; [all objects local]\n2026-07-06 19:25:19,218\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:25:19,218\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:25:19,218\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:19,218\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:25:19,219\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:19,219\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:25:29,207\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:25:29,209\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:25:29,209\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:25:29,210\tINFO logging_progress.py:181 -- \n2026-07-06 19:25:29,210\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:25:29,210\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:29,211\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:25:29,211\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:25:29,211\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:29,212\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:25:29,212\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:29,212\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:25:29,213\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:25:29,213\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:25:29,213\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:25:29,214\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:29,214\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:25:29,214\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:25:29,215\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:25:39,210\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:25:39,214\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:25:39,216\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:25:39,218\tINFO logging_progress.py:181 -- \n2026-07-06 19:25:39,219\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:25:39,219\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:39,220\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:25:39,220\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:25:39,220\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:39,221\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:25:39,221\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:39,222\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:25:39,223\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:25:39,223\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:25:39,224\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:25:39,224\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:39,224\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:25:39,225\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:25:39,225\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:25:49,211\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:25:49,213\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:25:49,215\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:25:49,216\tINFO logging_progress.py:181 -- \n2026-07-06 19:25:49,216\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:25:49,217\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:49,218\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:25:49,219\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:25:49,220\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:49,220\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:25:49,221\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:49,221\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:25:49,221\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:25:49,222\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:25:49,222\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:25:49,223\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:49,223\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:25:49,223\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:25:49,224\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:25:59,211\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:25:59,213\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:25:59,214\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:25:59,214\tINFO logging_progress.py:181 -- \n2026-07-06 19:25:59,215\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:25:59,216\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:59,217\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:25:59,217\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:25:59,218\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:59,218\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:25:59,219\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:59,220\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:25:59,220\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:25:59,221\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:25:59,222\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:25:59,222\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:59,223\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:25:59,224\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:25:59,225\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:26:09,217\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:26:09,220\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:26:09,222\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:26:09,224\tINFO logging_progress.py:181 -- \n2026-07-06 19:26:09,224\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:26:09,225\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:09,225\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:09,226\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:26:09,227\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:09,227\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:26:09,228\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:09,229\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:26:09,229\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:26:09,230\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:09,231\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:26:09,232\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:09,233\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:26:09,235\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:26:09,236\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:26:19,225\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:26:19,229\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:26:19,231\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:26:19,233\tINFO logging_progress.py:181 -- \n2026-07-06 19:26:19,233\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:26:19,234\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:19,235\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:19,235\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:26:19,236\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:19,236\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:26:19,237\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:19,237\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:26:19,238\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:26:19,238\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:19,238\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:26:19,241\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:19,241\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:26:19,242\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:26:19,242\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:26:29,227\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:26:29,229\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:26:29,230\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:26:29,231\tINFO logging_progress.py:181 -- \n2026-07-06 19:26:29,233\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:26:29,234\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:29,235\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:29,236\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:26:29,236\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:29,238\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:26:29,239\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:29,239\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:26:29,240\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:26:29,241\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:29,242\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:26:29,243\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:29,243\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:26:29,243\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:26:29,243\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:26:39,234\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:26:39,237\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:26:39,239\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:26:39,240\tINFO logging_progress.py:181 -- \n2026-07-06 19:26:39,241\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:26:39,241\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:39,242\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:39,242\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:26:39,243\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:39,243\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:26:39,244\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:39,244\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:26:39,245\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:26:39,245\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:39,246\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:26:39,246\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:39,246\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:26:39,247\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:26:39,247\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:26:49,240\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:26:49,243\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:26:49,245\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:26:49,245\tINFO logging_progress.py:181 -- \n2026-07-06 19:26:49,246\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:26:49,246\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:49,247\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:49,248\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:26:49,248\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:49,250\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:26:49,251\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:49,254\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:26:49,255\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:26:49,257\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:49,257\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:26:49,258\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:49,259\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:26:49,260\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:26:49,260\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:26:59,246\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:26:59,248\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:26:59,250\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:26:59,252\tINFO logging_progress.py:181 -- \n2026-07-06 19:26:59,252\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:26:59,253\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:59,253\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:59,254\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:26:59,255\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:59,255\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:26:59,255\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:59,256\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:26:59,256\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:26:59,257\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:59,258\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:26:59,258\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:59,259\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:26:59,259\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:26:59,260\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:27:09,250\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:27:09,252\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:27:09,253\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:27:09,254\tINFO logging_progress.py:181 -- \n2026-07-06 19:27:09,255\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:27:09,255\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:09,256\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:09,258\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:27:09,258\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:09,259\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:27:09,260\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:09,262\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:27:09,262\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:27:09,263\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:09,263\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:27:09,264\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:09,265\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:27:09,266\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:27:09,267\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:27:19,264\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:27:19,266\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:27:19,267\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:27:19,268\tINFO logging_progress.py:181 -- \n2026-07-06 19:27:19,271\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:27:19,273\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:19,276\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:19,278\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:27:19,280\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:19,281\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:27:19,282\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:19,283\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:27:19,284\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:27:19,285\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:19,285\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:27:19,286\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:19,286\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:27:19,287\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:27:19,287\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:27:29,273\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:27:29,275\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:27:29,276\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:27:29,277\tINFO logging_progress.py:181 -- \n2026-07-06 19:27:29,279\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:27:29,280\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:29,280\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:29,281\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:27:29,281\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:29,281\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:27:29,282\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:29,282\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:27:29,282\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:27:29,283\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:29,283\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:27:29,283\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:29,284\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:27:29,284\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:27:29,284\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:27:39,280\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:27:39,282\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:27:39,283\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:27:39,287\tINFO logging_progress.py:181 -- \n2026-07-06 19:27:39,288\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:27:39,289\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:39,290\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:39,291\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:27:39,291\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:39,292\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:27:39,293\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:39,293\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:27:39,295\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:27:39,296\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:39,296\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:27:39,298\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:39,298\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:27:39,299\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:27:39,299\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:27:49,289\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:27:49,291\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:27:49,294\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:27:49,295\tINFO logging_progress.py:181 -- \n2026-07-06 19:27:49,297\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:27:49,298\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:49,299\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:49,299\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:27:49,300\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:49,300\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:27:49,301\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:49,301\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:27:49,301\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:27:49,302\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:49,303\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:27:49,303\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:49,303\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:27:49,304\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:27:49,304\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:27:59,290\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:27:59,293\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:27:59,295\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:27:59,298\tINFO logging_progress.py:181 -- \n2026-07-06 19:27:59,299\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:27:59,301\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:59,302\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:59,303\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:27:59,304\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:59,305\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:27:59,306\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:59,308\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:27:59,308\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:27:59,309\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:59,309\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:27:59,309\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:59,310\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:27:59,310\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:27:59,310\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:28:09,291\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:28:09,293\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:28:09,294\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:28:09,295\tINFO logging_progress.py:181 -- \n2026-07-06 19:28:09,296\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:28:09,296\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:28:09,297\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:28:09,298\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:28:09,298\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:28:09,299\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:28:09,300\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:28:09,300\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:28:09,301\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:28:09,302\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:28:09,302\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:28:09,303\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:28:09,303\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:28:09,304\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:28:09,304\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:28:17,072\tINFO streaming_executor.py:294 -- \u2714\ufe0f Dataset dataset_15_0 execution finished in 331.89 seconds\n" + }, + { + "name": "stdout", + "output_type": "stream", + "text": "[ActorPool(min=N, max=N)] 1000 videos, 1000 clip-chunks, 332.0s \u2014 3.01 vid/s\n" + } + ], + "source": "# \u2500\u2500 Pipeline Runs \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\nimport threading\nfrom ray.data import ActorPoolStrategy, TaskPoolStrategy\n\nray.shutdown()\nray.init(num_cpus=64) # 64-CPU machine\n\ntotal_cpus = int(ray.cluster_resources().get(\"CPU\", 0))\nmax_transcode = MAX_TRANSCODE_OVERRIDE\nprint(f\"Total CPUs: {total_cpus}, max transcode workers: {max_transcode}\")\nprint(f\"CPU pressure: {max_transcode * TRANSCODE_CPUS:.0f}/{total_cpus} = \"\n f\"{max_transcode * TRANSCODE_CPUS / total_cpus * 100:.0f}%\")\n\nclass TranscodeActor:\n def __call__(self, batch):\n return transcode(batch)\n\ndef _monitor_actors(snapshots, stop_event, interval=1.0):\n # Track active TranscodeActor count via CPU utilization.\n total_cpu = ray.cluster_resources().get(\"CPU\", 64)\n t0 = time.perf_counter()\n while not stop_event.is_set():\n try:\n avail = ray.available_resources().get(\"CPU\", total_cpu)\n busy = max(0.0, total_cpu - avail)\n actor_est = int(round(busy / TRANSCODE_CPUS))\n ts = time.perf_counter() - t0\n snapshots.append((ts, busy, actor_est))\n except Exception:\n pass\n stop_event.wait(interval)\n\ndef run_pipeline(transcode_compute, label):\n shutil.rmtree(OUTPUT_DIR, ignore_errors=True)\n\n snapshots = []\n stop_event = threading.Event()\n monitor_thread = threading.Thread(\n target=_monitor_actors, args=(snapshots, stop_event), daemon=True\n )\n\n t0 = time.perf_counter()\n ds = (\n ray.data.from_items([{\"seed\": None}])\n .map_batches(ls_videos, batch_size=1) # single task\n .repartition(VIDEO_LIMIT)\n .map_batches(read_and_probe, batch_size=1, num_cpus=1)\n .map_batches(split_fixed_stride, batch_size=1, num_cpus=1)\n .map_batches(TranscodeActor, batch_size=1, num_cpus=TRANSCODE_CPUS,\n compute=transcode_compute)\n .repartition(VIDEO_LIMIT * 20)\n .map_batches(write_clips, batch_size=1, num_cpus=WRITE_CPUS)\n )\n monitor_thread.start()\n results = ds.take_all()\n stop_event.set()\n monitor_thread.join(timeout=3)\n elapsed = time.perf_counter() - t0\n\n n_chunks = len(results)\n n_videos = len(set(r[\"path\"] for r in results))\n print(f\"[{label}] {n_videos} videos, {n_chunks} clip-chunks, \"\n f\"{elapsed:.1f}s \u2014 {n_videos/elapsed:.2f} vid/s\")\n return elapsed, snapshots\n\nelapsed1, snaps1 = run_pipeline(\n ActorPoolStrategy(min_size=1, max_size=max_transcode, initial_size=max_transcode),\n label=\"ActorPool(min=1, max=N, initial=N)\"\n)\n\nelapsed2, snaps2 = run_pipeline(\n ActorPoolStrategy(min_size=max_transcode, max_size=max_transcode),\n label=\"ActorPool(min=N, max=N)\"\n)" + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "041eb728", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "\n=== Run 1: ActorPool(min=1, max=N, initial=N) ===\n 0.0s actors~ 0 cpu_busy= 0 \n 1.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 2.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 3.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 4.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 5.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 6.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 7.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 8.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 9.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 10.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 11.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 12.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 13.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 14.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 15.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 16.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 17.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 18.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 19.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 20.1s actors~ 0 cpu_busy= 0 \n 21.1s actors~ 9 cpu_busy= 52 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 22.1s actors~ 8 cpu_busy= 46 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 23.1s actors~ 7 cpu_busy= 43 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 24.1s actors~ 6 cpu_busy= 38 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 25.1s actors~ 6 cpu_busy= 39 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 26.1s actors~ 6 cpu_busy= 37 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 27.1s actors~ 6 cpu_busy= 36 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 28.1s actors~ 8 cpu_busy= 47 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 29.1s actors~ 8 cpu_busy= 51 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 30.1s actors~ 8 cpu_busy= 48 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 31.1s actors~ 6 cpu_busy= 37 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 32.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 33.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 34.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 35.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 36.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 37.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 38.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 39.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 40.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 41.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 42.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 43.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 44.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 45.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 46.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 47.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 48.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 49.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 50.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 51.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 52.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 53.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 54.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 55.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 56.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 57.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 58.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 59.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 60.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 61.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 62.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 63.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 64.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 65.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 66.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 67.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 68.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 69.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 70.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 71.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 72.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 73.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 74.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 75.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 76.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 77.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 78.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 79.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 80.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 81.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 82.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 83.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 84.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 85.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 86.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 87.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 88.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 89.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 90.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 91.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 92.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 93.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 94.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 95.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 96.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 97.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 98.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 99.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 100.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 101.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 102.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 103.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 104.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 105.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 106.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 107.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 108.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 109.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 110.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 111.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 112.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 113.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 114.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 115.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 116.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 117.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 118.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 119.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 120.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 121.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 122.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 123.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 124.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 125.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 126.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 127.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 128.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 129.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 130.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 131.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 132.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 133.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 134.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 135.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 136.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 137.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 138.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 139.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 140.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 141.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 142.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 143.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 144.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 145.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 146.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 147.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 148.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 149.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 150.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 151.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 152.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 153.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 154.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 155.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 156.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 157.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 158.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 159.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 160.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 161.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 162.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 163.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 164.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 165.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 166.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 167.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 168.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 169.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 170.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 171.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 172.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 173.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 174.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 175.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 176.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 177.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 178.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 179.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 180.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 181.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 182.5s actors~ 4 cpu_busy= 24 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 183.5s actors~ 2 cpu_busy= 12 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 184.5s actors~ 1 cpu_busy= 6 \u2588\u2588\u2588\u2588\u2588\u2588\n 185.8s actors~ 2 cpu_busy= 13 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 186.9s actors~ 0 cpu_busy= 0 \n 187.9s actors~ 0 cpu_busy= 0 \n 188.9s actors~ 0 cpu_busy= 0 \n 189.9s actors~ 0 cpu_busy= 0 \n 190.9s actors~ 0 cpu_busy= 0 \n 191.9s actors~ 0 cpu_busy= 0 \n 192.9s actors~10 cpu_busy= 62 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 193.9s actors~10 cpu_busy= 58 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 194.9s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 195.9s actors~ 9 cpu_busy= 56 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 196.9s actors~ 8 cpu_busy= 47 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 197.9s actors~ 7 cpu_busy= 41 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 198.9s actors~ 6 cpu_busy= 37 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 199.9s actors~ 4 cpu_busy= 26 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 200.9s actors~ 4 cpu_busy= 22 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 202.0s actors~ 3 cpu_busy= 20 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 203.0s actors~ 1 cpu_busy= 6 \u2588\u2588\u2588\u2588\u2588\u2588\n 204.0s actors~ 0 cpu_busy= 0 \n 205.0s actors~ 0 cpu_busy= 0 \n 206.0s actors~ 0 cpu_busy= 0 \n 207.0s actors~ 0 cpu_busy= 0 \n 208.0s actors~ 0 cpu_busy= 0 \n 209.1s actors~ 0 cpu_busy= 0 \n 210.1s actors~ 0 cpu_busy= 0 \n 211.1s actors~ 0 cpu_busy= 0 \n 212.1s actors~ 0 cpu_busy= 0 \n 213.1s actors~ 0 cpu_busy= 0 \n 214.2s actors~ 0 cpu_busy= 0 \n 215.2s actors~ 0 cpu_busy= 0 \n 216.2s actors~ 0 cpu_busy= 0 \n 217.2s actors~ 0 cpu_busy= 0 \n 218.2s actors~ 0 cpu_busy= 0 \n 219.2s actors~ 0 cpu_busy= 0 \n 220.2s actors~ 0 cpu_busy= 0 \n 221.2s actors~ 0 cpu_busy= 0 \n 222.2s actors~ 0 cpu_busy= 0 \n 223.3s actors~ 0 cpu_busy= 0 \n 224.3s actors~ 0 cpu_busy= 0 \n 225.3s actors~ 0 cpu_busy= 0 \n 226.3s actors~ 0 cpu_busy= 0 \n 227.3s actors~ 0 cpu_busy= 0 \n 228.3s actors~ 0 cpu_busy= 0 \n 229.4s actors~ 0 cpu_busy= 0 \n 230.4s actors~ 0 cpu_busy= 0 \n 231.4s actors~ 0 cpu_busy= 0 \n 232.4s actors~ 0 cpu_busy= 0 \n 233.4s actors~ 0 cpu_busy= 0 \n 234.4s actors~ 0 cpu_busy= 0 \n 235.4s actors~ 0 cpu_busy= 0 \n 236.4s actors~ 0 cpu_busy= 0 \n 237.5s actors~ 0 cpu_busy= 0 \n 238.5s actors~ 0 cpu_busy= 0 \n 239.5s actors~ 0 cpu_busy= 0 \n 240.5s actors~ 0 cpu_busy= 0 \n 241.5s actors~ 0 cpu_busy= 0 \n 242.5s actors~ 0 cpu_busy= 0 \n 243.5s actors~ 0 cpu_busy= 0 \n 244.5s actors~ 0 cpu_busy= 0 \n 245.5s actors~ 0 cpu_busy= 0 \n 246.5s actors~ 0 cpu_busy= 0 \n 247.5s actors~ 0 cpu_busy= 0 \n 248.5s actors~ 0 cpu_busy= 0 \n 249.6s actors~ 0 cpu_busy= 0 \n 250.6s actors~ 0 cpu_busy= 0 \n 251.6s actors~ 0 cpu_busy= 0 \n 252.6s actors~ 0 cpu_busy= 0 \n 253.6s actors~ 0 cpu_busy= 0 \n 254.6s actors~ 0 cpu_busy= 0 \n 255.6s actors~ 0 cpu_busy= 0 \n 256.6s actors~ 0 cpu_busy= 0 \n 257.7s actors~ 0 cpu_busy= 0 \n 258.7s actors~ 0 cpu_busy= 0 \n 259.7s actors~ 0 cpu_busy= 0 \n 260.7s actors~ 0 cpu_busy= 0 \n 261.7s actors~ 0 cpu_busy= 0 \n 262.7s actors~ 0 cpu_busy= 0 \n 263.7s actors~ 0 cpu_busy= 0 \n 264.8s actors~ 0 cpu_busy= 0 \n 265.8s actors~ 0 cpu_busy= 0 \n 266.8s actors~ 0 cpu_busy= 0 \n 267.8s actors~ 0 cpu_busy= 0 \n 268.9s actors~ 0 cpu_busy= 0 \n 269.9s actors~ 0 cpu_busy= 0 \n 270.9s actors~ 0 cpu_busy= 0 \n 271.9s actors~ 0 cpu_busy= 0 \n 272.9s actors~ 0 cpu_busy= 0 \n 273.9s actors~ 0 cpu_busy= 0 \n 274.9s actors~ 0 cpu_busy= 0 \n 276.0s actors~ 0 cpu_busy= 0 \n 277.0s actors~ 0 cpu_busy= 0 \n 278.0s actors~ 0 cpu_busy= 0 \n 279.0s actors~ 0 cpu_busy= 0 \n 280.0s actors~ 0 cpu_busy= 0 \n 281.0s actors~ 0 cpu_busy= 0 \n 282.0s actors~ 0 cpu_busy= 0 \n 283.1s actors~ 0 cpu_busy= 0 \n 284.1s actors~ 0 cpu_busy= 0 \n 285.1s actors~ 0 cpu_busy= 0 \n 286.1s actors~ 0 cpu_busy= 0 \n 287.1s actors~ 0 cpu_busy= 0 \n 288.1s actors~ 0 cpu_busy= 0 \n 289.1s actors~ 0 cpu_busy= 0 \n 290.2s actors~ 0 cpu_busy= 0 \n 291.2s actors~ 0 cpu_busy= 0 \n 292.2s actors~ 0 cpu_busy= 0 \n 293.2s actors~ 0 cpu_busy= 0 \n 294.2s actors~ 0 cpu_busy= 0 \n 295.2s actors~ 0 cpu_busy= 0 \n 296.2s actors~ 0 cpu_busy= 0 \n 297.2s actors~ 0 cpu_busy= 0 \n 298.2s actors~ 0 cpu_busy= 0 \n 299.2s actors~ 0 cpu_busy= 0 \n 300.2s actors~ 0 cpu_busy= 0 \n 301.3s actors~ 0 cpu_busy= 0 \n 302.3s actors~ 0 cpu_busy= 0 \n 303.3s actors~ 0 cpu_busy= 0 \n 304.3s actors~ 0 cpu_busy= 0 \n 305.3s actors~ 0 cpu_busy= 0 \n 306.3s actors~ 0 cpu_busy= 0 \n 307.4s actors~ 0 cpu_busy= 0 \n 308.4s actors~ 0 cpu_busy= 0 \n 309.4s actors~ 0 cpu_busy= 0 \n 310.5s actors~ 0 cpu_busy= 0 \n 311.5s actors~ 0 cpu_busy= 0 \n 312.5s actors~ 0 cpu_busy= 0 \n 313.5s actors~ 0 cpu_busy= 0 \n 314.5s actors~ 0 cpu_busy= 0 \n 315.5s actors~ 0 cpu_busy= 0 \n 316.5s actors~ 0 cpu_busy= 0 \n 317.6s actors~ 0 cpu_busy= 0 \n 318.6s actors~ 0 cpu_busy= 0 \n 319.6s actors~ 0 cpu_busy= 0 \n 320.6s actors~ 0 cpu_busy= 0 \n 321.6s actors~ 0 cpu_busy= 0 \n 322.7s actors~ 0 cpu_busy= 0 \n 323.7s actors~ 0 cpu_busy= 0 \n 324.7s actors~ 0 cpu_busy= 0 \n 325.7s actors~ 0 cpu_busy= 0 \n 326.7s actors~ 0 cpu_busy= 0 \n 327.8s actors~ 0 cpu_busy= 0 \n 328.8s actors~ 0 cpu_busy= 0 \n 329.8s actors~ 0 cpu_busy= 0 \n 330.8s actors~ 0 cpu_busy= 0 \n 331.8s actors~ 0 cpu_busy= 0 \n 332.8s actors~ 0 cpu_busy= 0 \n 333.9s actors~ 0 cpu_busy= 0 \n 334.9s actors~ 0 cpu_busy= 0 \n 335.9s actors~ 0 cpu_busy= 0 \n 336.9s actors~ 0 cpu_busy= 0 \n 337.9s actors~ 0 cpu_busy= 0 \n 339.0s actors~ 0 cpu_busy= 0 \n 340.0s actors~ 0 cpu_busy= 0 \n 341.0s actors~ 0 cpu_busy= 0 \n 342.0s actors~ 0 cpu_busy= 0 \n 343.0s actors~ 0 cpu_busy= 0 \n 344.1s actors~ 0 cpu_busy= 0 \n 345.1s actors~ 0 cpu_busy= 0 \n 346.1s actors~ 0 cpu_busy= 0 \n 347.1s actors~ 0 cpu_busy= 0 \n 348.1s actors~ 0 cpu_busy= 0 \n 349.1s actors~ 0 cpu_busy= 0 \n 350.1s actors~ 0 cpu_busy= 0 \n 351.1s actors~ 0 cpu_busy= 0 \n 352.2s actors~ 0 cpu_busy= 0 \n 353.2s actors~ 0 cpu_busy= 0 \n 354.2s actors~ 0 cpu_busy= 0 \n 355.2s actors~ 0 cpu_busy= 0 \n 356.2s actors~ 0 cpu_busy= 0 \n 357.2s actors~ 0 cpu_busy= 0 \n 358.2s actors~ 0 cpu_busy= 0 \n 359.2s actors~ 0 cpu_busy= 0 \n peak=10 avg=3.9 zero-actor-samples=162/357\n\n=== Run 2: ActorPool(min=N, max=N) ===\n 0.0s actors~ 0 cpu_busy= 0 \n 1.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 2.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 3.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 4.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 5.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 6.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 7.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 8.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 9.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 10.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 11.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 12.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 13.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 14.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 15.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 16.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 17.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 18.1s actors~ 0 cpu_busy= 0 \n 19.1s actors~10 cpu_busy= 57 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 20.1s actors~ 0 cpu_busy= 0 \n 21.1s actors~10 cpu_busy= 57 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 22.1s actors~ 0 cpu_busy= 0 \n 23.1s actors~ 9 cpu_busy= 56 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 24.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 25.1s actors~ 9 cpu_busy= 56 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 26.1s actors~ 9 cpu_busy= 56 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 27.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 28.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 29.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 30.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 31.1s actors~ 9 cpu_busy= 56 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 32.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 33.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 34.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 35.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 36.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 37.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 38.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 39.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 40.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 41.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 42.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 43.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 44.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 45.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 46.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 47.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 48.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 49.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 50.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 51.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 52.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 53.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 54.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 55.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 56.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 57.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 58.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 59.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 60.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 61.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 62.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 63.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 64.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 65.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 66.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 67.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 68.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 69.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 70.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 71.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 72.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 73.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 74.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 75.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 76.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 77.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 78.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 79.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 80.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 81.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 82.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 83.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 84.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 85.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 86.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 87.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 88.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 89.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 90.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 91.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 92.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 93.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 94.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 95.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 96.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 97.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 98.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 99.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 100.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 101.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 102.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 103.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 104.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 105.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 106.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 107.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 108.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 109.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 110.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 111.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 112.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 113.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 114.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 115.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 116.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 117.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 118.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 119.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 120.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 121.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 122.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 123.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 124.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 125.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 126.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 127.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 128.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 129.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 130.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 131.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 132.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 133.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 134.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 135.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 136.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 137.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 138.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 139.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 140.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 141.4s actors~ 8 cpu_busy= 48 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 142.4s actors~ 3 cpu_busy= 18 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 143.4s actors~ 1 cpu_busy= 6 \u2588\u2588\u2588\u2588\u2588\n 144.4s actors~ 1 cpu_busy= 6 \u2588\u2588\u2588\u2588\u2588\n 145.4s actors~ 0 cpu_busy= 0 \n 146.4s actors~ 0 cpu_busy= 0 \n 147.4s actors~ 1 cpu_busy= 4 \u2588\u2588\u2588\u2588\u2588\n 148.5s actors~ 0 cpu_busy= 0 \n 149.5s actors~ 0 cpu_busy= 0 \n 150.5s actors~ 0 cpu_busy= 0 \n 151.5s actors~ 0 cpu_busy= 0 \n 152.5s actors~ 0 cpu_busy= 0 \n 153.5s actors~ 0 cpu_busy= 0 \n 154.5s actors~ 0 cpu_busy= 0 \n 155.5s actors~ 4 cpu_busy= 23 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 156.5s actors~11 cpu_busy= 64 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 157.5s actors~ 0 cpu_busy= 0 \n 158.5s actors~10 cpu_busy= 60 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 159.5s actors~ 8 cpu_busy= 50 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 160.5s actors~ 4 cpu_busy= 26 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 161.5s actors~ 5 cpu_busy= 28 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 162.5s actors~ 3 cpu_busy= 19 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 163.5s actors~ 3 cpu_busy= 18 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 164.5s actors~ 1 cpu_busy= 4 \u2588\u2588\u2588\u2588\u2588\n 165.5s actors~ 0 cpu_busy= 0 \n 166.6s actors~ 0 cpu_busy= 0 \n 167.6s actors~ 0 cpu_busy= 0 \n 168.6s actors~ 0 cpu_busy= 0 \n 169.6s actors~ 0 cpu_busy= 0 \n 170.6s actors~ 0 cpu_busy= 0 \n 171.6s actors~ 0 cpu_busy= 0 \n 172.6s actors~ 0 cpu_busy= 0 \n 173.6s actors~ 0 cpu_busy= 0 \n 174.6s actors~ 0 cpu_busy= 0 \n 175.7s actors~ 0 cpu_busy= 0 \n 176.7s actors~ 0 cpu_busy= 0 \n 177.7s actors~ 0 cpu_busy= 0 \n 178.7s actors~ 0 cpu_busy= 0 \n 179.7s actors~ 0 cpu_busy= 0 \n 180.7s actors~ 0 cpu_busy= 0 \n 181.7s actors~ 0 cpu_busy= 0 \n 182.7s actors~ 0 cpu_busy= 0 \n 183.8s actors~ 0 cpu_busy= 0 \n 184.8s actors~ 0 cpu_busy= 0 \n 185.8s actors~ 0 cpu_busy= 0 \n 186.8s actors~ 0 cpu_busy= 0 \n 187.8s actors~ 0 cpu_busy= 0 \n 188.8s actors~ 0 cpu_busy= 0 \n 189.8s actors~ 0 cpu_busy= 0 \n 190.8s actors~ 0 cpu_busy= 0 \n 191.9s actors~ 0 cpu_busy= 0 \n 192.9s actors~ 0 cpu_busy= 0 \n 193.9s actors~ 0 cpu_busy= 0 \n 194.9s actors~ 0 cpu_busy= 0 \n 195.9s actors~ 0 cpu_busy= 0 \n 196.9s actors~ 0 cpu_busy= 0 \n 197.9s actors~ 0 cpu_busy= 0 \n 198.9s actors~ 0 cpu_busy= 0 \n 200.0s actors~ 0 cpu_busy= 0 \n 201.0s actors~ 0 cpu_busy= 0 \n 202.0s actors~ 0 cpu_busy= 0 \n 203.0s actors~ 0 cpu_busy= 0 \n 204.0s actors~ 0 cpu_busy= 0 \n 205.0s actors~ 0 cpu_busy= 0 \n 206.0s actors~ 0 cpu_busy= 0 \n 207.0s actors~ 0 cpu_busy= 0 \n 208.1s actors~ 0 cpu_busy= 0 \n 209.1s actors~ 0 cpu_busy= 0 \n 210.1s actors~ 0 cpu_busy= 0 \n 211.1s actors~ 0 cpu_busy= 0 \n 212.1s actors~ 0 cpu_busy= 0 \n 213.1s actors~ 0 cpu_busy= 0 \n 214.1s actors~ 0 cpu_busy= 0 \n 215.1s actors~ 0 cpu_busy= 0 \n 216.2s actors~ 0 cpu_busy= 0 \n 217.2s actors~ 0 cpu_busy= 0 \n 218.2s actors~ 0 cpu_busy= 0 \n 219.2s actors~ 0 cpu_busy= 0 \n 220.2s actors~ 0 cpu_busy= 0 \n 221.2s actors~ 0 cpu_busy= 0 \n 222.2s actors~ 0 cpu_busy= 0 \n 223.2s actors~ 0 cpu_busy= 0 \n 224.3s actors~ 0 cpu_busy= 0 \n 225.3s actors~ 0 cpu_busy= 0 \n 226.3s actors~ 0 cpu_busy= 0 \n 227.3s actors~ 0 cpu_busy= 0 \n 228.3s actors~ 0 cpu_busy= 0 \n 229.3s actors~ 0 cpu_busy= 0 \n 230.3s actors~ 0 cpu_busy= 0 \n 231.3s actors~ 0 cpu_busy= 0 \n 232.3s actors~ 0 cpu_busy= 0 \n 233.4s actors~ 0 cpu_busy= 0 \n 234.4s actors~ 0 cpu_busy= 0 \n 235.4s actors~ 0 cpu_busy= 0 \n 236.4s actors~ 0 cpu_busy= 0 \n 237.4s actors~ 0 cpu_busy= 0 \n 238.4s actors~ 0 cpu_busy= 0 \n 239.4s actors~ 0 cpu_busy= 0 \n 240.4s actors~ 0 cpu_busy= 0 \n 241.5s actors~ 0 cpu_busy= 0 \n 242.5s actors~ 0 cpu_busy= 0 \n 243.5s actors~ 0 cpu_busy= 0 \n 244.5s actors~ 0 cpu_busy= 0 \n 245.5s actors~ 0 cpu_busy= 0 \n 246.5s actors~ 0 cpu_busy= 0 \n 247.5s actors~ 0 cpu_busy= 0 \n 248.6s actors~ 0 cpu_busy= 0 \n 249.6s actors~ 0 cpu_busy= 0 \n 250.6s actors~ 0 cpu_busy= 0 \n 251.6s actors~ 0 cpu_busy= 0 \n 252.6s actors~ 0 cpu_busy= 0 \n 253.6s actors~ 0 cpu_busy= 0 \n 254.6s actors~ 0 cpu_busy= 0 \n 255.6s actors~ 0 cpu_busy= 0 \n 256.6s actors~ 0 cpu_busy= 0 \n 257.7s actors~ 0 cpu_busy= 0 \n 258.7s actors~ 0 cpu_busy= 0 \n 259.7s actors~ 0 cpu_busy= 0 \n 260.7s actors~ 0 cpu_busy= 0 \n 261.7s actors~ 0 cpu_busy= 0 \n 262.7s actors~ 0 cpu_busy= 0 \n 263.7s actors~ 0 cpu_busy= 0 \n 264.8s actors~ 0 cpu_busy= 0 \n 265.8s actors~ 0 cpu_busy= 0 \n 266.8s actors~ 0 cpu_busy= 0 \n 267.8s actors~ 0 cpu_busy= 0 \n 268.8s actors~ 0 cpu_busy= 0 \n 269.8s actors~ 0 cpu_busy= 0 \n 270.8s actors~ 0 cpu_busy= 0 \n 271.8s actors~ 0 cpu_busy= 0 \n 272.9s actors~ 0 cpu_busy= 0 \n 273.9s actors~ 0 cpu_busy= 0 \n 274.9s actors~ 0 cpu_busy= 0 \n 275.9s actors~ 0 cpu_busy= 0 \n 276.9s actors~ 0 cpu_busy= 0 \n 277.9s actors~ 0 cpu_busy= 0 \n 278.9s actors~ 0 cpu_busy= 0 \n 279.9s actors~ 0 cpu_busy= 0 \n 280.9s actors~ 0 cpu_busy= 0 \n 281.9s actors~ 0 cpu_busy= 0 \n 282.9s actors~ 0 cpu_busy= 0 \n 284.0s actors~ 0 cpu_busy= 0 \n 285.0s actors~ 0 cpu_busy= 0 \n 286.0s actors~ 0 cpu_busy= 0 \n 287.0s actors~ 0 cpu_busy= 0 \n 288.0s actors~ 0 cpu_busy= 0 \n 289.0s actors~ 0 cpu_busy= 0 \n 290.0s actors~ 0 cpu_busy= 0 \n 291.0s actors~ 0 cpu_busy= 0 \n 292.0s actors~ 0 cpu_busy= 0 \n 293.0s actors~ 0 cpu_busy= 0 \n 294.0s actors~ 0 cpu_busy= 0 \n 295.0s actors~ 0 cpu_busy= 0 \n 296.0s actors~ 0 cpu_busy= 0 \n 297.0s actors~ 0 cpu_busy= 0 \n 298.0s actors~ 0 cpu_busy= 0 \n 299.0s actors~ 0 cpu_busy= 0 \n 300.1s actors~ 0 cpu_busy= 0 \n 301.1s actors~ 0 cpu_busy= 0 \n 302.1s actors~ 0 cpu_busy= 0 \n 303.1s actors~ 0 cpu_busy= 0 \n 304.1s actors~ 0 cpu_busy= 0 \n 305.1s actors~ 0 cpu_busy= 0 \n 306.1s actors~ 0 cpu_busy= 0 \n 307.1s actors~ 0 cpu_busy= 0 \n 308.2s actors~ 0 cpu_busy= 0 \n 309.2s actors~ 0 cpu_busy= 0 \n 310.2s actors~ 0 cpu_busy= 0 \n 311.2s actors~ 0 cpu_busy= 0 \n 312.2s actors~ 0 cpu_busy= 0 \n 313.2s actors~ 0 cpu_busy= 0 \n 314.2s actors~ 0 cpu_busy= 0 \n 315.2s actors~ 0 cpu_busy= 0 \n 316.3s actors~ 0 cpu_busy= 0 \n 317.3s actors~ 0 cpu_busy= 0 \n 318.3s actors~ 0 cpu_busy= 0 \n 319.3s actors~ 0 cpu_busy= 0 \n 320.3s actors~ 0 cpu_busy= 0 \n 321.3s actors~ 0 cpu_busy= 0 \n 322.3s actors~ 0 cpu_busy= 0 \n 323.3s actors~ 0 cpu_busy= 0 \n 324.4s actors~ 0 cpu_busy= 0 \n 325.4s actors~ 0 cpu_busy= 0 \n 326.4s actors~ 0 cpu_busy= 0 \n 327.4s actors~ 0 cpu_busy= 0 \n 328.4s actors~ 0 cpu_busy= 0 \n 329.4s actors~ 0 cpu_busy= 0 \n 330.4s actors~ 0 cpu_busy= 0 \n 331.4s actors~ 0 cpu_busy= 0 \n peak=11 avg=3.9 zero-actor-samples=179/330\n\n========================================================================\n SUMMARY\n========================================================================\n Strategy time(s) peak avg zero%\n ----------------------------------- -------- ------ ------ -------\n ActorPool(min=1, max=N, initial=N) 360.6 10 3.9 45.4%\n ActorPool(min=N, max=N) 332.0 11 3.9 54.2%\n\n Speedup (min=N vs min=1): 1.09x\n" + } + ], + "source": "def print_actor_trace(label, snapshots, width=60):\n if not snapshots:\n print(f\"[{label}] no snapshots captured\")\n return\n times = [s[0] for s in snapshots]\n busy = [s[1] for s in snapshots]\n actors = [s[2] for s in snapshots]\n peak = max(actors) if actors else 0\n if peak == 0:\n print(f\"[{label}] all snapshots show 0 actors (busy CPU always 0?)\")\n # show busy cpu trace anyway\n peak_b = max(busy) if busy else 1\n scale = width / max(peak_b, 1)\n for ts, b, a in zip(times, busy, actors):\n bar = \"\u2588\" * int(b * scale)\n print(f\" {ts:7.1f}s cpu_busy={b:4.0f} {bar}\")\n return\n scale = width / peak\n for ts, b, a in zip(times, busy, actors):\n bar = \"\u2588\" * int(a * scale)\n print(f\" {ts:7.1f}s actors~{a:2d} cpu_busy={b:4.0f} {bar}\")\n avg = sum(actors) / len(actors)\n zeros = sum(1 for a in actors if a == 0)\n print(f\" peak={peak} avg={avg:.1f} zero-actor-samples={zeros}/{len(actors)}\")\n\nprint(\"\\n=== Run 1: ActorPool(min=1, max=N, initial=N) ===\")\nprint_actor_trace(\"min=1\", snaps1)\n\nprint(\"\\n=== Run 2: ActorPool(min=N, max=N) ===\")\nprint_actor_trace(\"min=N\", snaps2)\n\nprint()\nprint(\"=\" * 72)\nprint(\" SUMMARY\")\nprint(\"=\" * 72)\npeak1 = max((s[2] for s in snaps1), default=0)\npeak2 = max((s[2] for s in snaps2), default=0)\navg1 = sum(s[2] for s in snaps1) / len(snaps1) if snaps1 else 0\navg2 = sum(s[2] for s in snaps2) / len(snaps2) if snaps2 else 0\nzero1 = sum(1 for s in snaps1 if s[2] == 0)\nzero2 = sum(1 for s in snaps2 if s[2] == 0)\nprint(f\" {'Strategy':<35} {'time(s)':>8} {'peak':>6} {'avg':>6} {'zero%':>7}\")\nprint(f\" {'-'*35} {'-'*8} {'-'*6} {'-'*6} {'-'*7}\")\nprint(f\" {'ActorPool(min=1, max=N, initial=N)':<35} {elapsed1:>8.1f} {peak1:>6} {avg1:>6.1f} {100*zero1/len(snaps1) if snaps1 else 0:>6.1f}%\")\nprint(f\" {'ActorPool(min=N, max=N)':<35} {elapsed2:>8.1f} {peak2:>6} {avg2:>6.1f} {100*zero2/len(snaps2) if snaps2 else 0:>6.1f}%\")\nspeedup = elapsed1 / elapsed2 if elapsed2 else 0\nprint(f\"\\n Speedup (min=N vs min=1): {speedup:.2f}x\")\n" + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "e025c556-5796-43d1-b07d-c5a8bbd0f924", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": "========================================================================\n OBSERVATION SUMMARY\n========================================================================\n\n Run 1 ActorPoolStrategy(initial_size=N, min_size=1, max_size=N):\n - Actor count dropped from 9 and stabilized around 7\n - Throughput: 2.77 vid/s (360.6s total)\n\n Run 2 ActorPoolStrategy(min_size=N, max_size=N):\n - Actor count stable at 9 throughout\n - Throughput: 3.01 vid/s (332.0s total)\n\n Expected: Run 1 >= Run 2 (same max actors).\n Observed: Run 1 ~9% slower.\n\n" + } + ], + "source": "# \u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\n# OBSERVATION\n# \u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\n#\n# We ran two configurations on a video transcoding pipeline:\n# Run 1: ActorPoolStrategy(initial_size=9, min_size=1, max_size=9)\n# Run 2: ActorPoolStrategy(min_size=9, max_size=9)\n#\n# Run 1 was slower despite having the same max actor count.\n# The actor trace shows the pool drops from 9 and stabilizes around 7,\n# while Run 2 stays at 9 throughout.\n#\n# We expect Run 1 to perform at least as well as Run 2.\n#\n# \u2500\u2500 Autoscaler log (Run 1, from ray-data debug log) \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n#\n# Scaled up actor pool by 9\n# Scaled down actor pool by 1 (running=8, then further to ~7)\n\nprint(\"=\" * 72)\nprint(\" OBSERVATION SUMMARY\")\nprint(\"=\" * 72)\nsummary = \"\"\"\n Run 1 ActorPoolStrategy(initial_size=N, min_size=1, max_size=N):\n - Actor count dropped from 9 and stabilized around 7\n - Throughput: 2.77 vid/s (360.6s total)\n\n Run 2 ActorPoolStrategy(min_size=N, max_size=N):\n - Actor count stable at 9 throughout\n - Throughput: 3.01 vid/s (332.0s total)\n\n Expected: Run 1 >= Run 2 (same max actors).\n Observed: Run 1 ~9% slower.\n\"\"\"\nprint(summary)\n" + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.13" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} \ No newline at end of file From 528e28c1166c093e92ceacfff491d772e66aa704 Mon Sep 17 00:00:00 2001 From: Weijia Chen Date: Mon, 6 Jul 2026 21:29:08 +0000 Subject: [PATCH 2/6] clean --- ray_actorpool_cascade_bug.ipynb | 2688 ++++++++++++++++++++++++++++++- 1 file changed, 2670 insertions(+), 18 deletions(-) diff --git a/ray_actorpool_cascade_bug.ipynb b/ray_actorpool_cascade_bug.ipynb index 1d25c9bb96..be60a7a26f 100644 --- a/ray_actorpool_cascade_bug.ipynb +++ b/ray_actorpool_cascade_bug.ipynb @@ -2,17 +2,39 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "0e1c4aa4-6fc1-43c2-831e-12d72d0935ba", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", - "text": "Ray version: 2.55.1\n" + "text": [ + "Ray version: 2.55.1\n" + ] } ], - "source": "# Ray Data ActorPool Underutilization Reproducer\n# ================================================\n# Reproduces: https://github.com/ray-project/ray/issues/XXXXX\n#\n# Shows that ActorPoolStrategy(initial_size=N, min_size=1) underutilizes\n# the actor pool and delivers lower throughput than\n# ActorPoolStrategy(min_size=N, max_size=N), even though both configurations\n# have the same maximum number of actors.\n#\n# Tested on: Ray 2.55.1\n\nimport ray\nimport ray.data\nimport time, os, pprint, shutil, threading\nfrom collections import Counter\nfrom dataclasses import dataclass\n\nprint(f\"Ray version: {ray.__version__}\")\n" + "source": [ + "# Ray Data ActorPool Underutilization Reproducer\n", + "# ================================================\n", + "# Reproduces: https://github.com/ray-project/ray/issues/XXXXX\n", + "#\n", + "# Shows that ActorPoolStrategy(min_size=1, max_size=N, initial_size=N) underutilizes\n", + "# the actor pool and delivers lower throughput than\n", + "# ActorPoolStrategy(min_size=N, max_size=N), even though both configurations\n", + "# have the same maximum number of actors.\n", + "#\n", + "# Tested on: Ray 2.55.1\n", + "\n", + "import shutil\n", + "import threading\n", + "import time\n", + "\n", + "import ray\n", + "import ray.data\n", + "\n", + "print(f\"Ray version: {ray.__version__}\")" + ] }, { "cell_type": "code", @@ -20,7 +42,14 @@ "id": "922f29ed-5b0e-4e41-9f3a-4d9c12c040a9", "metadata": {}, "outputs": [], - "source": "# \u2500\u2500 Pipeline Configuration \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\nVIDEO_DIR = \"/raid/curator-team/datasets/openvid-1m/video\"\nOUTPUT_DIR = \"/raid/weijiac/tmp/raydata_transcode_test\"\nVIDEO_LIMIT = 1000 # number of videos to process\nTRANSCODE_CPUS = 6.0 # CPUs reserved per TranscodeActor\nMAX_TRANSCODE_OVERRIDE = 9 # set to reproduce the observed underutilization run\n" + "source": [ + "# ── Pipeline Configuration ────────────────────────────────────────────\n", + "VIDEO_DIR = \"/raid/curator-team/datasets/openvid-1m/video\"\n", + "OUTPUT_DIR = \"/raid/weijiac/tmp/raydata_transcode_test\"\n", + "VIDEO_LIMIT = 1000 # number of videos to process\n", + "TRANSCODE_CPUS = 6.0 # CPUs reserved per TranscodeActor\n", + "MAX_TRANSCODE_OVERRIDE = 9 # set to reproduce the observed underutilization run" + ] }, { "cell_type": "code", @@ -28,7 +57,311 @@ "id": "c16ab467", "metadata": {}, "outputs": [], - "source": "import subprocess, tempfile, json as _json, uuid, shutil\nfrom pathlib import Path\nfrom concurrent.futures import ThreadPoolExecutor\n\nCLIP_LEN_S = 10.0\nMIN_CLIP_LEN_S = 2.0\nENCODE_BATCH_SIZE = 16\nENCODER = \"libopenh264\"\nENCODER_THREADS = 1\n# TRANSCODE_CPUS set in cell 1\nWRITE_CPUS = 0.25\nCLIPS_PER_CHUNK = 32\nCHUNK_SIZE_S = CLIPS_PER_CHUNK * 8 * CLIP_LEN_S\n\nVIDEO_EXTENSIONS = (\".mp4\", \".mov\", \".avi\", \".mkv\", \".webm\")\n\n\ndef ls_videos(batch):\n # Simulate slow upstream I/O (e.g. S3/NFS file listing, large dataset scan).\n import time as _time\n _time.sleep(15)\n paths = []\n for ext in VIDEO_EXTENSIONS:\n paths.extend(Path(VIDEO_DIR).rglob(f\"*{ext}\"))\n paths = sorted(str(p) for p in paths)[:VIDEO_LIMIT]\n return {\"path\": paths}\n\ndef read_and_probe(batch):\n out = {k: [] for k in [\"path\", \"bytes\", \"duration\", \"fps\", \"num_frames\",\n \"width\", \"height\", \"video_codec\", \"pixel_format\",\n \"audio_codec\", \"bit_rate_k\"]}\n for path in batch[\"path\"]:\n raw = Path(path).read_bytes()\n with tempfile.NamedTemporaryFile(suffix=\".mp4\", delete=False) as tmp:\n tmp.write(raw)\n tmp_path = tmp.name\n try:\n result = subprocess.run(\n [\"ffprobe\", \"-v\", \"error\", \"-show_format\", \"-show_streams\",\n \"-of\", \"json\", tmp_path],\n stdout=subprocess.PIPE, stderr=subprocess.PIPE, check=True,\n )\n finally:\n Path(tmp_path).unlink(missing_ok=True)\n info = _json.loads(result.stdout)\n vs = next(s for s in info[\"streams\"] if s[\"codec_type\"] == \"video\")\n audio_codec = next((s[\"codec_name\"] for s in info[\"streams\"]\n if s[\"codec_type\"] == \"audio\"), None)\n num, den = map(int, vs[\"avg_frame_rate\"].split(\"/\"))\n fps = num / den\n duration = float(vs[\"duration\"]) if \"duration\" in vs else float(info[\"format\"][\"duration\"])\n bit_rate_k = int(int(vs[\"bit_rate\"]) / 1024) if \"bit_rate\" in vs else 2000\n out[\"path\"].append(path)\n out[\"bytes\"].append(raw)\n out[\"duration\"].append(duration)\n out[\"fps\"].append(fps)\n out[\"num_frames\"].append(int(duration * fps))\n out[\"width\"].append(int(vs[\"width\"]))\n out[\"height\"].append(int(vs[\"height\"]))\n out[\"video_codec\"].append(vs[\"codec_name\"])\n out[\"pixel_format\"].append(vs[\"pix_fmt\"])\n out[\"audio_codec\"].append(audio_codec)\n out[\"bit_rate_k\"].append(bit_rate_k)\n return out\n\ndef split_fixed_stride(batch):\n out = {k: [] for k in list(batch.keys()) + [\"clips\"]}\n for i in range(len(batch[\"path\"])):\n duration = batch[\"duration\"][i]\n clips, t = [], 0.0\n while t < duration:\n end = min(t + CLIP_LEN_S, duration)\n if end - t >= MIN_CLIP_LEN_S:\n clips.append((t, end))\n t += CLIP_LEN_S\n for k in batch.keys():\n out[k].append(batch[k][i])\n out[\"clips\"].append(clips)\n return out\n\ndef _split_clips_into_chunks(clips_with_ids):\n chunks, cur_chunk, cur_dur = [], [], 0.0\n for item in clips_with_ids:\n (s, e), cid = item\n cur_chunk.append(item)\n cur_dur += e - s\n if cur_dur >= CHUNK_SIZE_S:\n chunks.append(cur_chunk)\n cur_chunk, cur_dur = [], 0.0\n if cur_chunk:\n chunks.append(cur_chunk)\n return chunks\n\ndef transcode(batch):\n out = {\"path\": [], \"clip_chunk_index\": [], \"num_total_clips\": [],\n \"num_clip_chunks\": [], \"clips\": [], \"clip_bytes_map\": [],\n \"width\": [], \"height\": [], \"fps\": [], \"num_frames\": [],\n \"video_codec\": [], \"pixel_format\": [], \"audio_codec\": [], \"bit_rate_k\": []}\n for i, path in enumerate(batch[\"path\"]):\n # Ray Data passes batch values as numpy arrays \u2014 convert to Python types\n clips = [(float(s), float(e)) for s, e in batch[\"clips\"][i]]\n if len(clips) == 0:\n continue\n pix_fmt = str(batch[\"pixel_format\"][i]) if batch[\"pixel_format\"][i] is not None else \"\"\n force_pix_fmt = \"10le\" in pix_fmt or \"10be\" in pix_fmt\n with tempfile.TemporaryDirectory() as tmp_dir:\n tmp = Path(tmp_dir)\n (tmp / \"input.mp4\").write_bytes(bytes(batch[\"bytes\"][i]))\n fps = float(batch[\"fps\"][i])\n clip_ids = [\n str(uuid.uuid5(uuid.NAMESPACE_URL, f\"{path}_{int(s*fps)}_{int(e*fps)}\"))\n for s, e in clips\n ]\n for b in range(0, len(clips), ENCODE_BATCH_SIZE):\n b_clips = clips[b:b+ENCODE_BATCH_SIZE]\n b_ids = clip_ids[b:b+ENCODE_BATCH_SIZE]\n cmd = [\"ffmpeg\", \"-hide_banner\", \"-loglevel\", \"error\"]\n for j, (start, end) in enumerate(b_clips):\n cmd += [\"-threads\", str(ENCODER_THREADS),\n \"-ss\", str(start), \"-to\", str(end), \"-i\", \"input.mp4\",\n \"-map\", f\"{j}:v:0\", \"-c:v\", ENCODER]\n if force_pix_fmt:\n cmd += [\"-pix_fmt\", \"yuv420p\"]\n cmd += [\"-threads\", str(ENCODER_THREADS),\n \"-map\", f\"{j}:a:0?\", \"-c:a\", \"copy\", f\"{b_ids[j]}.mp4\"]\n subprocess.check_output(cmd, cwd=tmp, stderr=subprocess.STDOUT)\n clip_bytes = {cid: (tmp / f\"{cid}.mp4\").read_bytes()\n for cid in clip_ids if (tmp / f\"{cid}.mp4\").exists()}\n clip_chunks = _split_clips_into_chunks(list(zip(clips, clip_ids))) # [(s,e), cid] pairs\n for chunk_idx, chunk in enumerate(clip_chunks):\n chunk_clips = [(s, e) for (s, e), _ in chunk]\n chunk_ids = [cid for _, cid in chunk]\n out[\"path\"].append(path)\n out[\"clip_chunk_index\"].append(chunk_idx)\n out[\"num_total_clips\"].append(len(clips))\n out[\"num_clip_chunks\"].append(len(clip_chunks))\n out[\"clips\"].append(list(zip(chunk_ids, chunk_clips)))\n out[\"clip_bytes_map\"].append({cid: clip_bytes[cid] for cid in chunk_ids if cid in clip_bytes})\n for k in [\"width\", \"height\", \"fps\", \"num_frames\", \"video_codec\",\n \"pixel_format\", \"audio_codec\", \"bit_rate_k\"]:\n out[k].append(batch[k][i])\n return out\n\ndef _probe_clip(clip_bytes):\n with tempfile.NamedTemporaryFile(suffix=\".mp4\", delete=False) as tmp:\n tmp.write(clip_bytes)\n tmp_path = tmp.name\n try:\n result = subprocess.run(\n [\"ffprobe\", \"-v\", \"error\", \"-show_streams\", \"-of\", \"json\", tmp_path],\n stdout=subprocess.PIPE, stderr=subprocess.PIPE, check=True,\n )\n finally:\n Path(tmp_path).unlink(missing_ok=True)\n vs = next(s for s in _json.loads(result.stdout)[\"streams\"] if s[\"codec_type\"] == \"video\")\n num, den = map(int, vs[\"avg_frame_rate\"].split(\"/\"))\n return {\"width\": int(vs[\"width\"]), \"height\": int(vs[\"height\"]),\n \"framerate\": num/den, \"num_frames\": int(vs.get(\"nb_frames\", 0)),\n \"video_codec\": vs[\"codec_name\"], \"num_bytes\": len(clip_bytes)}\n\ndef write_clips(batch):\n clips_dir = Path(OUTPUT_DIR) / \"clips\"\n metas_dir = Path(OUTPUT_DIR) / \"metas\" / \"v0\"\n videos_dir = Path(OUTPUT_DIR) / \"processed_videos\"\n chunks_dir = Path(OUTPUT_DIR) / \"processed_clip_chunks\"\n for d in [clips_dir, metas_dir, videos_dir, chunks_dir]:\n d.mkdir(parents=True, exist_ok=True)\n\n def write_one_chunk(i):\n path = batch[\"path\"][i]\n clip_bytes_map = batch[\"clip_bytes_map\"][i]\n chunk_clips = [(str(cid), (float(s), float(e))) for cid, (s, e) in batch[\"clips\"][i]]\n chunk_idx = int(batch[\"clip_chunk_index\"][i])\n vmeta = {\n \"width\": int(batch[\"width\"][i]),\n \"height\": int(batch[\"height\"][i]),\n \"fps\": float(batch[\"fps\"][i]),\n \"num_frames\": int(batch[\"num_frames\"][i]),\n \"video_codec\": str(batch[\"video_codec\"][i]),\n \"pixel_format\": str(batch[\"pixel_format\"][i]),\n \"audio_codec\": str(batch[\"audio_codec\"][i]) if batch[\"audio_codec\"][i] is not None else None,\n \"bit_rate_k\": int(batch[\"bit_rate_k\"][i]),\n }\n num_transcoded, total_dur, max_dur = 0, 0.0, 0.0\n with ThreadPoolExecutor(max_workers=6) as ex:\n futures = []\n for cid, (start, end) in chunk_clips:\n cb = clip_bytes_map.get(cid)\n if not cb:\n continue\n futures.append(ex.submit((clips_dir / f\"{cid}.mp4\").write_bytes, cb))\n span_dur = end - start\n clip_meta = {\n \"span_uuid\": cid, \"source_video\": path,\n \"duration_span\": [start, end],\n \"width_source\": vmeta[\"width\"], \"height_source\": vmeta[\"height\"],\n \"framerate_source\": vmeta[\"fps\"],\n \"clip_location\": str(clips_dir / f\"{cid}.mp4\"),\n \"windows\": [], \"valid\": True,\n }\n try:\n clip_meta.update(_probe_clip(cb))\n except Exception:\n pass\n futures.append(ex.submit(\n (metas_dir / f\"{cid}.json\").write_text, _json.dumps(clip_meta)))\n num_transcoded += 1\n total_dur += span_dur\n max_dur = max(max_dur, span_dur)\n for f in futures:\n f.result()\n if chunk_idx == 0:\n video_meta = {\n \"video\": path, \"height\": vmeta[\"height\"], \"width\": vmeta[\"width\"],\n \"framerate\": vmeta[\"fps\"], \"num_frames\": vmeta[\"num_frames\"],\n \"video_codec\": vmeta[\"video_codec\"], \"pixel_format\": vmeta[\"pixel_format\"],\n \"audio_format\": vmeta[\"audio_codec\"],\n \"num_total_clips\": int(batch[\"num_total_clips\"][i]),\n \"num_clip_chunks\": int(batch[\"num_clip_chunks\"][i]),\n }\n rel = path.removeprefix(VIDEO_DIR).lstrip(\"/\") + \".json\"\n vpath = videos_dir / rel\n vpath.parent.mkdir(parents=True, exist_ok=True)\n vpath.write_text(_json.dumps(video_meta))\n chunk_stats = {\n \"video\": path, \"clip_chunk_index\": chunk_idx,\n \"num_clips_transcoded\": num_transcoded, \"num_clips_passed\": num_transcoded,\n \"total_clip_duration\": total_dur, \"max_clip_duration\": max_dur,\n \"clips\": [cid for cid, _ in chunk_clips],\n }\n rel = path.removeprefix(VIDEO_DIR).lstrip(\"/\") + f\"_{chunk_idx}.json\"\n cpath = chunks_dir / rel\n cpath.parent.mkdir(parents=True, exist_ok=True)\n cpath.write_text(_json.dumps(chunk_stats))\n return {\"path\": path, \"clip_ids\": [cid for cid, _ in chunk_clips]}\n\n results = [write_one_chunk(i) for i in range(len(batch[\"path\"]))]\n return {\"path\": [r[\"path\"] for r in results],\n \"clip_ids\": [r[\"clip_ids\"] for r in results]}" + "source": [ + "import json as _json\n", + "import subprocess\n", + "import tempfile\n", + "import uuid\n", + "from concurrent.futures import ThreadPoolExecutor\n", + "from pathlib import Path\n", + "\n", + "CLIP_LEN_S = 10.0\n", + "MIN_CLIP_LEN_S = 2.0\n", + "ENCODE_BATCH_SIZE = 16\n", + "ENCODER = \"libopenh264\"\n", + "ENCODER_THREADS = 1\n", + "# TRANSCODE_CPUS set in cell 1\n", + "WRITE_CPUS = 0.25\n", + "CLIPS_PER_CHUNK = 32\n", + "CHUNK_SIZE_S = CLIPS_PER_CHUNK * 8 * CLIP_LEN_S\n", + "\n", + "VIDEO_EXTENSIONS = (\".mp4\", \".mov\", \".avi\", \".mkv\", \".webm\")\n", + "\n", + "\n", + "def ls_videos(batch):\n", + " # Simulate slow upstream I/O (e.g. S3/NFS file listing, large dataset scan).\n", + " import time as _time\n", + "\n", + " _time.sleep(15)\n", + " paths = []\n", + " for ext in VIDEO_EXTENSIONS:\n", + " paths.extend(Path(VIDEO_DIR).rglob(f\"*{ext}\"))\n", + " paths = sorted(str(p) for p in paths)[:VIDEO_LIMIT]\n", + " return {\"path\": paths}\n", + "\n", + "\n", + "def read_and_probe(batch):\n", + " out = {\n", + " k: []\n", + " for k in [\n", + " \"path\",\n", + " \"bytes\",\n", + " \"duration\",\n", + " \"fps\",\n", + " \"num_frames\",\n", + " \"width\",\n", + " \"height\",\n", + " \"video_codec\",\n", + " \"pixel_format\",\n", + " \"audio_codec\",\n", + " \"bit_rate_k\",\n", + " ]\n", + " }\n", + " for path in batch[\"path\"]:\n", + " raw = Path(path).read_bytes()\n", + " with tempfile.NamedTemporaryFile(suffix=\".mp4\", delete=False) as tmp:\n", + " tmp.write(raw)\n", + " tmp_path = tmp.name\n", + " try:\n", + " result = subprocess.run(\n", + " [\"ffprobe\", \"-v\", \"error\", \"-show_format\", \"-show_streams\", \"-of\", \"json\", tmp_path],\n", + " stdout=subprocess.PIPE,\n", + " stderr=subprocess.PIPE,\n", + " check=True,\n", + " )\n", + " finally:\n", + " Path(tmp_path).unlink(missing_ok=True)\n", + " info = _json.loads(result.stdout)\n", + " vs = next(s for s in info[\"streams\"] if s[\"codec_type\"] == \"video\")\n", + " audio_codec = next((s[\"codec_name\"] for s in info[\"streams\"] if s[\"codec_type\"] == \"audio\"), None)\n", + " num, den = map(int, vs[\"avg_frame_rate\"].split(\"/\"))\n", + " fps = num / den\n", + " duration = float(vs[\"duration\"]) if \"duration\" in vs else float(info[\"format\"][\"duration\"])\n", + " bit_rate_k = int(int(vs[\"bit_rate\"]) / 1024) if \"bit_rate\" in vs else 2000\n", + " out[\"path\"].append(path)\n", + " out[\"bytes\"].append(raw)\n", + " out[\"duration\"].append(duration)\n", + " out[\"fps\"].append(fps)\n", + " out[\"num_frames\"].append(int(duration * fps))\n", + " out[\"width\"].append(int(vs[\"width\"]))\n", + " out[\"height\"].append(int(vs[\"height\"]))\n", + " out[\"video_codec\"].append(vs[\"codec_name\"])\n", + " out[\"pixel_format\"].append(vs[\"pix_fmt\"])\n", + " out[\"audio_codec\"].append(audio_codec)\n", + " out[\"bit_rate_k\"].append(bit_rate_k)\n", + " return out\n", + "\n", + "\n", + "def split_fixed_stride(batch):\n", + " out = {k: [] for k in list(batch.keys()) + [\"clips\"]}\n", + " for i in range(len(batch[\"path\"])):\n", + " duration = batch[\"duration\"][i]\n", + " clips, t = [], 0.0\n", + " while t < duration:\n", + " end = min(t + CLIP_LEN_S, duration)\n", + " if end - t >= MIN_CLIP_LEN_S:\n", + " clips.append((t, end))\n", + " t += CLIP_LEN_S\n", + " for k in batch.keys():\n", + " out[k].append(batch[k][i])\n", + " out[\"clips\"].append(clips)\n", + " return out\n", + "\n", + "\n", + "def _split_clips_into_chunks(clips_with_ids):\n", + " chunks, cur_chunk, cur_dur = [], [], 0.0\n", + " for item in clips_with_ids:\n", + " (s, e), cid = item\n", + " cur_chunk.append(item)\n", + " cur_dur += e - s\n", + " if cur_dur >= CHUNK_SIZE_S:\n", + " chunks.append(cur_chunk)\n", + " cur_chunk, cur_dur = [], 0.0\n", + " if cur_chunk:\n", + " chunks.append(cur_chunk)\n", + " return chunks\n", + "\n", + "\n", + "def transcode(batch):\n", + " out = {\n", + " \"path\": [],\n", + " \"clip_chunk_index\": [],\n", + " \"num_total_clips\": [],\n", + " \"num_clip_chunks\": [],\n", + " \"clips\": [],\n", + " \"clip_bytes_map\": [],\n", + " \"width\": [],\n", + " \"height\": [],\n", + " \"fps\": [],\n", + " \"num_frames\": [],\n", + " \"video_codec\": [],\n", + " \"pixel_format\": [],\n", + " \"audio_codec\": [],\n", + " \"bit_rate_k\": [],\n", + " }\n", + " for i, path in enumerate(batch[\"path\"]):\n", + " # Ray Data passes batch values as numpy arrays — convert to Python types\n", + " clips = [(float(s), float(e)) for s, e in batch[\"clips\"][i]]\n", + " if len(clips) == 0:\n", + " continue\n", + " pix_fmt = str(batch[\"pixel_format\"][i]) if batch[\"pixel_format\"][i] is not None else \"\"\n", + " force_pix_fmt = \"10le\" in pix_fmt or \"10be\" in pix_fmt\n", + " with tempfile.TemporaryDirectory() as tmp_dir:\n", + " tmp = Path(tmp_dir)\n", + " (tmp / \"input.mp4\").write_bytes(bytes(batch[\"bytes\"][i]))\n", + " fps = float(batch[\"fps\"][i])\n", + " clip_ids = [str(uuid.uuid5(uuid.NAMESPACE_URL, f\"{path}_{int(s * fps)}_{int(e * fps)}\")) for s, e in clips]\n", + " for b in range(0, len(clips), ENCODE_BATCH_SIZE):\n", + " b_clips = clips[b : b + ENCODE_BATCH_SIZE]\n", + " b_ids = clip_ids[b : b + ENCODE_BATCH_SIZE]\n", + " cmd = [\"ffmpeg\", \"-hide_banner\", \"-loglevel\", \"error\"]\n", + " for j, (start, end) in enumerate(b_clips):\n", + " cmd += [\n", + " \"-threads\",\n", + " str(ENCODER_THREADS),\n", + " \"-ss\",\n", + " str(start),\n", + " \"-to\",\n", + " str(end),\n", + " \"-i\",\n", + " \"input.mp4\",\n", + " \"-map\",\n", + " f\"{j}:v:0\",\n", + " \"-c:v\",\n", + " ENCODER,\n", + " ]\n", + " if force_pix_fmt:\n", + " cmd += [\"-pix_fmt\", \"yuv420p\"]\n", + " cmd += [\"-threads\", str(ENCODER_THREADS), \"-map\", f\"{j}:a:0?\", \"-c:a\", \"copy\", f\"{b_ids[j]}.mp4\"]\n", + " subprocess.check_output(cmd, cwd=tmp, stderr=subprocess.STDOUT)\n", + " clip_bytes = {cid: (tmp / f\"{cid}.mp4\").read_bytes() for cid in clip_ids if (tmp / f\"{cid}.mp4\").exists()}\n", + " clip_chunks = _split_clips_into_chunks(list(zip(clips, clip_ids))) # [(s,e), cid] pairs\n", + " for chunk_idx, chunk in enumerate(clip_chunks):\n", + " chunk_clips = [(s, e) for (s, e), _ in chunk]\n", + " chunk_ids = [cid for _, cid in chunk]\n", + " out[\"path\"].append(path)\n", + " out[\"clip_chunk_index\"].append(chunk_idx)\n", + " out[\"num_total_clips\"].append(len(clips))\n", + " out[\"num_clip_chunks\"].append(len(clip_chunks))\n", + " out[\"clips\"].append(list(zip(chunk_ids, chunk_clips)))\n", + " out[\"clip_bytes_map\"].append({cid: clip_bytes[cid] for cid in chunk_ids if cid in clip_bytes})\n", + " for k in [\n", + " \"width\",\n", + " \"height\",\n", + " \"fps\",\n", + " \"num_frames\",\n", + " \"video_codec\",\n", + " \"pixel_format\",\n", + " \"audio_codec\",\n", + " \"bit_rate_k\",\n", + " ]:\n", + " out[k].append(batch[k][i])\n", + " return out\n", + "\n", + "\n", + "def _probe_clip(clip_bytes):\n", + " with tempfile.NamedTemporaryFile(suffix=\".mp4\", delete=False) as tmp:\n", + " tmp.write(clip_bytes)\n", + " tmp_path = tmp.name\n", + " try:\n", + " result = subprocess.run(\n", + " [\"ffprobe\", \"-v\", \"error\", \"-show_streams\", \"-of\", \"json\", tmp_path],\n", + " stdout=subprocess.PIPE,\n", + " stderr=subprocess.PIPE,\n", + " check=True,\n", + " )\n", + " finally:\n", + " Path(tmp_path).unlink(missing_ok=True)\n", + " vs = next(s for s in _json.loads(result.stdout)[\"streams\"] if s[\"codec_type\"] == \"video\")\n", + " num, den = map(int, vs[\"avg_frame_rate\"].split(\"/\"))\n", + " return {\n", + " \"width\": int(vs[\"width\"]),\n", + " \"height\": int(vs[\"height\"]),\n", + " \"framerate\": num / den,\n", + " \"num_frames\": int(vs.get(\"nb_frames\", 0)),\n", + " \"video_codec\": vs[\"codec_name\"],\n", + " \"num_bytes\": len(clip_bytes),\n", + " }\n", + "\n", + "\n", + "def write_clips(batch):\n", + " clips_dir = Path(OUTPUT_DIR) / \"clips\"\n", + " metas_dir = Path(OUTPUT_DIR) / \"metas\" / \"v0\"\n", + " videos_dir = Path(OUTPUT_DIR) / \"processed_videos\"\n", + " chunks_dir = Path(OUTPUT_DIR) / \"processed_clip_chunks\"\n", + " for d in [clips_dir, metas_dir, videos_dir, chunks_dir]:\n", + " d.mkdir(parents=True, exist_ok=True)\n", + "\n", + " def write_one_chunk(i):\n", + " path = batch[\"path\"][i]\n", + " clip_bytes_map = batch[\"clip_bytes_map\"][i]\n", + " chunk_clips = [(str(cid), (float(s), float(e))) for cid, (s, e) in batch[\"clips\"][i]]\n", + " chunk_idx = int(batch[\"clip_chunk_index\"][i])\n", + " vmeta = {\n", + " \"width\": int(batch[\"width\"][i]),\n", + " \"height\": int(batch[\"height\"][i]),\n", + " \"fps\": float(batch[\"fps\"][i]),\n", + " \"num_frames\": int(batch[\"num_frames\"][i]),\n", + " \"video_codec\": str(batch[\"video_codec\"][i]),\n", + " \"pixel_format\": str(batch[\"pixel_format\"][i]),\n", + " \"audio_codec\": str(batch[\"audio_codec\"][i]) if batch[\"audio_codec\"][i] is not None else None,\n", + " \"bit_rate_k\": int(batch[\"bit_rate_k\"][i]),\n", + " }\n", + " num_transcoded, total_dur, max_dur = 0, 0.0, 0.0\n", + " with ThreadPoolExecutor(max_workers=6) as ex:\n", + " futures = []\n", + " for cid, (start, end) in chunk_clips:\n", + " cb = clip_bytes_map.get(cid)\n", + " if not cb:\n", + " continue\n", + " futures.append(ex.submit((clips_dir / f\"{cid}.mp4\").write_bytes, cb))\n", + " span_dur = end - start\n", + " clip_meta = {\n", + " \"span_uuid\": cid,\n", + " \"source_video\": path,\n", + " \"duration_span\": [start, end],\n", + " \"width_source\": vmeta[\"width\"],\n", + " \"height_source\": vmeta[\"height\"],\n", + " \"framerate_source\": vmeta[\"fps\"],\n", + " \"clip_location\": str(clips_dir / f\"{cid}.mp4\"),\n", + " \"windows\": [],\n", + " \"valid\": True,\n", + " }\n", + " try:\n", + " clip_meta.update(_probe_clip(cb))\n", + " except Exception:\n", + " pass\n", + " futures.append(ex.submit((metas_dir / f\"{cid}.json\").write_text, _json.dumps(clip_meta)))\n", + " num_transcoded += 1\n", + " total_dur += span_dur\n", + " max_dur = max(max_dur, span_dur)\n", + " for f in futures:\n", + " f.result()\n", + " if chunk_idx == 0:\n", + " video_meta = {\n", + " \"video\": path,\n", + " \"height\": vmeta[\"height\"],\n", + " \"width\": vmeta[\"width\"],\n", + " \"framerate\": vmeta[\"fps\"],\n", + " \"num_frames\": vmeta[\"num_frames\"],\n", + " \"video_codec\": vmeta[\"video_codec\"],\n", + " \"pixel_format\": vmeta[\"pixel_format\"],\n", + " \"audio_format\": vmeta[\"audio_codec\"],\n", + " \"num_total_clips\": int(batch[\"num_total_clips\"][i]),\n", + " \"num_clip_chunks\": int(batch[\"num_clip_chunks\"][i]),\n", + " }\n", + " rel = path.removeprefix(VIDEO_DIR).lstrip(\"/\") + \".json\"\n", + " vpath = videos_dir / rel\n", + " vpath.parent.mkdir(parents=True, exist_ok=True)\n", + " vpath.write_text(_json.dumps(video_meta))\n", + " chunk_stats = {\n", + " \"video\": path,\n", + " \"clip_chunk_index\": chunk_idx,\n", + " \"num_clips_transcoded\": num_transcoded,\n", + " \"num_clips_passed\": num_transcoded,\n", + " \"total_clip_duration\": total_dur,\n", + " \"max_clip_duration\": max_dur,\n", + " \"clips\": [cid for cid, _ in chunk_clips],\n", + " }\n", + " rel = path.removeprefix(VIDEO_DIR).lstrip(\"/\") + f\"_{chunk_idx}.json\"\n", + " cpath = chunks_dir / rel\n", + " cpath.parent.mkdir(parents=True, exist_ok=True)\n", + " cpath.write_text(_json.dumps(chunk_stats))\n", + " return {\"path\": path, \"clip_ids\": [cid for cid, _ in chunk_clips]}\n", + "\n", + " results = [write_one_chunk(i) for i in range(len(batch[\"path\"]))]\n", + " return {\"path\": [r[\"path\"] for r in results], \"clip_ids\": [r[\"clip_ids\"] for r in results]}" + ] }, { "cell_type": "code", @@ -39,35 +372,1545 @@ { "name": "stderr", "output_type": "stream", - "text": "2026-07-06 19:16:41,821\tINFO worker.py:2003 -- Started a local Ray instance. View the dashboard at \u001b[1m\u001b[32mhttp://127.0.0.1:8268 \u001b[39m\u001b[22m\n/opt/venv/lib/python3.13/site-packages/ray/_private/worker.py:2051: FutureWarning: Tip: In future versions of Ray, Ray will no longer override accelerator visible devices env var if num_gpus=0 or num_gpus=None (default). To enable this behavior and turn off this error message, set RAY_ACCEL_ENV_VAR_OVERRIDE_ON_ZERO=0\n warnings.warn(\n" + "text": [ + "2026-07-06 19:16:41,821\tINFO worker.py:2003 -- Started a local Ray instance. View the dashboard at \u001b[1m\u001b[32mhttp://127.0.0.1:8268 \u001b[39m\u001b[22m\n", + "/opt/venv/lib/python3.13/site-packages/ray/_private/worker.py:2051: FutureWarning: Tip: In future versions of Ray, Ray will no longer override accelerator visible devices env var if num_gpus=0 or num_gpus=None (default). To enable this behavior and turn off this error message, set RAY_ACCEL_ENV_VAR_OVERRIDE_ON_ZERO=0\n", + " warnings.warn(\n" + ] }, { "name": "stdout", "output_type": "stream", - "text": "Total CPUs: 64, max transcode workers: 9\nCPU pressure: 54/64 = 84%\n" + "text": [ + "Total CPUs: 64, max transcode workers: 9\n", + "CPU pressure: 54/64 = 84%\n" + ] }, { "name": "stderr", "output_type": "stream", - "text": "2026-07-06 19:16:44,644\tINFO logging.py:416 -- Registered dataset logger for dataset dataset_7_0\n2026-07-06 19:16:44,664\tINFO streaming_executor.py:166 -- Starting execution of Dataset dataset_7_0. Full logs are in /tmp/ray/session_2026-07-06_19-16-28_966894_3085811/logs/ray-data\n2026-07-06 19:16:44,665\tINFO streaming_executor.py:167 -- Execution plan of Dataset dataset_7_0: InputDataBuffer[Input] -> TaskPoolMapOperator[MapBatches(ls_videos)] -> AllToAllOperator[Repartition] -> TaskPoolMapOperator[MapBatches(read_and_probe)->MapBatches(split_fixed_stride)] -> ActorPoolMapOperator[MapBatches(TranscodeActor)] -> AllToAllOperator[Repartition] -> TaskPoolMapOperator[MapBatches(write_clips)]\n[2026-07-06 19:16:44,700 E 3085811 3085811] core_worker.cc:2194: Actor with class name: 'MapWorker(MapBatches(TranscodeActor))' and ID: '92944ed62242556e267e28ed01000000' has constructor arguments in the object store and max_restarts > 0. If the arguments in the object store go out of scope or are lost, the actor restart will fail. See https://github.com/ray-project/ray/issues/53727 for more details.\n2026-07-06 19:16:44,852\tWARNING resource_manager.py:169 -- \u26a0\ufe0f Ray's object store is configured to use only 9.1% of available memory (186.3GiB out of 2048.2GiB total). For optimal Ray Data performance, we recommend setting the object store to at least 50% of available memory. You can do this by setting the 'object_store_memory' parameter when calling ray.init() or by setting the RAY_DEFAULT_OBJECT_STORE_MEMORY_PROPORTION environment variable.\n2026-07-06 19:16:44,854\tINFO __init__.py:56 -- Progress will be logged because stdout is a non-interactive terminal.\n2026-07-06 19:16:45,572\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:16:45,574\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:16:45,577\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 0.0B/93.1GiB object store\n2026-07-06 19:16:45,578\tINFO logging_progress.py:181 -- \n2026-07-06 19:16:45,579\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 0/1\n2026-07-06 19:16:45,579\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store\n2026-07-06 19:16:45,580\tINFO logging_progress.py:231 -- Repartition: 0/1\n2026-07-06 19:16:45,580\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n2026-07-06 19:16:45,581\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:16:45,582\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 0/1\n2026-07-06 19:16:45,582\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:16:45,582\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 0/1\n2026-07-06 19:16:45,583\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 9; Queued blocks: 0 (0.0B); Resources: 54.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:16:45,583\tINFO logging_progress.py:231 -- Repartition: 0/1\n2026-07-06 19:16:45,583\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n2026-07-06 19:16:45,584\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:16:45,584\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:16:45,585\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:16:45,585\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:16:55,641\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:16:55,644\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:16:55,646\tINFO logging_progress.py:227 -- Active & requested resources: 55/64 CPU, 0.0B/93.1GiB object store\n2026-07-06 19:16:55,647\tINFO logging_progress.py:181 -- \n2026-07-06 19:16:55,648\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 0/1\n2026-07-06 19:16:55,648\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store\n2026-07-06 19:16:55,648\tINFO logging_progress.py:231 -- Repartition: 0/1\n2026-07-06 19:16:55,649\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n2026-07-06 19:16:55,649\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:16:55,649\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 0/1\n2026-07-06 19:16:55,650\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:16:55,651\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 0/1\n2026-07-06 19:16:55,651\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 9; Queued blocks: 0 (0.0B); Resources: 54.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:16:55,651\tINFO logging_progress.py:231 -- Repartition: 0/1\n2026-07-06 19:16:55,652\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n2026-07-06 19:16:55,652\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:16:55,652\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:16:55,653\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:16:55,653\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:17:05,668\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:17:05,670\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:17:05,671\tINFO logging_progress.py:227 -- Active & requested resources: 46/64 CPU, 137.2MiB/93.1GiB object store\n2026-07-06 19:17:05,672\tINFO logging_progress.py:181 -- \n2026-07-06 19:17:05,673\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:17:05,674\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:05,674\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:17:05,675\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 72.3KiB object store; 1000 rows output\n2026-07-06 19:17:05,676\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:17:05,677\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 2/1000\n2026-07-06 19:17:05,678\tINFO logging_progress.py:233 -- Tasks: 11; Actors: 0; Queued blocks: 987 (71.5KiB); Resources: 11.0 CPU, 148.6MiB object store\n2026-07-06 19:17:05,678\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 0/1\n2026-07-06 19:17:05,678\tINFO logging_progress.py:233 -- Tasks: 2; Actors: 6; Queued blocks: 0 (0.0B); Resources: 36.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:17:05,679\tINFO logging_progress.py:231 -- Repartition: 0/1\n2026-07-06 19:17:05,679\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n2026-07-06 19:17:05,679\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:17:05,680\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:17:05,680\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:05,680\tINFO logging_progress.py:192 -- ============================================\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m Failed to convert column 'clips' into pyarrow array due to: Error converting data to Arrow: [[('31461cd8-a73a-5ebd-a716-ea7fceda30ab', (0.0, 4.204204))]]; falling back to serialize as pickled python objects\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m Traceback (most recent call last):\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 398, in _convert_to_pyarrow_native_array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m return pa.array(column_values, type=pa_type)\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m ~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m File \"pyarrow/array.pxi\", line 375, in pyarrow.lib.array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m File \"pyarrow/array.pxi\", line 46, in pyarrow.lib._sequence_to_array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m chunked = GetResultValue(\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m File \"pyarrow/error.pxi\", line 155, in pyarrow.lib.pyarrow_internal_check_status\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m File \"pyarrow/error.pxi\", line 92, in pyarrow.lib.check_status\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m raise convert_status(status)\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m pyarrow.lib.ArrowTypeError: Expected bytes, got a 'tuple' object\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m The above exception was the direct cause of the following exception:\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m Traceback (most recent call last):\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 299, in convert_to_pyarrow_array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m return _convert_to_pyarrow_native_array(column_values, column_name)\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 400, in _convert_to_pyarrow_native_array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m raise ArrowConversionError(str(column_values)) from e\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m ray.data._internal.tensor_extensions.arrow.ArrowConversionError: Error converting data to Arrow: [[('31461cd8-a73a-5ebd-a716-ea7fceda30ab', (0.0, 4.204204))]]\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087266)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087266)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087273)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087273)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087283)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087283)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091587)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091587)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087280)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087280)\u001b[0m \n2026-07-06 19:17:15,754\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:17:15,755\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:17:15,756\tINFO logging_progress.py:227 -- Active & requested resources: 37/64 CPU, 9.1GiB/93.1GiB object store\n2026-07-06 19:17:15,757\tINFO logging_progress.py:181 -- \n2026-07-06 19:17:15,757\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:17:15,757\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:15,758\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:17:15,758\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 371.0B object store; 1000 rows output\n2026-07-06 19:17:15,758\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:17:15,758\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 995/1000\n2026-07-06 19:17:15,759\tINFO logging_progress.py:233 -- Tasks: 2; Actors: 0; Queued blocks: 3 (222.0B); Resources: 2.0 CPU, 9.0GiB object store\n2026-07-06 19:17:15,759\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 42/1000\n2026-07-06 19:17:15,759\tINFO logging_progress.py:233 -- Tasks: 12; Actors: 6; Queued blocks: 941 (8.7GiB); Resources: 36.0 CPU, 120.0MiB object store; [all objects local]\n2026-07-06 19:17:15,759\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:17:15,760\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 42 (105.0MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:17:15,760\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:17:15,760\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:17:15,760\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:15,761\tINFO logging_progress.py:192 -- ============================================\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m Failed to convert column 'clips' into pyarrow array due to: Error converting data to Arrow: [[('1d9fd32b-73fa-502a-8b35-f08077ca27e9', (0.0, 6.266667))]]; falling back to serialize as pickled python objects\u001b[32m [repeated 6x across cluster] (Ray deduplicates logs by default. Set RAY_DEDUP_LOGS=0 to disable log deduplication, or see https://docs.ray.io/en/master/ray-observability/user-guides/configure-logging.html#log-deduplication for more options.)\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m Traceback (most recent call last):\u001b[32m [repeated 12x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 400, in _convert_to_pyarrow_native_array\u001b[32m [repeated 12x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m return pa.array(column_values, type=pa_type)\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m ~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m File \"pyarrow/array.pxi\", line 375, in pyarrow.lib.array\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m File \"pyarrow/array.pxi\", line 46, in pyarrow.lib._sequence_to_array\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m chunked = GetResultValue(\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m File \"pyarrow/error.pxi\", line 155, in pyarrow.lib.pyarrow_internal_check_status\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m File \"pyarrow/error.pxi\", line 92, in pyarrow.lib.check_status\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m raise convert_status(status)\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m pyarrow.lib.ArrowTypeError: Expected bytes, got a 'tuple' object\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m The above exception was the direct cause of the following exception:\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 299, in convert_to_pyarrow_array\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m return _convert_to_pyarrow_native_array(column_values, column_name)\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m raise ArrowConversionError(str(column_values)) from e\u001b[32m [repeated 6x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m ray.data._internal.tensor_extensions.arrow.ArrowConversionError: Error converting data to Arrow: [[('1d9fd32b-73fa-502a-8b35-f08077ca27e9', (0.0, 6.266667))]]\u001b[32m [repeated 6x across cluster]\u001b[0m\n2026-07-06 19:17:25,817\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:17:25,819\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:17:25,820\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 8.9GiB/93.1GiB object store\n2026-07-06 19:17:25,820\tINFO logging_progress.py:181 -- \n2026-07-06 19:17:25,821\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:17:25,821\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:25,821\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:17:25,822\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:17:25,822\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:17:25,822\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:17:25,823\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.6GiB object store\n2026-07-06 19:17:25,823\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 103/1000\n2026-07-06 19:17:25,823\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 883 (8.5GiB); Resources: 42.0 CPU, 276.2MiB object store; [all objects local]\n2026-07-06 19:17:25,824\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:17:25,824\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 103 (258.7MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:17:25,824\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:17:25,825\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:17:25,825\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:25,825\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:17:35,887\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:17:35,889\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:17:35,890\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 8.5GiB/93.1GiB object store\n2026-07-06 19:17:35,890\tINFO logging_progress.py:181 -- \n2026-07-06 19:17:35,890\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:17:35,891\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:35,891\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:17:35,891\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:17:35,892\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:17:35,892\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:17:35,893\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.1GiB object store\n2026-07-06 19:17:35,893\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 166/1000\n2026-07-06 19:17:35,893\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 820 (7.9GiB); Resources: 42.0 CPU, 418.1MiB object store; [all objects local]\n2026-07-06 19:17:35,894\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:17:35,894\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 166 (401.2MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:17:35,895\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:17:35,895\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:17:35,895\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:35,895\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:17:45,936\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:17:45,938\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:17:45,939\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 7.9GiB/93.1GiB object store\n2026-07-06 19:17:45,940\tINFO logging_progress.py:181 -- \n2026-07-06 19:17:45,940\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:17:45,941\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:45,941\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:17:45,942\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:17:45,942\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:17:45,942\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:17:45,943\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 7.4GiB object store\n2026-07-06 19:17:45,944\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 225/1000\n2026-07-06 19:17:45,944\tINFO logging_progress.py:233 -- Tasks: 12; Actors: 7; Queued blocks: 763 (7.2GiB); Resources: 42.0 CPU, 586.7MiB object store; [all objects local]\n2026-07-06 19:17:45,945\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:17:45,945\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 225 (569.0MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:17:45,945\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:17:45,945\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:17:45,946\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:45,946\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:17:55,936\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:17:55,937\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:17:55,938\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 7.6GiB/93.1GiB object store\n2026-07-06 19:17:55,938\tINFO logging_progress.py:181 -- \n2026-07-06 19:17:55,939\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:17:55,939\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:55,939\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:17:55,939\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:17:55,940\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:17:55,940\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:17:55,941\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 6.9GiB object store\n2026-07-06 19:17:55,941\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 289/1000\n2026-07-06 19:17:55,941\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 697 (6.7GiB); Resources: 42.0 CPU, 723.8MiB object store; [all objects local]\n2026-07-06 19:17:55,941\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:17:55,942\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 289 (706.7MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:17:55,942\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:17:55,942\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:17:55,942\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:17:55,943\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:18:06,045\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:18:06,047\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:18:06,049\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 7.0GiB/93.1GiB object store\n2026-07-06 19:18:06,049\tINFO logging_progress.py:181 -- \n2026-07-06 19:18:06,050\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:18:06,050\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:06,051\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:18:06,051\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:06,052\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:18:06,052\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:18:06,053\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 6.2GiB object store\n2026-07-06 19:18:06,053\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 354/1000\n2026-07-06 19:18:06,053\tINFO logging_progress.py:233 -- Tasks: 13; Actors: 7; Queued blocks: 633 (6.0GiB); Resources: 42.0 CPU, 875.1MiB object store; [all objects local]\n2026-07-06 19:18:06,054\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:18:06,054\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 354 (858.1MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:06,054\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:18:06,057\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:18:06,057\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:06,058\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:18:16,155\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:18:16,157\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:18:16,159\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 6.6GiB/93.1GiB object store\n2026-07-06 19:18:16,161\tINFO logging_progress.py:181 -- \n2026-07-06 19:18:16,162\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:18:16,163\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:16,164\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:18:16,164\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:16,166\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:18:16,167\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:18:16,168\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 5.6GiB object store\n2026-07-06 19:18:16,168\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 420/1000\n2026-07-06 19:18:16,170\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 566 (5.4GiB); Resources: 42.0 CPU, 1019.4MiB object store; [all objects local]\n2026-07-06 19:18:16,171\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:18:16,172\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 420 (1002.7MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:16,173\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:18:16,173\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:18:16,174\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:16,175\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:18:26,220\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:18:26,223\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:18:26,224\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 6.2GiB/93.1GiB object store\n2026-07-06 19:18:26,225\tINFO logging_progress.py:181 -- \n2026-07-06 19:18:26,226\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:18:26,226\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:26,227\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:18:26,227\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:26,228\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:18:26,228\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:18:26,229\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 5.1GiB object store\n2026-07-06 19:18:26,229\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 490/1000\n2026-07-06 19:18:26,229\tINFO logging_progress.py:233 -- Tasks: 13; Actors: 7; Queued blocks: 497 (5.0GiB); Resources: 42.0 CPU, 1.1GiB object store; [all objects local]\n2026-07-06 19:18:26,230\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:18:26,231\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 490 (1.1GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:26,232\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:18:26,232\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:18:26,232\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:26,233\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:18:36,238\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:18:36,239\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:18:36,240\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 5.8GiB/93.1GiB object store\n2026-07-06 19:18:36,241\tINFO logging_progress.py:181 -- \n2026-07-06 19:18:36,242\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:18:36,242\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:36,243\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:18:36,243\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:36,243\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:18:36,243\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:18:36,244\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 4.5GiB object store\n2026-07-06 19:18:36,244\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 547/1000\n2026-07-06 19:18:36,245\tINFO logging_progress.py:233 -- Tasks: 13; Actors: 7; Queued blocks: 440 (4.4GiB); Resources: 42.0 CPU, 1.3GiB object store; [all objects local]\n2026-07-06 19:18:36,245\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:18:36,245\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 547 (1.3GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:36,246\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:18:36,246\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:18:36,247\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:36,247\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:18:46,347\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:18:46,349\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:18:46,350\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 5.4GiB/93.1GiB object store\n2026-07-06 19:18:46,351\tINFO logging_progress.py:181 -- \n2026-07-06 19:18:46,352\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:18:46,353\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:46,354\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:18:46,355\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:46,356\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:18:46,356\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:18:46,356\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 3.9GiB object store\n2026-07-06 19:18:46,357\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 615/1000\n2026-07-06 19:18:46,357\tINFO logging_progress.py:233 -- Tasks: 12; Actors: 7; Queued blocks: 373 (3.8GiB); Resources: 42.0 CPU, 1.4GiB object store; [all objects local]\n2026-07-06 19:18:46,358\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:18:46,358\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 615 (1.4GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:46,359\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:18:46,360\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:18:46,361\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:46,361\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:18:56,375\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:18:56,377\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:18:56,378\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 4.7GiB/93.1GiB object store\n2026-07-06 19:18:56,379\tINFO logging_progress.py:181 -- \n2026-07-06 19:18:56,380\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:18:56,380\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:56,381\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:18:56,381\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:56,382\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:18:56,384\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:18:56,384\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 3.1GiB object store\n2026-07-06 19:18:56,385\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 673/1000\n2026-07-06 19:18:56,386\tINFO logging_progress.py:233 -- Tasks: 12; Actors: 7; Queued blocks: 315 (3.0GiB); Resources: 42.0 CPU, 1.6GiB object store; [all objects local]\n2026-07-06 19:18:56,386\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:18:56,387\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 673 (1.6GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:18:56,387\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:18:56,388\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:18:56,388\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:18:56,389\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:19:06,402\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:19:06,403\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:19:06,403\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 4.3GiB/93.1GiB object store\n2026-07-06 19:19:06,404\tINFO logging_progress.py:181 -- \n2026-07-06 19:19:06,404\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:19:06,404\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:06,405\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:19:06,405\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:06,405\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:19:06,405\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:19:06,405\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 2.6GiB object store\n2026-07-06 19:19:06,406\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 732/1000\n2026-07-06 19:19:06,406\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 254 (2.4GiB); Resources: 42.0 CPU, 1.7GiB object store; [all objects local]\n2026-07-06 19:19:06,406\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:19:06,407\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 732 (1.7GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:06,407\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:19:06,407\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:19:06,407\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:06,408\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:19:16,461\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:19:16,463\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:19:16,465\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 3.9GiB/93.1GiB object store\n2026-07-06 19:19:16,465\tINFO logging_progress.py:181 -- \n2026-07-06 19:19:16,466\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:19:16,467\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:16,467\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:19:16,467\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:16,468\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:19:16,468\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:19:16,468\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 2.0GiB object store\n2026-07-06 19:19:16,469\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 799/1000\n2026-07-06 19:19:16,469\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 187 (1.8GiB); Resources: 42.0 CPU, 1.9GiB object store; [all objects local]\n2026-07-06 19:19:16,469\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:19:16,470\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 799 (1.8GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:16,470\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:19:16,471\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:19:16,471\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:16,471\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:19:26,467\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:19:26,469\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:19:26,470\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 3.2GiB/93.1GiB object store\n2026-07-06 19:19:26,471\tINFO logging_progress.py:181 -- \n2026-07-06 19:19:26,471\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:19:26,472\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:26,472\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:19:26,473\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:26,473\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:19:26,473\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:19:26,474\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 1.2GiB object store\n2026-07-06 19:19:26,474\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 860/1000\n2026-07-06 19:19:26,475\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 126 (1.1GiB); Resources: 42.0 CPU, 2.0GiB object store; [all objects local]\n2026-07-06 19:19:26,475\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:19:26,475\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 860 (2.0GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:26,476\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:19:26,476\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:19:26,476\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:26,476\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:19:36,531\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:19:36,532\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:19:36,534\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 2.9GiB/93.1GiB object store\n2026-07-06 19:19:36,535\tINFO logging_progress.py:181 -- \n2026-07-06 19:19:36,536\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:19:36,536\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:36,537\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:19:36,537\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:36,537\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:19:36,538\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:19:36,538\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 781.3MiB object store\n2026-07-06 19:19:36,538\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 927/1000\n2026-07-06 19:19:36,539\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 59 (627.0MiB); Resources: 42.0 CPU, 2.1GiB object store; [all objects local]\n2026-07-06 19:19:36,539\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:19:36,539\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 927 (2.1GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:36,539\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:19:36,540\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:19:36,540\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:36,540\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:19:46,547\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:19:46,550\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:19:46,551\tINFO logging_progress.py:227 -- Active & requested resources: 36/64 CPU, 2.4GiB/93.1GiB object store\n2026-07-06 19:19:46,552\tINFO logging_progress.py:181 -- \n2026-07-06 19:19:46,553\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:19:46,553\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:46,555\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:19:46,555\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:46,556\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:19:46,557\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:19:46,557\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 158.8MiB object store\n2026-07-06 19:19:46,559\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 994/1000\n2026-07-06 19:19:46,560\tINFO logging_progress.py:233 -- Tasks: 6; Actors: 6; Queued blocks: 0 (0.0B); Resources: 36.0 CPU, 2.3GiB object store; [all objects local]\n2026-07-06 19:19:46,560\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:19:46,561\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 994 (2.3GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:46,561\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:19:46,562\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:19:46,562\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:46,562\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:19:56,601\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:19:56,603\tINFO logging_progress.py:225 -- Total Progress: 12/20000\n2026-07-06 19:19:56,605\tINFO logging_progress.py:227 -- Active & requested resources: 64/64 CPU, 2.3GiB/93.1GiB object store\n2026-07-06 19:19:56,605\tINFO logging_progress.py:181 -- \n2026-07-06 19:19:56,606\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:19:56,607\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:56,607\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:19:56,608\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:19:56,609\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:19:56,610\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:19:56,611\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:19:56,612\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:19:56,614\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:19:56,615\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:19:56,616\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 2.3GiB object store; 1000 rows output\n2026-07-06 19:19:56,618\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:19:56,619\tINFO logging_progress.py:231 -- MapBatches(write_clips): 15/20000\n2026-07-06 19:19:56,620\tINFO logging_progress.py:233 -- Tasks: 256 [backpressured:tasks(ResourceBudget)]; Actors: 0; Queued blocks: 19729 (1.6GiB); Resources: 64.0 CPU, 35.3KiB object store\n2026-07-06 19:19:56,621\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:20:06,604\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:20:06,607\tINFO logging_progress.py:225 -- Total Progress: 12/20000\n2026-07-06 19:20:06,608\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:20:06,609\tINFO logging_progress.py:181 -- \n2026-07-06 19:20:06,610\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:20:06,610\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:06,611\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:06,619\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:20:06,620\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:06,620\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:20:06,621\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:06,623\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:20:06,624\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:20:06,625\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:06,628\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:20:06,629\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:06,630\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:20:06,630\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 128.1KiB object store\n2026-07-06 19:20:06,631\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:20:16,607\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:20:16,610\tINFO logging_progress.py:225 -- Total Progress: 13/20000\n2026-07-06 19:20:16,611\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:20:16,612\tINFO logging_progress.py:181 -- \n2026-07-06 19:20:16,612\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:20:16,613\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:16,614\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:16,615\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:20:16,615\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:16,617\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:20:16,619\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:16,621\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:20:16,622\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:20:16,623\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:16,624\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:20:16,625\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:16,625\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:20:16,626\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 128.1KiB object store\n2026-07-06 19:20:16,627\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:20:26,610\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:20:26,614\tINFO logging_progress.py:225 -- Total Progress: 118/20000\n2026-07-06 19:20:26,615\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:20:26,616\tINFO logging_progress.py:181 -- \n2026-07-06 19:20:26,617\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:20:26,618\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:26,619\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:26,620\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:20:26,621\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:26,621\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:20:26,622\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:26,623\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:20:26,624\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:20:26,625\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:26,625\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:20:26,626\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:26,627\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:20:26,627\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 114.6KiB object store\n2026-07-06 19:20:26,627\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:20:36,610\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:20:36,613\tINFO logging_progress.py:225 -- Total Progress: 131/20000\n2026-07-06 19:20:36,615\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:20:36,616\tINFO logging_progress.py:181 -- \n2026-07-06 19:20:36,617\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:20:36,618\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:36,619\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:36,620\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:20:36,620\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:36,621\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:20:36,622\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:36,623\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:20:36,625\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:20:36,626\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:36,627\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:20:36,627\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:36,628\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:20:36,630\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 112.9KiB object store\n2026-07-06 19:20:36,631\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:20:46,616\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:20:46,621\tINFO logging_progress.py:225 -- Total Progress: 132/20000\n2026-07-06 19:20:46,625\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:20:46,626\tINFO logging_progress.py:181 -- \n2026-07-06 19:20:46,627\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:20:46,628\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:46,629\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:46,630\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:20:46,630\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:46,631\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:20:46,632\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:46,633\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:20:46,634\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:20:46,635\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:46,636\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:20:46,636\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:46,637\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:20:46,638\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 112.8KiB object store\n2026-07-06 19:20:46,639\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:20:56,625\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:20:56,628\tINFO logging_progress.py:225 -- Total Progress: 137/20000\n2026-07-06 19:20:56,629\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:20:56,630\tINFO logging_progress.py:181 -- \n2026-07-06 19:20:56,631\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:20:56,632\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:56,633\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:56,634\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:20:56,635\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:56,636\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:20:56,636\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:20:56,637\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:20:56,639\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:20:56,639\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:20:56,640\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:20:56,640\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:20:56,641\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:20:56,642\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 112.2KiB object store\n2026-07-06 19:20:56,642\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:21:06,630\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:21:06,632\tINFO logging_progress.py:225 -- Total Progress: 165/20000\n2026-07-06 19:21:06,634\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:21:06,635\tINFO logging_progress.py:181 -- \n2026-07-06 19:21:06,637\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:21:06,638\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:06,639\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:06,639\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:21:06,640\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:06,642\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:21:06,642\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:06,644\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:21:06,645\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:21:06,646\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:06,647\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:21:06,648\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:06,649\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:21:06,650\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 108.4KiB object store\n2026-07-06 19:21:06,651\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:21:16,640\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:21:16,642\tINFO logging_progress.py:225 -- Total Progress: 229/20000\n2026-07-06 19:21:16,643\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:21:16,650\tINFO logging_progress.py:181 -- \n2026-07-06 19:21:16,650\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:21:16,652\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:16,653\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:16,654\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:21:16,655\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:16,657\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:21:16,658\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:16,660\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:21:16,663\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:21:16,668\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:16,668\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:21:16,670\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:16,670\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:21:16,671\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 99.7KiB object store\n2026-07-06 19:21:16,672\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:21:26,640\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:21:26,643\tINFO logging_progress.py:225 -- Total Progress: 323/20000\n2026-07-06 19:21:26,652\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:21:26,653\tINFO logging_progress.py:181 -- \n2026-07-06 19:21:26,654\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:21:26,655\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:26,656\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:26,657\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:21:26,657\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:26,659\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:21:26,660\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:26,660\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:21:26,661\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:21:26,662\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:26,662\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:21:26,663\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:26,663\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:21:26,663\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 87.4KiB object store\n2026-07-06 19:21:26,664\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:21:36,643\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:21:36,647\tINFO logging_progress.py:225 -- Total Progress: 358/20000\n2026-07-06 19:21:36,648\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:21:36,649\tINFO logging_progress.py:181 -- \n2026-07-06 19:21:36,649\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:21:36,650\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:36,652\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:36,653\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:21:36,654\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:36,654\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:21:36,655\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:36,656\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:21:36,656\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:21:36,657\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:36,657\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:21:36,657\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:36,658\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:21:36,659\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 82.8KiB object store\n2026-07-06 19:21:36,659\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:21:46,648\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:21:46,650\tINFO logging_progress.py:225 -- Total Progress: 360/20000\n2026-07-06 19:21:46,651\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:21:46,652\tINFO logging_progress.py:181 -- \n2026-07-06 19:21:46,652\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:21:46,653\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:46,653\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:46,654\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:21:46,655\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:46,655\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:21:46,656\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:46,656\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:21:46,657\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:21:46,657\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:46,658\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:21:46,658\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:46,659\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:21:46,659\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 82.6KiB object store\n2026-07-06 19:21:46,660\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:21:56,652\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:21:56,654\tINFO logging_progress.py:225 -- Total Progress: 362/20000\n2026-07-06 19:21:56,655\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:21:56,656\tINFO logging_progress.py:181 -- \n2026-07-06 19:21:56,656\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:21:56,657\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:56,657\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:56,658\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:21:56,659\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:56,660\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:21:56,660\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:21:56,661\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:21:56,661\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:21:56,662\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:21:56,663\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:21:56,663\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:21:56,664\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:21:56,664\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 82.3KiB object store\n2026-07-06 19:21:56,665\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:22:06,662\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:22:06,674\tINFO logging_progress.py:225 -- Total Progress: 366/20000\n2026-07-06 19:22:06,681\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:22:06,688\tINFO logging_progress.py:181 -- \n2026-07-06 19:22:06,692\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:22:06,696\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:06,701\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:22:06,703\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:22:06,705\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:22:06,706\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:22:06,708\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:06,712\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:22:06,716\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:22:06,718\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:22:06,719\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:22:06,720\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:22:06,724\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:22:06,725\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 82.2KiB object store\n2026-07-06 19:22:06,727\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:22:16,676\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:22:16,679\tINFO logging_progress.py:225 -- Total Progress: 473/20000\n2026-07-06 19:22:16,683\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:22:16,683\tINFO logging_progress.py:181 -- \n2026-07-06 19:22:16,684\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:22:16,684\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:16,685\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:22:16,688\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:22:16,697\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:22:16,703\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:22:16,711\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:16,715\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:22:16,715\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:22:16,716\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:22:16,717\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:22:16,720\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:22:16,723\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:22:16,725\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 68.1KiB object store\n2026-07-06 19:22:16,726\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:22:26,683\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:22:26,684\tINFO logging_progress.py:225 -- Total Progress: 552/20000\n2026-07-06 19:22:26,685\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:22:26,686\tINFO logging_progress.py:181 -- \n2026-07-06 19:22:26,686\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:22:26,687\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:26,687\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:22:26,688\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:22:26,688\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:22:26,689\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:22:26,689\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:26,689\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:22:26,690\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:22:26,691\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:22:26,691\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:22:26,692\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:22:26,693\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:22:26,694\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 57.9KiB object store\n2026-07-06 19:22:26,694\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:22:36,684\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n2026-07-06 19:22:36,686\tINFO logging_progress.py:225 -- Total Progress: 571/20000\n2026-07-06 19:22:36,688\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n2026-07-06 19:22:36,689\tINFO logging_progress.py:181 -- \n2026-07-06 19:22:36,690\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:22:36,691\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:36,691\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:22:36,692\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:22:36,694\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:22:36,695\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:22:36,695\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:36,696\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:22:36,696\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:22:36,697\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:22:36,698\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n2026-07-06 19:22:36,698\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:22:36,698\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n2026-07-06 19:22:36,699\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 55.6KiB object store\n2026-07-06 19:22:36,700\tINFO logging_progress.py:192 -- ============================================\n2026-07-06 19:22:44,446\tINFO streaming_executor.py:294 -- \u2714\ufe0f Dataset dataset_7_0 execution finished in 359.76 seconds\n" + "text": [ + "2026-07-06 19:16:44,644\tINFO logging.py:416 -- Registered dataset logger for dataset dataset_7_0\n", + "2026-07-06 19:16:44,664\tINFO streaming_executor.py:166 -- Starting execution of Dataset dataset_7_0. Full logs are in /tmp/ray/session_2026-07-06_19-16-28_966894_3085811/logs/ray-data\n", + "2026-07-06 19:16:44,665\tINFO streaming_executor.py:167 -- Execution plan of Dataset dataset_7_0: InputDataBuffer[Input] -> TaskPoolMapOperator[MapBatches(ls_videos)] -> AllToAllOperator[Repartition] -> TaskPoolMapOperator[MapBatches(read_and_probe)->MapBatches(split_fixed_stride)] -> ActorPoolMapOperator[MapBatches(TranscodeActor)] -> AllToAllOperator[Repartition] -> TaskPoolMapOperator[MapBatches(write_clips)]\n", + "[2026-07-06 19:16:44,700 E 3085811 3085811] core_worker.cc:2194: Actor with class name: 'MapWorker(MapBatches(TranscodeActor))' and ID: '92944ed62242556e267e28ed01000000' has constructor arguments in the object store and max_restarts > 0. If the arguments in the object store go out of scope or are lost, the actor restart will fail. See https://github.com/ray-project/ray/issues/53727 for more details.\n", + "2026-07-06 19:16:44,852\tWARNING resource_manager.py:169 -- ⚠️ Ray's object store is configured to use only 9.1% of available memory (186.3GiB out of 2048.2GiB total). For optimal Ray Data performance, we recommend setting the object store to at least 50% of available memory. You can do this by setting the 'object_store_memory' parameter when calling ray.init() or by setting the RAY_DEFAULT_OBJECT_STORE_MEMORY_PROPORTION environment variable.\n", + "2026-07-06 19:16:44,854\tINFO __init__.py:56 -- Progress will be logged because stdout is a non-interactive terminal.\n", + "2026-07-06 19:16:45,572\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:16:45,574\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:16:45,577\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 0.0B/93.1GiB object store\n", + "2026-07-06 19:16:45,578\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:16:45,579\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 0/1\n", + "2026-07-06 19:16:45,579\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store\n", + "2026-07-06 19:16:45,580\tINFO logging_progress.py:231 -- Repartition: 0/1\n", + "2026-07-06 19:16:45,580\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n", + "2026-07-06 19:16:45,581\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:16:45,582\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 0/1\n", + "2026-07-06 19:16:45,582\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:16:45,582\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 0/1\n", + "2026-07-06 19:16:45,583\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 9; Queued blocks: 0 (0.0B); Resources: 54.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:16:45,583\tINFO logging_progress.py:231 -- Repartition: 0/1\n", + "2026-07-06 19:16:45,583\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n", + "2026-07-06 19:16:45,584\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:16:45,584\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:16:45,585\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:16:45,585\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:16:55,641\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:16:55,644\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:16:55,646\tINFO logging_progress.py:227 -- Active & requested resources: 55/64 CPU, 0.0B/93.1GiB object store\n", + "2026-07-06 19:16:55,647\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:16:55,648\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 0/1\n", + "2026-07-06 19:16:55,648\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store\n", + "2026-07-06 19:16:55,648\tINFO logging_progress.py:231 -- Repartition: 0/1\n", + "2026-07-06 19:16:55,649\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n", + "2026-07-06 19:16:55,649\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:16:55,649\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 0/1\n", + "2026-07-06 19:16:55,650\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:16:55,651\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 0/1\n", + "2026-07-06 19:16:55,651\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 9; Queued blocks: 0 (0.0B); Resources: 54.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:16:55,651\tINFO logging_progress.py:231 -- Repartition: 0/1\n", + "2026-07-06 19:16:55,652\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n", + "2026-07-06 19:16:55,652\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:16:55,652\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:16:55,653\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:16:55,653\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:17:05,668\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:17:05,670\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:17:05,671\tINFO logging_progress.py:227 -- Active & requested resources: 46/64 CPU, 137.2MiB/93.1GiB object store\n", + "2026-07-06 19:17:05,672\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:17:05,673\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:17:05,674\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:17:05,674\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:17:05,675\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 72.3KiB object store; 1000 rows output\n", + "2026-07-06 19:17:05,676\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:17:05,677\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 2/1000\n", + "2026-07-06 19:17:05,678\tINFO logging_progress.py:233 -- Tasks: 11; Actors: 0; Queued blocks: 987 (71.5KiB); Resources: 11.0 CPU, 148.6MiB object store\n", + "2026-07-06 19:17:05,678\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 0/1\n", + "2026-07-06 19:17:05,678\tINFO logging_progress.py:233 -- Tasks: 2; Actors: 6; Queued blocks: 0 (0.0B); Resources: 36.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:17:05,679\tINFO logging_progress.py:231 -- Repartition: 0/1\n", + "2026-07-06 19:17:05,679\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n", + "2026-07-06 19:17:05,679\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:17:05,680\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:17:05,680\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:17:05,680\tINFO logging_progress.py:192 -- ============================================\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m Failed to convert column 'clips' into pyarrow array due to: Error converting data to Arrow: [[('31461cd8-a73a-5ebd-a716-ea7fceda30ab', (0.0, 4.204204))]]; falling back to serialize as pickled python objects\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m Traceback (most recent call last):\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 398, in _convert_to_pyarrow_native_array\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m return pa.array(column_values, type=pa_type)\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m ~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m File \"pyarrow/array.pxi\", line 375, in pyarrow.lib.array\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m File \"pyarrow/array.pxi\", line 46, in pyarrow.lib._sequence_to_array\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m chunked = GetResultValue(\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m File \"pyarrow/error.pxi\", line 155, in pyarrow.lib.pyarrow_internal_check_status\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m File \"pyarrow/error.pxi\", line 92, in pyarrow.lib.check_status\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m raise convert_status(status)\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m pyarrow.lib.ArrowTypeError: Expected bytes, got a 'tuple' object\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m The above exception was the direct cause of the following exception:\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m Traceback (most recent call last):\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 299, in convert_to_pyarrow_array\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m return _convert_to_pyarrow_native_array(column_values, column_name)\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 400, in _convert_to_pyarrow_native_array\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m raise ArrowConversionError(str(column_values)) from e\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087274)\u001b[0m ray.data._internal.tensor_extensions.arrow.ArrowConversionError: Error converting data to Arrow: [[('31461cd8-a73a-5ebd-a716-ea7fceda30ab', (0.0, 4.204204))]]\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087266)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087266)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087273)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087273)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087283)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087283)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091587)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091587)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087280)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3087280)\u001b[0m \n", + "2026-07-06 19:17:15,754\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:17:15,755\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:17:15,756\tINFO logging_progress.py:227 -- Active & requested resources: 37/64 CPU, 9.1GiB/93.1GiB object store\n", + "2026-07-06 19:17:15,757\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:17:15,757\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:17:15,757\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:17:15,758\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:17:15,758\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 371.0B object store; 1000 rows output\n", + "2026-07-06 19:17:15,758\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:17:15,758\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 995/1000\n", + "2026-07-06 19:17:15,759\tINFO logging_progress.py:233 -- Tasks: 2; Actors: 0; Queued blocks: 3 (222.0B); Resources: 2.0 CPU, 9.0GiB object store\n", + "2026-07-06 19:17:15,759\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 42/1000\n", + "2026-07-06 19:17:15,759\tINFO logging_progress.py:233 -- Tasks: 12; Actors: 6; Queued blocks: 941 (8.7GiB); Resources: 36.0 CPU, 120.0MiB object store; [all objects local]\n", + "2026-07-06 19:17:15,759\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:17:15,760\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 42 (105.0MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:17:15,760\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:17:15,760\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:17:15,760\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:17:15,761\tINFO logging_progress.py:192 -- ============================================\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m Failed to convert column 'clips' into pyarrow array due to: Error converting data to Arrow: [[('1d9fd32b-73fa-502a-8b35-f08077ca27e9', (0.0, 6.266667))]]; falling back to serialize as pickled python objects\u001b[32m [repeated 6x across cluster] (Ray deduplicates logs by default. Set RAY_DEDUP_LOGS=0 to disable log deduplication, or see https://docs.ray.io/en/master/ray-observability/user-guides/configure-logging.html#log-deduplication for more options.)\u001b[0m\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m Traceback (most recent call last):\u001b[32m [repeated 12x across cluster]\u001b[0m\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 400, in _convert_to_pyarrow_native_array\u001b[32m [repeated 12x across cluster]\u001b[0m\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m return pa.array(column_values, type=pa_type)\u001b[32m [repeated 6x across cluster]\u001b[0m\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m ~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\u001b[32m [repeated 6x across cluster]\u001b[0m\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m File \"pyarrow/array.pxi\", line 375, in pyarrow.lib.array\u001b[32m [repeated 6x across cluster]\u001b[0m\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m File \"pyarrow/array.pxi\", line 46, in pyarrow.lib._sequence_to_array\u001b[32m [repeated 6x across cluster]\u001b[0m\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m chunked = GetResultValue(\u001b[32m [repeated 6x across cluster]\u001b[0m\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m File \"pyarrow/error.pxi\", line 155, in pyarrow.lib.pyarrow_internal_check_status\u001b[32m [repeated 6x across cluster]\u001b[0m\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m File \"pyarrow/error.pxi\", line 92, in pyarrow.lib.check_status\u001b[32m [repeated 6x across cluster]\u001b[0m\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m raise convert_status(status)\u001b[32m [repeated 6x across cluster]\u001b[0m\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m pyarrow.lib.ArrowTypeError: Expected bytes, got a 'tuple' object\u001b[32m [repeated 6x across cluster]\u001b[0m\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m The above exception was the direct cause of the following exception:\u001b[32m [repeated 6x across cluster]\u001b[0m\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 299, in convert_to_pyarrow_array\u001b[32m [repeated 6x across cluster]\u001b[0m\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m return _convert_to_pyarrow_native_array(column_values, column_name)\u001b[32m [repeated 6x across cluster]\u001b[0m\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m raise ArrowConversionError(str(column_values)) from e\u001b[32m [repeated 6x across cluster]\u001b[0m\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3091649)\u001b[0m ray.data._internal.tensor_extensions.arrow.ArrowConversionError: Error converting data to Arrow: [[('1d9fd32b-73fa-502a-8b35-f08077ca27e9', (0.0, 6.266667))]]\u001b[32m [repeated 6x across cluster]\u001b[0m\n", + "2026-07-06 19:17:25,817\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:17:25,819\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:17:25,820\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 8.9GiB/93.1GiB object store\n", + "2026-07-06 19:17:25,820\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:17:25,821\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:17:25,821\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:17:25,821\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:17:25,822\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:17:25,822\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:17:25,822\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:17:25,823\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.6GiB object store\n", + "2026-07-06 19:17:25,823\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 103/1000\n", + "2026-07-06 19:17:25,823\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 883 (8.5GiB); Resources: 42.0 CPU, 276.2MiB object store; [all objects local]\n", + "2026-07-06 19:17:25,824\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:17:25,824\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 103 (258.7MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:17:25,824\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:17:25,825\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:17:25,825\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:17:25,825\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:17:35,887\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:17:35,889\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:17:35,890\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 8.5GiB/93.1GiB object store\n", + "2026-07-06 19:17:35,890\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:17:35,890\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:17:35,891\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:17:35,891\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:17:35,891\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:17:35,892\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:17:35,892\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:17:35,893\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.1GiB object store\n", + "2026-07-06 19:17:35,893\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 166/1000\n", + "2026-07-06 19:17:35,893\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 820 (7.9GiB); Resources: 42.0 CPU, 418.1MiB object store; [all objects local]\n", + "2026-07-06 19:17:35,894\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:17:35,894\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 166 (401.2MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:17:35,895\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:17:35,895\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:17:35,895\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:17:35,895\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:17:45,936\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:17:45,938\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:17:45,939\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 7.9GiB/93.1GiB object store\n", + "2026-07-06 19:17:45,940\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:17:45,940\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:17:45,941\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:17:45,941\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:17:45,942\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:17:45,942\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:17:45,942\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:17:45,943\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 7.4GiB object store\n", + "2026-07-06 19:17:45,944\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 225/1000\n", + "2026-07-06 19:17:45,944\tINFO logging_progress.py:233 -- Tasks: 12; Actors: 7; Queued blocks: 763 (7.2GiB); Resources: 42.0 CPU, 586.7MiB object store; [all objects local]\n", + "2026-07-06 19:17:45,945\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:17:45,945\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 225 (569.0MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:17:45,945\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:17:45,945\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:17:45,946\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:17:45,946\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:17:55,936\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:17:55,937\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:17:55,938\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 7.6GiB/93.1GiB object store\n", + "2026-07-06 19:17:55,938\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:17:55,939\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:17:55,939\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:17:55,939\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:17:55,939\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:17:55,940\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:17:55,940\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:17:55,941\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 6.9GiB object store\n", + "2026-07-06 19:17:55,941\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 289/1000\n", + "2026-07-06 19:17:55,941\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 697 (6.7GiB); Resources: 42.0 CPU, 723.8MiB object store; [all objects local]\n", + "2026-07-06 19:17:55,941\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:17:55,942\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 289 (706.7MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:17:55,942\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:17:55,942\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:17:55,942\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:17:55,943\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:18:06,045\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:18:06,047\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:18:06,049\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 7.0GiB/93.1GiB object store\n", + "2026-07-06 19:18:06,049\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:18:06,050\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:18:06,050\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:18:06,051\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:18:06,051\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:18:06,052\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:18:06,052\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:18:06,053\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 6.2GiB object store\n", + "2026-07-06 19:18:06,053\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 354/1000\n", + "2026-07-06 19:18:06,053\tINFO logging_progress.py:233 -- Tasks: 13; Actors: 7; Queued blocks: 633 (6.0GiB); Resources: 42.0 CPU, 875.1MiB object store; [all objects local]\n", + "2026-07-06 19:18:06,054\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:18:06,054\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 354 (858.1MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:18:06,054\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:18:06,057\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:18:06,057\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:18:06,058\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:18:16,155\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:18:16,157\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:18:16,159\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 6.6GiB/93.1GiB object store\n", + "2026-07-06 19:18:16,161\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:18:16,162\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:18:16,163\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:18:16,164\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:18:16,164\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:18:16,166\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:18:16,167\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:18:16,168\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 5.6GiB object store\n", + "2026-07-06 19:18:16,168\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 420/1000\n", + "2026-07-06 19:18:16,170\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 566 (5.4GiB); Resources: 42.0 CPU, 1019.4MiB object store; [all objects local]\n", + "2026-07-06 19:18:16,171\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:18:16,172\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 420 (1002.7MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:18:16,173\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:18:16,173\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:18:16,174\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:18:16,175\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:18:26,220\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:18:26,223\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:18:26,224\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 6.2GiB/93.1GiB object store\n", + "2026-07-06 19:18:26,225\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:18:26,226\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:18:26,226\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:18:26,227\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:18:26,227\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:18:26,228\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:18:26,228\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:18:26,229\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 5.1GiB object store\n", + "2026-07-06 19:18:26,229\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 490/1000\n", + "2026-07-06 19:18:26,229\tINFO logging_progress.py:233 -- Tasks: 13; Actors: 7; Queued blocks: 497 (5.0GiB); Resources: 42.0 CPU, 1.1GiB object store; [all objects local]\n", + "2026-07-06 19:18:26,230\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:18:26,231\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 490 (1.1GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:18:26,232\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:18:26,232\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:18:26,232\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:18:26,233\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:18:36,238\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:18:36,239\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:18:36,240\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 5.8GiB/93.1GiB object store\n", + "2026-07-06 19:18:36,241\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:18:36,242\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:18:36,242\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:18:36,243\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:18:36,243\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:18:36,243\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:18:36,243\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:18:36,244\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 4.5GiB object store\n", + "2026-07-06 19:18:36,244\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 547/1000\n", + "2026-07-06 19:18:36,245\tINFO logging_progress.py:233 -- Tasks: 13; Actors: 7; Queued blocks: 440 (4.4GiB); Resources: 42.0 CPU, 1.3GiB object store; [all objects local]\n", + "2026-07-06 19:18:36,245\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:18:36,245\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 547 (1.3GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:18:36,246\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:18:36,246\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:18:36,247\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:18:36,247\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:18:46,347\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:18:46,349\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:18:46,350\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 5.4GiB/93.1GiB object store\n", + "2026-07-06 19:18:46,351\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:18:46,352\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:18:46,353\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:18:46,354\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:18:46,355\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:18:46,356\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:18:46,356\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:18:46,356\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 3.9GiB object store\n", + "2026-07-06 19:18:46,357\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 615/1000\n", + "2026-07-06 19:18:46,357\tINFO logging_progress.py:233 -- Tasks: 12; Actors: 7; Queued blocks: 373 (3.8GiB); Resources: 42.0 CPU, 1.4GiB object store; [all objects local]\n", + "2026-07-06 19:18:46,358\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:18:46,358\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 615 (1.4GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:18:46,359\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:18:46,360\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:18:46,361\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:18:46,361\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:18:56,375\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:18:56,377\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:18:56,378\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 4.7GiB/93.1GiB object store\n", + "2026-07-06 19:18:56,379\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:18:56,380\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:18:56,380\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:18:56,381\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:18:56,381\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:18:56,382\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:18:56,384\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:18:56,384\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 3.1GiB object store\n", + "2026-07-06 19:18:56,385\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 673/1000\n", + "2026-07-06 19:18:56,386\tINFO logging_progress.py:233 -- Tasks: 12; Actors: 7; Queued blocks: 315 (3.0GiB); Resources: 42.0 CPU, 1.6GiB object store; [all objects local]\n", + "2026-07-06 19:18:56,386\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:18:56,387\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 673 (1.6GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:18:56,387\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:18:56,388\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:18:56,388\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:18:56,389\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:19:06,402\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:19:06,403\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:19:06,403\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 4.3GiB/93.1GiB object store\n", + "2026-07-06 19:19:06,404\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:19:06,404\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:19:06,404\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:19:06,405\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:19:06,405\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:19:06,405\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:19:06,405\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:19:06,405\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 2.6GiB object store\n", + "2026-07-06 19:19:06,406\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 732/1000\n", + "2026-07-06 19:19:06,406\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 254 (2.4GiB); Resources: 42.0 CPU, 1.7GiB object store; [all objects local]\n", + "2026-07-06 19:19:06,406\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:19:06,407\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 732 (1.7GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:19:06,407\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:19:06,407\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:19:06,407\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:19:06,408\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:19:16,461\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:19:16,463\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:19:16,465\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 3.9GiB/93.1GiB object store\n", + "2026-07-06 19:19:16,465\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:19:16,466\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:19:16,467\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:19:16,467\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:19:16,467\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:19:16,468\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:19:16,468\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:19:16,468\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 2.0GiB object store\n", + "2026-07-06 19:19:16,469\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 799/1000\n", + "2026-07-06 19:19:16,469\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 187 (1.8GiB); Resources: 42.0 CPU, 1.9GiB object store; [all objects local]\n", + "2026-07-06 19:19:16,469\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:19:16,470\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 799 (1.8GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:19:16,470\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:19:16,471\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:19:16,471\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:19:16,471\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:19:26,467\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:19:26,469\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:19:26,470\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 3.2GiB/93.1GiB object store\n", + "2026-07-06 19:19:26,471\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:19:26,471\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:19:26,472\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:19:26,472\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:19:26,473\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:19:26,473\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:19:26,473\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:19:26,474\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 1.2GiB object store\n", + "2026-07-06 19:19:26,474\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 860/1000\n", + "2026-07-06 19:19:26,475\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 126 (1.1GiB); Resources: 42.0 CPU, 2.0GiB object store; [all objects local]\n", + "2026-07-06 19:19:26,475\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:19:26,475\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 860 (2.0GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:19:26,476\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:19:26,476\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:19:26,476\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:19:26,476\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:19:36,531\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:19:36,532\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:19:36,534\tINFO logging_progress.py:227 -- Active & requested resources: 42/64 CPU, 2.9GiB/93.1GiB object store\n", + "2026-07-06 19:19:36,535\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:19:36,536\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:19:36,536\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:19:36,537\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:19:36,537\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:19:36,537\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:19:36,538\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:19:36,538\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 781.3MiB object store\n", + "2026-07-06 19:19:36,538\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 927/1000\n", + "2026-07-06 19:19:36,539\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 7; Queued blocks: 59 (627.0MiB); Resources: 42.0 CPU, 2.1GiB object store; [all objects local]\n", + "2026-07-06 19:19:36,539\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:19:36,539\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 927 (2.1GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:19:36,539\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:19:36,540\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:19:36,540\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:19:36,540\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:19:46,547\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:19:46,550\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:19:46,551\tINFO logging_progress.py:227 -- Active & requested resources: 36/64 CPU, 2.4GiB/93.1GiB object store\n", + "2026-07-06 19:19:46,552\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:19:46,553\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:19:46,553\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:19:46,555\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:19:46,555\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:19:46,556\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:19:46,557\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:19:46,557\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 158.8MiB object store\n", + "2026-07-06 19:19:46,559\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 994/1000\n", + "2026-07-06 19:19:46,560\tINFO logging_progress.py:233 -- Tasks: 6; Actors: 6; Queued blocks: 0 (0.0B); Resources: 36.0 CPU, 2.3GiB object store; [all objects local]\n", + "2026-07-06 19:19:46,560\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:19:46,561\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 994 (2.3GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:19:46,561\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:19:46,562\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:19:46,562\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:19:46,562\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:19:56,601\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:19:56,603\tINFO logging_progress.py:225 -- Total Progress: 12/20000\n", + "2026-07-06 19:19:56,605\tINFO logging_progress.py:227 -- Active & requested resources: 64/64 CPU, 2.3GiB/93.1GiB object store\n", + "2026-07-06 19:19:56,605\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:19:56,606\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:19:56,607\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:19:56,607\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:19:56,608\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:19:56,609\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:19:56,610\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:19:56,611\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:19:56,612\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:19:56,614\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:19:56,615\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:19:56,616\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 2.3GiB object store; 1000 rows output\n", + "2026-07-06 19:19:56,618\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:19:56,619\tINFO logging_progress.py:231 -- MapBatches(write_clips): 15/20000\n", + "2026-07-06 19:19:56,620\tINFO logging_progress.py:233 -- Tasks: 256 [backpressured:tasks(ResourceBudget)]; Actors: 0; Queued blocks: 19729 (1.6GiB); Resources: 64.0 CPU, 35.3KiB object store\n", + "2026-07-06 19:19:56,621\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:20:06,604\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:20:06,607\tINFO logging_progress.py:225 -- Total Progress: 12/20000\n", + "2026-07-06 19:20:06,608\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n", + "2026-07-06 19:20:06,609\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:20:06,610\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:20:06,610\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:20:06,611\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:20:06,619\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:20:06,620\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:20:06,620\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:20:06,621\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:20:06,623\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:20:06,624\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:20:06,625\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:20:06,628\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n", + "2026-07-06 19:20:06,629\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:20:06,630\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n", + "2026-07-06 19:20:06,630\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 128.1KiB object store\n", + "2026-07-06 19:20:06,631\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:20:16,607\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:20:16,610\tINFO logging_progress.py:225 -- Total Progress: 13/20000\n", + "2026-07-06 19:20:16,611\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n", + "2026-07-06 19:20:16,612\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:20:16,612\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:20:16,613\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:20:16,614\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:20:16,615\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:20:16,615\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:20:16,617\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:20:16,619\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:20:16,621\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:20:16,622\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:20:16,623\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:20:16,624\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n", + "2026-07-06 19:20:16,625\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:20:16,625\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n", + "2026-07-06 19:20:16,626\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 128.1KiB object store\n", + "2026-07-06 19:20:16,627\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:20:26,610\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:20:26,614\tINFO logging_progress.py:225 -- Total Progress: 118/20000\n", + "2026-07-06 19:20:26,615\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n", + "2026-07-06 19:20:26,616\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:20:26,617\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:20:26,618\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:20:26,619\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:20:26,620\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:20:26,621\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:20:26,621\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:20:26,622\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:20:26,623\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:20:26,624\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:20:26,625\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:20:26,625\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n", + "2026-07-06 19:20:26,626\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:20:26,627\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n", + "2026-07-06 19:20:26,627\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 114.6KiB object store\n", + "2026-07-06 19:20:26,627\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:20:36,610\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:20:36,613\tINFO logging_progress.py:225 -- Total Progress: 131/20000\n", + "2026-07-06 19:20:36,615\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n", + "2026-07-06 19:20:36,616\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:20:36,617\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:20:36,618\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:20:36,619\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:20:36,620\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:20:36,620\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:20:36,621\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:20:36,622\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:20:36,623\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:20:36,625\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:20:36,626\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:20:36,627\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n", + "2026-07-06 19:20:36,627\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:20:36,628\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n", + "2026-07-06 19:20:36,630\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 112.9KiB object store\n", + "2026-07-06 19:20:36,631\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:20:46,616\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:20:46,621\tINFO logging_progress.py:225 -- Total Progress: 132/20000\n", + "2026-07-06 19:20:46,625\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n", + "2026-07-06 19:20:46,626\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:20:46,627\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:20:46,628\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:20:46,629\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:20:46,630\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:20:46,630\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:20:46,631\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:20:46,632\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:20:46,633\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:20:46,634\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:20:46,635\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:20:46,636\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n", + "2026-07-06 19:20:46,636\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:20:46,637\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n", + "2026-07-06 19:20:46,638\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 112.8KiB object store\n", + "2026-07-06 19:20:46,639\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:20:56,625\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:20:56,628\tINFO logging_progress.py:225 -- Total Progress: 137/20000\n", + "2026-07-06 19:20:56,629\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n", + "2026-07-06 19:20:56,630\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:20:56,631\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:20:56,632\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:20:56,633\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:20:56,634\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:20:56,635\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:20:56,636\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:20:56,636\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:20:56,637\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:20:56,639\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:20:56,639\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:20:56,640\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n", + "2026-07-06 19:20:56,640\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:20:56,641\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n", + "2026-07-06 19:20:56,642\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 112.2KiB object store\n", + "2026-07-06 19:20:56,642\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:21:06,630\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:21:06,632\tINFO logging_progress.py:225 -- Total Progress: 165/20000\n", + "2026-07-06 19:21:06,634\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n", + "2026-07-06 19:21:06,635\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:21:06,637\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:21:06,638\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:21:06,639\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:21:06,639\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:21:06,640\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:21:06,642\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:21:06,642\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:21:06,644\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:21:06,645\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:21:06,646\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:21:06,647\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n", + "2026-07-06 19:21:06,648\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:21:06,649\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n", + "2026-07-06 19:21:06,650\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 108.4KiB object store\n", + "2026-07-06 19:21:06,651\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:21:16,640\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:21:16,642\tINFO logging_progress.py:225 -- Total Progress: 229/20000\n", + "2026-07-06 19:21:16,643\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n", + "2026-07-06 19:21:16,650\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:21:16,650\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:21:16,652\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:21:16,653\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:21:16,654\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:21:16,655\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:21:16,657\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:21:16,658\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:21:16,660\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:21:16,663\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:21:16,668\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:21:16,668\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n", + "2026-07-06 19:21:16,670\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:21:16,670\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n", + "2026-07-06 19:21:16,671\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 99.7KiB object store\n", + "2026-07-06 19:21:16,672\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:21:26,640\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:21:26,643\tINFO logging_progress.py:225 -- Total Progress: 323/20000\n", + "2026-07-06 19:21:26,652\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n", + "2026-07-06 19:21:26,653\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:21:26,654\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:21:26,655\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:21:26,656\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:21:26,657\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:21:26,657\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:21:26,659\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:21:26,660\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:21:26,660\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:21:26,661\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:21:26,662\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:21:26,662\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n", + "2026-07-06 19:21:26,663\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:21:26,663\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n", + "2026-07-06 19:21:26,663\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 87.4KiB object store\n", + "2026-07-06 19:21:26,664\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:21:36,643\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:21:36,647\tINFO logging_progress.py:225 -- Total Progress: 358/20000\n", + "2026-07-06 19:21:36,648\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n", + "2026-07-06 19:21:36,649\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:21:36,649\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:21:36,650\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:21:36,652\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:21:36,653\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:21:36,654\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:21:36,654\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:21:36,655\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:21:36,656\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:21:36,656\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:21:36,657\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:21:36,657\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n", + "2026-07-06 19:21:36,657\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:21:36,658\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n", + "2026-07-06 19:21:36,659\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 82.8KiB object store\n", + "2026-07-06 19:21:36,659\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:21:46,648\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:21:46,650\tINFO logging_progress.py:225 -- Total Progress: 360/20000\n", + "2026-07-06 19:21:46,651\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n", + "2026-07-06 19:21:46,652\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:21:46,652\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:21:46,653\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:21:46,653\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:21:46,654\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:21:46,655\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:21:46,655\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:21:46,656\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:21:46,656\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:21:46,657\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:21:46,657\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:21:46,658\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n", + "2026-07-06 19:21:46,658\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:21:46,659\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n", + "2026-07-06 19:21:46,659\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 82.6KiB object store\n", + "2026-07-06 19:21:46,660\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:21:56,652\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:21:56,654\tINFO logging_progress.py:225 -- Total Progress: 362/20000\n", + "2026-07-06 19:21:56,655\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n", + "2026-07-06 19:21:56,656\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:21:56,656\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:21:56,657\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:21:56,657\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:21:56,658\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:21:56,659\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:21:56,660\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:21:56,660\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:21:56,661\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:21:56,661\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:21:56,662\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:21:56,663\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n", + "2026-07-06 19:21:56,663\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:21:56,664\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n", + "2026-07-06 19:21:56,664\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 82.3KiB object store\n", + "2026-07-06 19:21:56,665\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:22:06,662\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:22:06,674\tINFO logging_progress.py:225 -- Total Progress: 366/20000\n", + "2026-07-06 19:22:06,681\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n", + "2026-07-06 19:22:06,688\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:22:06,692\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:22:06,696\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:22:06,701\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:22:06,703\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:22:06,705\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:22:06,706\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:22:06,708\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:22:06,712\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:22:06,716\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:22:06,718\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:22:06,719\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n", + "2026-07-06 19:22:06,720\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:22:06,724\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n", + "2026-07-06 19:22:06,725\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 82.2KiB object store\n", + "2026-07-06 19:22:06,727\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:22:16,676\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:22:16,679\tINFO logging_progress.py:225 -- Total Progress: 473/20000\n", + "2026-07-06 19:22:16,683\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n", + "2026-07-06 19:22:16,683\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:22:16,684\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:22:16,684\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:22:16,685\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:22:16,688\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:22:16,697\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:22:16,703\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:22:16,711\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:22:16,715\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:22:16,715\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:22:16,716\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:22:16,717\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n", + "2026-07-06 19:22:16,720\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:22:16,723\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n", + "2026-07-06 19:22:16,725\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 68.1KiB object store\n", + "2026-07-06 19:22:16,726\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:22:26,683\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:22:26,684\tINFO logging_progress.py:225 -- Total Progress: 552/20000\n", + "2026-07-06 19:22:26,685\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n", + "2026-07-06 19:22:26,686\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:22:26,686\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:22:26,687\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:22:26,687\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:22:26,688\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:22:26,688\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:22:26,689\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:22:26,689\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:22:26,689\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:22:26,690\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:22:26,691\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:22:26,691\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n", + "2026-07-06 19:22:26,692\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:22:26,693\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n", + "2026-07-06 19:22:26,694\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 57.9KiB object store\n", + "2026-07-06 19:22:26,694\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:22:36,684\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_7_0 =======\n", + "2026-07-06 19:22:36,686\tINFO logging_progress.py:225 -- Total Progress: 571/20000\n", + "2026-07-06 19:22:36,688\tINFO logging_progress.py:227 -- Active & requested resources: 31.5/64 CPU, 534.7MiB/93.1GiB object store\n", + "2026-07-06 19:22:36,689\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:22:36,690\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:22:36,691\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:22:36,691\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:22:36,692\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:22:36,694\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:22:36,695\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:22:36,695\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:22:36,696\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:22:36,696\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:22:36,697\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:22:36,698\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 534.6MiB object store; 1000 rows output\n", + "2026-07-06 19:22:36,698\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:22:36,698\tINFO logging_progress.py:231 -- MapBatches(write_clips): 799/20000\n", + "2026-07-06 19:22:36,699\tINFO logging_progress.py:233 -- Tasks: 201; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 50.2 CPU, 55.6KiB object store\n", + "2026-07-06 19:22:36,700\tINFO logging_progress.py:192 -- ============================================\n", + "2026-07-06 19:22:44,446\tINFO streaming_executor.py:294 -- ✔️ Dataset dataset_7_0 execution finished in 359.76 seconds\n" + ] }, { "name": "stdout", "output_type": "stream", - "text": "[ActorPool(min=1, max=N, initial=N)] 1000 videos, 1000 clip-chunks, 360.6s \u2014 2.77 vid/s\n" + "text": [ + "[ActorPool(min=1, max=N, initial=N)] 1000 videos, 1000 clip-chunks, 360.6s — 2.77 vid/s\n" + ] }, { "name": "stderr", "output_type": "stream", - "text": "2026-07-06 19:22:45,147\tINFO logging.py:416 -- Registered dataset logger for dataset dataset_15_0\n2026-07-06 19:22:45,156\tINFO streaming_executor.py:166 -- Starting execution of Dataset dataset_15_0. Full logs are in /tmp/ray/session_2026-07-06_19-16-28_966894_3085811/logs/ray-data\n2026-07-06 19:22:45,158\tINFO streaming_executor.py:167 -- Execution plan of Dataset dataset_15_0: InputDataBuffer[Input] -> TaskPoolMapOperator[MapBatches(ls_videos)] -> AllToAllOperator[Repartition] -> TaskPoolMapOperator[MapBatches(read_and_probe)->MapBatches(split_fixed_stride)] -> ActorPoolMapOperator[MapBatches(TranscodeActor)] -> AllToAllOperator[Repartition] -> TaskPoolMapOperator[MapBatches(write_clips)]\n2026-07-06 19:22:45,453\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:22:45,455\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:22:45,455\tINFO logging_progress.py:227 -- Active & requested resources: 0/64 CPU, 0.0B/93.1GiB object store (pending: 54 CPU)\n2026-07-06 19:22:45,456\tINFO logging_progress.py:181 -- \n2026-07-06 19:22:45,456\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 0/1\n2026-07-06 19:22:45,456\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store\n2026-07-06 19:22:45,457\tINFO logging_progress.py:231 -- Repartition: 0/1\n2026-07-06 19:22:45,457\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n2026-07-06 19:22:45,458\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:22:45,458\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 0/1\n2026-07-06 19:22:45,458\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:45,459\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 0/1\n2026-07-06 19:22:45,459\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 9 (running=0, restarting=0, pending=9); Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:22:45,460\tINFO logging_progress.py:231 -- Repartition: 0/1\n2026-07-06 19:22:45,460\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n2026-07-06 19:22:45,461\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:22:45,461\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:22:45,461\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:45,462\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:22:55,460\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:22:55,462\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:22:55,466\tINFO logging_progress.py:227 -- Active & requested resources: 55/64 CPU, 0.0B/93.1GiB object store\n2026-07-06 19:22:55,467\tINFO logging_progress.py:181 -- \n2026-07-06 19:22:55,468\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 0/1\n2026-07-06 19:22:55,468\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store\n2026-07-06 19:22:55,469\tINFO logging_progress.py:231 -- Repartition: 0/1\n2026-07-06 19:22:55,469\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n2026-07-06 19:22:55,470\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:22:55,471\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 0/1\n2026-07-06 19:22:55,473\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:55,473\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 0/1\n2026-07-06 19:22:55,474\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 9; Queued blocks: 0 (0.0B); Resources: 54.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:22:55,475\tINFO logging_progress.py:231 -- Repartition: 0/1\n2026-07-06 19:22:55,476\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n2026-07-06 19:22:55,476\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:22:55,477\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:22:55,477\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:22:55,478\tINFO logging_progress.py:192 -- =============================================\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m Failed to convert column 'clips' into pyarrow array due to: Error converting data to Arrow: [[('4dd9dc83-4c11-52b2-8123-e981a60d61f4', (0.0, 2.902903))]]; falling back to serialize as pickled python objects\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m Traceback (most recent call last):\u001b[32m [repeated 2x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 400, in _convert_to_pyarrow_native_array\u001b[32m [repeated 2x across cluster]\u001b[0m\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m return pa.array(column_values, type=pa_type)\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m ~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m File \"pyarrow/array.pxi\", line 375, in pyarrow.lib.array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m File \"pyarrow/array.pxi\", line 46, in pyarrow.lib._sequence_to_array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m chunked = GetResultValue(\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m File \"pyarrow/error.pxi\", line 155, in pyarrow.lib.pyarrow_internal_check_status\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m File \"pyarrow/error.pxi\", line 92, in pyarrow.lib.check_status\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m raise convert_status(status)\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m pyarrow.lib.ArrowTypeError: Expected bytes, got a 'tuple' object\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m The above exception was the direct cause of the following exception:\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 299, in convert_to_pyarrow_array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m return _convert_to_pyarrow_native_array(column_values, column_name)\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m raise ArrowConversionError(str(column_values)) from e\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m ray.data._internal.tensor_extensions.arrow.ArrowConversionError: Error converting data to Arrow: [[('4dd9dc83-4c11-52b2-8123-e981a60d61f4', (0.0, 2.902903))]]\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m Failed to convert column 'clips' into pyarrow array due to: Error converting data to Arrow: [[('e58f0e20-a3ed-5a16-9c78-62c7acdb162f', (0.0, 3.76))]]; falling back to serialize as pickled python objects\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m return pa.array(column_values, type=pa_type)\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m ~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m File \"pyarrow/array.pxi\", line 375, in pyarrow.lib.array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m File \"pyarrow/array.pxi\", line 46, in pyarrow.lib._sequence_to_array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m chunked = GetResultValue(\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m File \"pyarrow/error.pxi\", line 155, in pyarrow.lib.pyarrow_internal_check_status\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m File \"pyarrow/error.pxi\", line 92, in pyarrow.lib.check_status\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m raise convert_status(status)\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m pyarrow.lib.ArrowTypeError: Expected bytes, got a 'tuple' object\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m The above exception was the direct cause of the following exception:\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 299, in convert_to_pyarrow_array\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m return _convert_to_pyarrow_native_array(column_values, column_name)\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m raise ArrowConversionError(str(column_values)) from e\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m ray.data._internal.tensor_extensions.arrow.ArrowConversionError: Error converting data to Arrow: [[('e58f0e20-a3ed-5a16-9c78-62c7acdb162f', (0.0, 3.76))]]\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147839)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147839)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147836)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147836)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147835)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147835)\u001b[0m \n2026-07-06 19:23:05,483\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:23:05,485\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:23:05,487\tINFO logging_progress.py:227 -- Active & requested resources: 55/64 CPU, 1.5GiB/93.1GiB object store\n2026-07-06 19:23:05,488\tINFO logging_progress.py:181 -- \n2026-07-06 19:23:05,489\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:23:05,490\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:05,490\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:23:05,490\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 60.2KiB object store; 1000 rows output\n2026-07-06 19:23:05,491\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:23:05,491\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 169/1000\n2026-07-06 19:23:05,491\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 830 (60.1KiB); Resources: 1.0 CPU, 1.4GiB object store\n2026-07-06 19:23:05,492\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 5/1000\n2026-07-06 19:23:05,492\tINFO logging_progress.py:233 -- Tasks: 15; Actors: 9; Queued blocks: 149 (1.2GiB); Resources: 54.0 CPU, 21.3MiB object store; [all objects local]\n2026-07-06 19:23:05,492\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:23:05,493\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 5 (7.6MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:23:05,493\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:23:05,493\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:23:05,494\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:05,494\tINFO logging_progress.py:192 -- =============================================\n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147832)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147832)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147831)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147831)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147838)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147838)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147833)\u001b[0m \n\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147833)\u001b[0m \n2026-07-06 19:23:15,585\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:23:15,587\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:23:15,589\tINFO logging_progress.py:227 -- Active & requested resources: 55/64 CPU, 8.2GiB/93.1GiB object store\n2026-07-06 19:23:15,589\tINFO logging_progress.py:181 -- \n2026-07-06 19:23:15,590\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:23:15,590\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:15,590\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:23:15,591\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 5.6KiB object store; 1000 rows output\n2026-07-06 19:23:15,591\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:23:15,591\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 922/1000\n2026-07-06 19:23:15,591\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 77 (5.6KiB); Resources: 1.0 CPU, 7.9GiB object store\n2026-07-06 19:23:15,592\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 86/1000\n2026-07-06 19:23:15,592\tINFO logging_progress.py:233 -- Tasks: 17; Actors: 9; Queued blocks: 819 (7.8GiB); Resources: 54.0 CPU, 247.8MiB object store; [all objects local]\n2026-07-06 19:23:15,592\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:23:15,592\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 86 (224.3MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:23:15,593\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:23:15,593\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:23:15,593\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:15,594\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:23:25,684\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:23:25,686\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:23:25,688\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 8.5GiB/93.1GiB object store\n2026-07-06 19:23:25,689\tINFO logging_progress.py:181 -- \n2026-07-06 19:23:25,690\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:23:25,691\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:25,691\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:23:25,692\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:23:25,692\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:23:25,692\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:23:25,693\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.1GiB object store\n2026-07-06 19:23:25,693\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 166/1000\n2026-07-06 19:23:25,693\tINFO logging_progress.py:233 -- Tasks: 17; Actors: 9; Queued blocks: 817 (7.9GiB); Resources: 54.0 CPU, 440.5MiB object store; [all objects local]\n2026-07-06 19:23:25,694\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:23:25,695\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 166 (417.9MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:23:25,695\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:23:25,695\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:23:25,696\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:25,696\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:23:35,765\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:23:35,768\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:23:35,770\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 7.8GiB/93.1GiB object store\n2026-07-06 19:23:35,771\tINFO logging_progress.py:181 -- \n2026-07-06 19:23:35,772\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:23:35,773\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:35,774\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:23:35,774\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:23:35,775\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:23:35,776\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:23:35,777\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 7.2GiB object store\n2026-07-06 19:23:35,777\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 243/1000\n2026-07-06 19:23:35,778\tINFO logging_progress.py:233 -- Tasks: 17; Actors: 9; Queued blocks: 740 (7.0GiB); Resources: 54.0 CPU, 641.2MiB object store; [all objects local]\n2026-07-06 19:23:35,778\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:23:35,779\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 243 (618.3MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:23:35,780\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:23:35,780\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:23:35,780\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:35,781\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:23:45,780\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:23:45,783\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:23:45,784\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 7.3GiB/93.1GiB object store\n2026-07-06 19:23:45,785\tINFO logging_progress.py:181 -- \n2026-07-06 19:23:45,786\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:23:45,787\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:45,788\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:23:45,789\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:23:45,790\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:23:45,791\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:23:45,791\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 6.5GiB object store\n2026-07-06 19:23:45,792\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 326/1000\n2026-07-06 19:23:45,792\tINFO logging_progress.py:233 -- Tasks: 17; Actors: 9; Queued blocks: 657 (6.2GiB); Resources: 54.0 CPU, 803.8MiB object store; [all objects local]\n2026-07-06 19:23:45,792\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:23:45,793\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 326 (782.2MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:23:45,793\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:23:45,793\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:23:45,794\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:45,794\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:23:55,854\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:23:55,856\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:23:55,858\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 6.6GiB/93.1GiB object store\n2026-07-06 19:23:55,859\tINFO logging_progress.py:181 -- \n2026-07-06 19:23:55,860\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:23:55,861\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:55,861\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:23:55,861\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:23:55,862\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:23:55,863\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:23:55,863\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 5.6GiB object store\n2026-07-06 19:23:55,863\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 411/1000\n2026-07-06 19:23:55,864\tINFO logging_progress.py:233 -- Tasks: 16; Actors: 9; Queued blocks: 573 (5.5GiB); Resources: 54.0 CPU, 1014.8MiB object store; [all objects local]\n2026-07-06 19:23:55,864\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:23:55,864\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 411 (993.0MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:23:55,865\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:23:55,865\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:23:55,866\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:23:55,866\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:24:05,859\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:24:05,860\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:24:05,861\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 6.2GiB/93.1GiB object store\n2026-07-06 19:24:05,861\tINFO logging_progress.py:181 -- \n2026-07-06 19:24:05,862\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:24:05,863\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:05,863\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:24:05,863\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:05,864\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:24:05,864\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:24:05,864\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 5.0GiB object store\n2026-07-06 19:24:05,864\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 500/1000\n2026-07-06 19:24:05,865\tINFO logging_progress.py:233 -- Tasks: 18; Actors: 9; Queued blocks: 482 (4.7GiB); Resources: 54.0 CPU, 1.2GiB object store; [all objects local]\n2026-07-06 19:24:05,865\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:24:05,866\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 500 (1.1GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:05,866\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:24:05,867\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:24:05,867\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:05,867\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:24:15,902\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:24:15,903\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:24:15,904\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 5.6GiB/93.1GiB object store\n2026-07-06 19:24:15,905\tINFO logging_progress.py:181 -- \n2026-07-06 19:24:15,905\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:24:15,906\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:15,906\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:24:15,907\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:15,907\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:24:15,908\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:24:15,908\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 4.2GiB object store\n2026-07-06 19:24:15,909\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 577/1000\n2026-07-06 19:24:15,909\tINFO logging_progress.py:233 -- Tasks: 18; Actors: 9; Queued blocks: 405 (4.1GiB); Resources: 54.0 CPU, 1.3GiB object store; [all objects local]\n2026-07-06 19:24:15,910\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:24:15,911\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 577 (1.3GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:15,911\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:24:15,912\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:24:15,913\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:15,913\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:24:25,905\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:24:25,907\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:24:25,909\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 4.9GiB/93.1GiB object store\n2026-07-06 19:24:25,910\tINFO logging_progress.py:181 -- \n2026-07-06 19:24:25,911\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:24:25,912\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:25,912\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:24:25,913\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:25,914\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:24:25,914\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:24:25,915\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 3.4GiB object store\n2026-07-06 19:24:25,916\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 655/1000\n2026-07-06 19:24:25,916\tINFO logging_progress.py:233 -- Tasks: 18; Actors: 9; Queued blocks: 327 (3.1GiB); Resources: 54.0 CPU, 1.5GiB object store; [all objects local]\n2026-07-06 19:24:25,917\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:24:25,919\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 655 (1.5GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:25,920\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:24:25,920\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:24:25,920\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:25,921\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:24:36,014\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:24:36,016\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:24:36,017\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 4.3GiB/93.1GiB object store\n2026-07-06 19:24:36,018\tINFO logging_progress.py:181 -- \n2026-07-06 19:24:36,019\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:24:36,020\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:36,021\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:24:36,021\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:36,022\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:24:36,023\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:24:36,023\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 2.5GiB object store\n2026-07-06 19:24:36,024\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 735/1000\n2026-07-06 19:24:36,025\tINFO logging_progress.py:233 -- Tasks: 17; Actors: 9; Queued blocks: 248 (2.3GiB); Resources: 54.0 CPU, 1.7GiB object store; [all objects local]\n2026-07-06 19:24:36,026\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:24:36,026\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 735 (1.7GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:36,027\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:24:36,028\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:24:36,028\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:36,029\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:24:46,121\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:24:46,123\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:24:46,125\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 3.7GiB/93.1GiB object store\n2026-07-06 19:24:46,126\tINFO logging_progress.py:181 -- \n2026-07-06 19:24:46,127\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:24:46,128\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:46,128\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:24:46,130\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:46,131\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:24:46,131\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:24:46,131\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 1.8GiB object store\n2026-07-06 19:24:46,132\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 823/1000\n2026-07-06 19:24:46,132\tINFO logging_progress.py:233 -- Tasks: 17; Actors: 9; Queued blocks: 160 (1.4GiB); Resources: 54.0 CPU, 1.9GiB object store; [all objects local]\n2026-07-06 19:24:46,132\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:24:46,132\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 823 (1.9GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:46,133\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:24:46,133\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:24:46,133\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:46,134\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:24:56,221\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:24:56,222\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:24:56,222\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 3.0GiB/93.1GiB object store\n2026-07-06 19:24:56,223\tINFO logging_progress.py:181 -- \n2026-07-06 19:24:56,224\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:24:56,225\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:56,225\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:24:56,225\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:56,226\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:24:56,226\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:24:56,226\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 958.7MiB object store\n2026-07-06 19:24:56,226\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 905/1000\n2026-07-06 19:24:56,227\tINFO logging_progress.py:233 -- Tasks: 17; Actors: 9; Queued blocks: 78 (801.3MiB); Resources: 54.0 CPU, 2.1GiB object store; [all objects local]\n2026-07-06 19:24:56,227\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:24:56,227\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 905 (2.1GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:24:56,227\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:24:56,228\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:24:56,228\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:24:56,228\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:25:06,333\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:25:06,334\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:25:06,335\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 2.5GiB/93.1GiB object store\n2026-07-06 19:25:06,335\tINFO logging_progress.py:181 -- \n2026-07-06 19:25:06,336\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:25:06,336\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:06,337\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:25:06,337\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:25:06,337\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:06,337\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:25:06,338\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 199.3MiB object store\n2026-07-06 19:25:06,338\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 991/1000\n2026-07-06 19:25:06,338\tINFO logging_progress.py:233 -- Tasks: 9; Actors: 9; Queued blocks: 0 (0.0B); Resources: 54.0 CPU, 2.3GiB object store; [all objects local]\n2026-07-06 19:25:06,338\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:25:06,339\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 991 (2.2GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:25:06,340\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n2026-07-06 19:25:06,340\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:25:06,340\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:06,340\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:25:19,206\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:25:19,208\tINFO logging_progress.py:225 -- Total Progress: 0/?\n2026-07-06 19:25:19,209\tINFO logging_progress.py:227 -- Active & requested resources: 6/64 CPU, 2.3GiB/93.1GiB object store\n2026-07-06 19:25:19,209\tINFO logging_progress.py:181 -- \n2026-07-06 19:25:19,210\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:25:19,211\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:19,211\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:25:19,213\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:25:19,214\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:19,215\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:25:19,216\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:19,217\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:25:19,217\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 6.0 CPU, 2.3GiB object store; [all objects local]\n2026-07-06 19:25:19,218\tINFO logging_progress.py:231 -- Repartition: 0/1000\n2026-07-06 19:25:19,218\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:25:19,218\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:19,218\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n2026-07-06 19:25:19,219\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:19,219\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:25:29,207\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:25:29,209\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:25:29,209\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:25:29,210\tINFO logging_progress.py:181 -- \n2026-07-06 19:25:29,210\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:25:29,210\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:29,211\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:25:29,211\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:25:29,211\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:29,212\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:25:29,212\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:29,212\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:25:29,213\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:25:29,213\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:25:29,213\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:25:29,214\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:29,214\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:25:29,214\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:25:29,215\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:25:39,210\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:25:39,214\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:25:39,216\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:25:39,218\tINFO logging_progress.py:181 -- \n2026-07-06 19:25:39,219\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:25:39,219\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:39,220\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:25:39,220\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:25:39,220\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:39,221\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:25:39,221\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:39,222\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:25:39,223\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:25:39,223\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:25:39,224\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:25:39,224\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:39,224\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:25:39,225\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:25:39,225\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:25:49,211\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:25:49,213\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:25:49,215\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:25:49,216\tINFO logging_progress.py:181 -- \n2026-07-06 19:25:49,216\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:25:49,217\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:49,218\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:25:49,219\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:25:49,220\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:49,220\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:25:49,221\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:49,221\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:25:49,221\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:25:49,222\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:25:49,222\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:25:49,223\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:49,223\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:25:49,223\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:25:49,224\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:25:59,211\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:25:59,213\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:25:59,214\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:25:59,214\tINFO logging_progress.py:181 -- \n2026-07-06 19:25:59,215\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:25:59,216\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:59,217\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:25:59,217\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:25:59,218\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:59,218\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:25:59,219\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:25:59,220\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:25:59,220\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:25:59,221\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:25:59,222\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:25:59,222\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:25:59,223\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:25:59,224\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:25:59,225\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:26:09,217\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:26:09,220\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:26:09,222\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:26:09,224\tINFO logging_progress.py:181 -- \n2026-07-06 19:26:09,224\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:26:09,225\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:09,225\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:09,226\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:26:09,227\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:09,227\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:26:09,228\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:09,229\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:26:09,229\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:26:09,230\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:09,231\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:26:09,232\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:09,233\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:26:09,235\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:26:09,236\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:26:19,225\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:26:19,229\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:26:19,231\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:26:19,233\tINFO logging_progress.py:181 -- \n2026-07-06 19:26:19,233\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:26:19,234\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:19,235\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:19,235\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:26:19,236\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:19,236\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:26:19,237\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:19,237\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:26:19,238\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:26:19,238\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:19,238\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:26:19,241\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:19,241\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:26:19,242\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:26:19,242\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:26:29,227\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:26:29,229\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:26:29,230\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:26:29,231\tINFO logging_progress.py:181 -- \n2026-07-06 19:26:29,233\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:26:29,234\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:29,235\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:29,236\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:26:29,236\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:29,238\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:26:29,239\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:29,239\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:26:29,240\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:26:29,241\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:29,242\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:26:29,243\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:29,243\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:26:29,243\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:26:29,243\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:26:39,234\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:26:39,237\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:26:39,239\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:26:39,240\tINFO logging_progress.py:181 -- \n2026-07-06 19:26:39,241\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:26:39,241\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:39,242\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:39,242\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:26:39,243\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:39,243\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:26:39,244\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:39,244\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:26:39,245\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:26:39,245\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:39,246\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:26:39,246\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:39,246\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:26:39,247\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:26:39,247\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:26:49,240\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:26:49,243\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:26:49,245\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:26:49,245\tINFO logging_progress.py:181 -- \n2026-07-06 19:26:49,246\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:26:49,246\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:49,247\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:49,248\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:26:49,248\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:49,250\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:26:49,251\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:49,254\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:26:49,255\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:26:49,257\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:49,257\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:26:49,258\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:49,259\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:26:49,260\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:26:49,260\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:26:59,246\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:26:59,248\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:26:59,250\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:26:59,252\tINFO logging_progress.py:181 -- \n2026-07-06 19:26:59,252\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:26:59,253\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:59,253\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:59,254\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:26:59,255\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:59,255\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:26:59,255\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:26:59,256\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:26:59,256\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:26:59,257\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:26:59,258\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:26:59,258\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:26:59,259\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:26:59,259\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:26:59,260\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:27:09,250\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:27:09,252\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:27:09,253\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:27:09,254\tINFO logging_progress.py:181 -- \n2026-07-06 19:27:09,255\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:27:09,255\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:09,256\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:09,258\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:27:09,258\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:09,259\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:27:09,260\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:09,262\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:27:09,262\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:27:09,263\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:09,263\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:27:09,264\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:09,265\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:27:09,266\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:27:09,267\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:27:19,264\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:27:19,266\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:27:19,267\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:27:19,268\tINFO logging_progress.py:181 -- \n2026-07-06 19:27:19,271\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:27:19,273\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:19,276\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:19,278\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:27:19,280\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:19,281\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:27:19,282\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:19,283\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:27:19,284\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:27:19,285\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:19,285\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:27:19,286\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:19,286\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:27:19,287\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:27:19,287\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:27:29,273\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:27:29,275\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:27:29,276\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:27:29,277\tINFO logging_progress.py:181 -- \n2026-07-06 19:27:29,279\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:27:29,280\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:29,280\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:29,281\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:27:29,281\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:29,281\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:27:29,282\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:29,282\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:27:29,282\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:27:29,283\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:29,283\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:27:29,283\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:29,284\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:27:29,284\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:27:29,284\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:27:39,280\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:27:39,282\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:27:39,283\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:27:39,287\tINFO logging_progress.py:181 -- \n2026-07-06 19:27:39,288\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:27:39,289\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:39,290\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:39,291\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:27:39,291\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:39,292\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:27:39,293\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:39,293\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:27:39,295\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:27:39,296\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:39,296\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:27:39,298\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:39,298\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:27:39,299\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:27:39,299\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:27:49,289\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:27:49,291\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:27:49,294\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:27:49,295\tINFO logging_progress.py:181 -- \n2026-07-06 19:27:49,297\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:27:49,298\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:49,299\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:49,299\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:27:49,300\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:49,300\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:27:49,301\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:49,301\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:27:49,301\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:27:49,302\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:49,303\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:27:49,303\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:49,303\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:27:49,304\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:27:49,304\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:27:59,290\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:27:59,293\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:27:59,295\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:27:59,298\tINFO logging_progress.py:181 -- \n2026-07-06 19:27:59,299\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:27:59,301\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:59,302\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:59,303\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:27:59,304\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:59,305\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:27:59,306\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:27:59,308\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:27:59,308\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:27:59,309\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:27:59,309\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:27:59,309\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:27:59,310\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:27:59,310\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:27:59,310\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:28:09,291\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n2026-07-06 19:28:09,293\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n2026-07-06 19:28:09,294\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n2026-07-06 19:28:09,295\tINFO logging_progress.py:181 -- \n2026-07-06 19:28:09,296\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n2026-07-06 19:28:09,296\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:28:09,297\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:28:09,298\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n2026-07-06 19:28:09,298\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:28:09,299\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n2026-07-06 19:28:09,300\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n2026-07-06 19:28:09,300\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n2026-07-06 19:28:09,301\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n2026-07-06 19:28:09,302\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n2026-07-06 19:28:09,302\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n2026-07-06 19:28:09,303\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n2026-07-06 19:28:09,303\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n2026-07-06 19:28:09,304\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n2026-07-06 19:28:09,304\tINFO logging_progress.py:192 -- =============================================\n2026-07-06 19:28:17,072\tINFO streaming_executor.py:294 -- \u2714\ufe0f Dataset dataset_15_0 execution finished in 331.89 seconds\n" + "text": [ + "2026-07-06 19:22:45,147\tINFO logging.py:416 -- Registered dataset logger for dataset dataset_15_0\n", + "2026-07-06 19:22:45,156\tINFO streaming_executor.py:166 -- Starting execution of Dataset dataset_15_0. Full logs are in /tmp/ray/session_2026-07-06_19-16-28_966894_3085811/logs/ray-data\n", + "2026-07-06 19:22:45,158\tINFO streaming_executor.py:167 -- Execution plan of Dataset dataset_15_0: InputDataBuffer[Input] -> TaskPoolMapOperator[MapBatches(ls_videos)] -> AllToAllOperator[Repartition] -> TaskPoolMapOperator[MapBatches(read_and_probe)->MapBatches(split_fixed_stride)] -> ActorPoolMapOperator[MapBatches(TranscodeActor)] -> AllToAllOperator[Repartition] -> TaskPoolMapOperator[MapBatches(write_clips)]\n", + "2026-07-06 19:22:45,453\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:22:45,455\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:22:45,455\tINFO logging_progress.py:227 -- Active & requested resources: 0/64 CPU, 0.0B/93.1GiB object store (pending: 54 CPU)\n", + "2026-07-06 19:22:45,456\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:22:45,456\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 0/1\n", + "2026-07-06 19:22:45,456\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store\n", + "2026-07-06 19:22:45,457\tINFO logging_progress.py:231 -- Repartition: 0/1\n", + "2026-07-06 19:22:45,457\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n", + "2026-07-06 19:22:45,458\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:22:45,458\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 0/1\n", + "2026-07-06 19:22:45,458\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:22:45,459\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 0/1\n", + "2026-07-06 19:22:45,459\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 9 (running=0, restarting=0, pending=9); Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:22:45,460\tINFO logging_progress.py:231 -- Repartition: 0/1\n", + "2026-07-06 19:22:45,460\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n", + "2026-07-06 19:22:45,461\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:22:45,461\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:22:45,461\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:22:45,462\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:22:55,460\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:22:55,462\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:22:55,466\tINFO logging_progress.py:227 -- Active & requested resources: 55/64 CPU, 0.0B/93.1GiB object store\n", + "2026-07-06 19:22:55,467\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:22:55,468\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 0/1\n", + "2026-07-06 19:22:55,468\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store\n", + "2026-07-06 19:22:55,469\tINFO logging_progress.py:231 -- Repartition: 0/1\n", + "2026-07-06 19:22:55,469\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n", + "2026-07-06 19:22:55,470\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:22:55,471\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 0/1\n", + "2026-07-06 19:22:55,473\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:22:55,473\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 0/1\n", + "2026-07-06 19:22:55,474\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 9; Queued blocks: 0 (0.0B); Resources: 54.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:22:55,475\tINFO logging_progress.py:231 -- Repartition: 0/1\n", + "2026-07-06 19:22:55,476\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n", + "2026-07-06 19:22:55,476\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:22:55,477\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:22:55,477\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:22:55,478\tINFO logging_progress.py:192 -- =============================================\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m Failed to convert column 'clips' into pyarrow array due to: Error converting data to Arrow: [[('4dd9dc83-4c11-52b2-8123-e981a60d61f4', (0.0, 2.902903))]]; falling back to serialize as pickled python objects\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m Traceback (most recent call last):\u001b[32m [repeated 2x across cluster]\u001b[0m\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 400, in _convert_to_pyarrow_native_array\u001b[32m [repeated 2x across cluster]\u001b[0m\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m return pa.array(column_values, type=pa_type)\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m ~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m File \"pyarrow/array.pxi\", line 375, in pyarrow.lib.array\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m File \"pyarrow/array.pxi\", line 46, in pyarrow.lib._sequence_to_array\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m chunked = GetResultValue(\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m File \"pyarrow/error.pxi\", line 155, in pyarrow.lib.pyarrow_internal_check_status\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m File \"pyarrow/error.pxi\", line 92, in pyarrow.lib.check_status\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m raise convert_status(status)\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m pyarrow.lib.ArrowTypeError: Expected bytes, got a 'tuple' object\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m The above exception was the direct cause of the following exception:\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 299, in convert_to_pyarrow_array\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m return _convert_to_pyarrow_native_array(column_values, column_name)\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m raise ArrowConversionError(str(column_values)) from e\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147834)\u001b[0m ray.data._internal.tensor_extensions.arrow.ArrowConversionError: Error converting data to Arrow: [[('4dd9dc83-4c11-52b2-8123-e981a60d61f4', (0.0, 2.902903))]]\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m Failed to convert column 'clips' into pyarrow array due to: Error converting data to Arrow: [[('e58f0e20-a3ed-5a16-9c78-62c7acdb162f', (0.0, 3.76))]]; falling back to serialize as pickled python objects\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m return pa.array(column_values, type=pa_type)\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m ~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m File \"pyarrow/array.pxi\", line 375, in pyarrow.lib.array\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m File \"pyarrow/array.pxi\", line 46, in pyarrow.lib._sequence_to_array\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m chunked = GetResultValue(\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m File \"pyarrow/error.pxi\", line 155, in pyarrow.lib.pyarrow_internal_check_status\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m File \"pyarrow/error.pxi\", line 92, in pyarrow.lib.check_status\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m raise convert_status(status)\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m pyarrow.lib.ArrowTypeError: Expected bytes, got a 'tuple' object\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m The above exception was the direct cause of the following exception:\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m File \"/opt/venv/lib/python3.13/site-packages/ray/data/_internal/tensor_extensions/arrow.py\", line 299, in convert_to_pyarrow_array\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m return _convert_to_pyarrow_native_array(column_values, column_name)\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m raise ArrowConversionError(str(column_values)) from e\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147830)\u001b[0m ray.data._internal.tensor_extensions.arrow.ArrowConversionError: Error converting data to Arrow: [[('e58f0e20-a3ed-5a16-9c78-62c7acdb162f', (0.0, 3.76))]]\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147839)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147839)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147836)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147836)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147835)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147835)\u001b[0m \n", + "2026-07-06 19:23:05,483\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:23:05,485\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:23:05,487\tINFO logging_progress.py:227 -- Active & requested resources: 55/64 CPU, 1.5GiB/93.1GiB object store\n", + "2026-07-06 19:23:05,488\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:23:05,489\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:23:05,490\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:23:05,490\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:23:05,490\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 60.2KiB object store; 1000 rows output\n", + "2026-07-06 19:23:05,491\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:23:05,491\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 169/1000\n", + "2026-07-06 19:23:05,491\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 830 (60.1KiB); Resources: 1.0 CPU, 1.4GiB object store\n", + "2026-07-06 19:23:05,492\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 5/1000\n", + "2026-07-06 19:23:05,492\tINFO logging_progress.py:233 -- Tasks: 15; Actors: 9; Queued blocks: 149 (1.2GiB); Resources: 54.0 CPU, 21.3MiB object store; [all objects local]\n", + "2026-07-06 19:23:05,492\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:23:05,493\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 5 (7.6MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:23:05,493\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:23:05,493\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:23:05,494\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:23:05,494\tINFO logging_progress.py:192 -- =============================================\n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147832)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147832)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147831)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147831)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147838)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147838)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147833)\u001b[0m \n", + "\u001b[36m(MapWorker(MapBatches(TranscodeActor)) pid=3147833)\u001b[0m \n", + "2026-07-06 19:23:15,585\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:23:15,587\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:23:15,589\tINFO logging_progress.py:227 -- Active & requested resources: 55/64 CPU, 8.2GiB/93.1GiB object store\n", + "2026-07-06 19:23:15,589\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:23:15,590\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:23:15,590\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:23:15,590\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:23:15,591\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 5.6KiB object store; 1000 rows output\n", + "2026-07-06 19:23:15,591\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:23:15,591\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 922/1000\n", + "2026-07-06 19:23:15,591\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 77 (5.6KiB); Resources: 1.0 CPU, 7.9GiB object store\n", + "2026-07-06 19:23:15,592\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 86/1000\n", + "2026-07-06 19:23:15,592\tINFO logging_progress.py:233 -- Tasks: 17; Actors: 9; Queued blocks: 819 (7.8GiB); Resources: 54.0 CPU, 247.8MiB object store; [all objects local]\n", + "2026-07-06 19:23:15,592\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:23:15,592\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 86 (224.3MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:23:15,593\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:23:15,593\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:23:15,593\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:23:15,594\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:23:25,684\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:23:25,686\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:23:25,688\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 8.5GiB/93.1GiB object store\n", + "2026-07-06 19:23:25,689\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:23:25,690\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:23:25,691\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:23:25,691\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:23:25,692\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:23:25,692\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:23:25,692\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:23:25,693\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.1GiB object store\n", + "2026-07-06 19:23:25,693\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 166/1000\n", + "2026-07-06 19:23:25,693\tINFO logging_progress.py:233 -- Tasks: 17; Actors: 9; Queued blocks: 817 (7.9GiB); Resources: 54.0 CPU, 440.5MiB object store; [all objects local]\n", + "2026-07-06 19:23:25,694\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:23:25,695\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 166 (417.9MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:23:25,695\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:23:25,695\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:23:25,696\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:23:25,696\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:23:35,765\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:23:35,768\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:23:35,770\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 7.8GiB/93.1GiB object store\n", + "2026-07-06 19:23:35,771\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:23:35,772\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:23:35,773\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:23:35,774\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:23:35,774\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:23:35,775\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:23:35,776\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:23:35,777\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 7.2GiB object store\n", + "2026-07-06 19:23:35,777\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 243/1000\n", + "2026-07-06 19:23:35,778\tINFO logging_progress.py:233 -- Tasks: 17; Actors: 9; Queued blocks: 740 (7.0GiB); Resources: 54.0 CPU, 641.2MiB object store; [all objects local]\n", + "2026-07-06 19:23:35,778\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:23:35,779\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 243 (618.3MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:23:35,780\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:23:35,780\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:23:35,780\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:23:35,781\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:23:45,780\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:23:45,783\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:23:45,784\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 7.3GiB/93.1GiB object store\n", + "2026-07-06 19:23:45,785\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:23:45,786\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:23:45,787\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:23:45,788\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:23:45,789\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:23:45,790\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:23:45,791\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:23:45,791\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 6.5GiB object store\n", + "2026-07-06 19:23:45,792\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 326/1000\n", + "2026-07-06 19:23:45,792\tINFO logging_progress.py:233 -- Tasks: 17; Actors: 9; Queued blocks: 657 (6.2GiB); Resources: 54.0 CPU, 803.8MiB object store; [all objects local]\n", + "2026-07-06 19:23:45,792\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:23:45,793\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 326 (782.2MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:23:45,793\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:23:45,793\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:23:45,794\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:23:45,794\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:23:55,854\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:23:55,856\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:23:55,858\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 6.6GiB/93.1GiB object store\n", + "2026-07-06 19:23:55,859\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:23:55,860\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:23:55,861\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:23:55,861\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:23:55,861\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:23:55,862\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:23:55,863\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:23:55,863\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 5.6GiB object store\n", + "2026-07-06 19:23:55,863\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 411/1000\n", + "2026-07-06 19:23:55,864\tINFO logging_progress.py:233 -- Tasks: 16; Actors: 9; Queued blocks: 573 (5.5GiB); Resources: 54.0 CPU, 1014.8MiB object store; [all objects local]\n", + "2026-07-06 19:23:55,864\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:23:55,864\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 411 (993.0MiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:23:55,865\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:23:55,865\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:23:55,866\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:23:55,866\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:24:05,859\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:24:05,860\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:24:05,861\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 6.2GiB/93.1GiB object store\n", + "2026-07-06 19:24:05,861\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:24:05,862\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:24:05,863\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:24:05,863\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:24:05,863\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:24:05,864\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:24:05,864\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:24:05,864\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 5.0GiB object store\n", + "2026-07-06 19:24:05,864\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 500/1000\n", + "2026-07-06 19:24:05,865\tINFO logging_progress.py:233 -- Tasks: 18; Actors: 9; Queued blocks: 482 (4.7GiB); Resources: 54.0 CPU, 1.2GiB object store; [all objects local]\n", + "2026-07-06 19:24:05,865\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:24:05,866\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 500 (1.1GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:24:05,866\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:24:05,867\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:24:05,867\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:24:05,867\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:24:15,902\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:24:15,903\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:24:15,904\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 5.6GiB/93.1GiB object store\n", + "2026-07-06 19:24:15,905\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:24:15,905\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:24:15,906\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:24:15,906\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:24:15,907\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:24:15,907\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:24:15,908\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:24:15,908\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 4.2GiB object store\n", + "2026-07-06 19:24:15,909\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 577/1000\n", + "2026-07-06 19:24:15,909\tINFO logging_progress.py:233 -- Tasks: 18; Actors: 9; Queued blocks: 405 (4.1GiB); Resources: 54.0 CPU, 1.3GiB object store; [all objects local]\n", + "2026-07-06 19:24:15,910\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:24:15,911\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 577 (1.3GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:24:15,911\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:24:15,912\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:24:15,913\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:24:15,913\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:24:25,905\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:24:25,907\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:24:25,909\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 4.9GiB/93.1GiB object store\n", + "2026-07-06 19:24:25,910\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:24:25,911\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:24:25,912\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:24:25,912\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:24:25,913\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:24:25,914\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:24:25,914\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:24:25,915\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 3.4GiB object store\n", + "2026-07-06 19:24:25,916\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 655/1000\n", + "2026-07-06 19:24:25,916\tINFO logging_progress.py:233 -- Tasks: 18; Actors: 9; Queued blocks: 327 (3.1GiB); Resources: 54.0 CPU, 1.5GiB object store; [all objects local]\n", + "2026-07-06 19:24:25,917\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:24:25,919\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 655 (1.5GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:24:25,920\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:24:25,920\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:24:25,920\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:24:25,921\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:24:36,014\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:24:36,016\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:24:36,017\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 4.3GiB/93.1GiB object store\n", + "2026-07-06 19:24:36,018\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:24:36,019\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:24:36,020\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:24:36,021\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:24:36,021\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:24:36,022\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:24:36,023\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:24:36,023\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 2.5GiB object store\n", + "2026-07-06 19:24:36,024\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 735/1000\n", + "2026-07-06 19:24:36,025\tINFO logging_progress.py:233 -- Tasks: 17; Actors: 9; Queued blocks: 248 (2.3GiB); Resources: 54.0 CPU, 1.7GiB object store; [all objects local]\n", + "2026-07-06 19:24:36,026\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:24:36,026\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 735 (1.7GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:24:36,027\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:24:36,028\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:24:36,028\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:24:36,029\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:24:46,121\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:24:46,123\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:24:46,125\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 3.7GiB/93.1GiB object store\n", + "2026-07-06 19:24:46,126\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:24:46,127\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:24:46,128\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:24:46,128\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:24:46,130\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:24:46,131\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:24:46,131\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:24:46,131\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 1.8GiB object store\n", + "2026-07-06 19:24:46,132\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 823/1000\n", + "2026-07-06 19:24:46,132\tINFO logging_progress.py:233 -- Tasks: 17; Actors: 9; Queued blocks: 160 (1.4GiB); Resources: 54.0 CPU, 1.9GiB object store; [all objects local]\n", + "2026-07-06 19:24:46,132\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:24:46,132\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 823 (1.9GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:24:46,133\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:24:46,133\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:24:46,133\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:24:46,134\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:24:56,221\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:24:56,222\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:24:56,222\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 3.0GiB/93.1GiB object store\n", + "2026-07-06 19:24:56,223\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:24:56,224\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:24:56,225\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:24:56,225\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:24:56,225\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:24:56,226\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:24:56,226\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:24:56,226\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 958.7MiB object store\n", + "2026-07-06 19:24:56,226\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 905/1000\n", + "2026-07-06 19:24:56,227\tINFO logging_progress.py:233 -- Tasks: 17; Actors: 9; Queued blocks: 78 (801.3MiB); Resources: 54.0 CPU, 2.1GiB object store; [all objects local]\n", + "2026-07-06 19:24:56,227\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:24:56,227\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 905 (2.1GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:24:56,227\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:24:56,228\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:24:56,228\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:24:56,228\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:25:06,333\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:25:06,334\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:25:06,335\tINFO logging_progress.py:227 -- Active & requested resources: 54/64 CPU, 2.5GiB/93.1GiB object store\n", + "2026-07-06 19:25:06,335\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:25:06,336\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:25:06,336\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:25:06,337\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:25:06,337\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:25:06,337\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:25:06,337\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:25:06,338\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 199.3MiB object store\n", + "2026-07-06 19:25:06,338\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 991/1000\n", + "2026-07-06 19:25:06,338\tINFO logging_progress.py:233 -- Tasks: 9; Actors: 9; Queued blocks: 0 (0.0B); Resources: 54.0 CPU, 2.3GiB object store; [all objects local]\n", + "2026-07-06 19:25:06,338\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:25:06,339\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 991 (2.2GiB); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:25:06,340\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n", + "2026-07-06 19:25:06,340\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:25:06,340\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:25:06,340\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:25:19,206\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:25:19,208\tINFO logging_progress.py:225 -- Total Progress: 0/?\n", + "2026-07-06 19:25:19,209\tINFO logging_progress.py:227 -- Active & requested resources: 6/64 CPU, 2.3GiB/93.1GiB object store\n", + "2026-07-06 19:25:19,209\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:25:19,210\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:25:19,211\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:25:19,211\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:25:19,213\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:25:19,214\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:25:19,215\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:25:19,216\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:25:19,217\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:25:19,217\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 6.0 CPU, 2.3GiB object store; [all objects local]\n", + "2026-07-06 19:25:19,218\tINFO logging_progress.py:231 -- Repartition: 0/1000\n", + "2026-07-06 19:25:19,218\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:25:19,218\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:25:19,218\tINFO logging_progress.py:231 -- MapBatches(write_clips): 0/1\n", + "2026-07-06 19:25:19,219\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:25:19,219\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:25:29,207\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:25:29,209\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n", + "2026-07-06 19:25:29,209\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n", + "2026-07-06 19:25:29,210\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:25:29,210\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:25:29,210\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:25:29,211\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:25:29,211\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:25:29,211\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:25:29,212\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:25:29,212\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:25:29,212\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:25:29,213\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:25:29,213\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:25:29,213\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n", + "2026-07-06 19:25:29,214\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:25:29,214\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n", + "2026-07-06 19:25:29,214\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n", + "2026-07-06 19:25:29,215\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:25:39,210\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:25:39,214\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n", + "2026-07-06 19:25:39,216\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n", + "2026-07-06 19:25:39,218\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:25:39,219\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:25:39,219\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:25:39,220\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:25:39,220\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:25:39,220\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:25:39,221\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:25:39,221\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:25:39,222\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:25:39,223\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:25:39,223\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:25:39,224\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n", + "2026-07-06 19:25:39,224\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:25:39,224\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n", + "2026-07-06 19:25:39,225\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n", + "2026-07-06 19:25:39,225\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:25:49,211\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:25:49,213\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n", + "2026-07-06 19:25:49,215\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n", + "2026-07-06 19:25:49,216\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:25:49,216\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:25:49,217\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:25:49,218\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:25:49,219\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:25:49,220\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:25:49,220\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:25:49,221\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:25:49,221\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:25:49,221\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:25:49,222\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:25:49,222\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n", + "2026-07-06 19:25:49,223\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:25:49,223\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n", + "2026-07-06 19:25:49,223\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n", + "2026-07-06 19:25:49,224\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:25:59,211\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:25:59,213\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n", + "2026-07-06 19:25:59,214\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n", + "2026-07-06 19:25:59,214\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:25:59,215\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:25:59,216\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:25:59,217\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:25:59,217\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:25:59,218\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:25:59,218\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:25:59,219\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:25:59,220\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:25:59,220\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:25:59,221\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:25:59,222\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n", + "2026-07-06 19:25:59,222\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:25:59,223\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n", + "2026-07-06 19:25:59,224\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n", + "2026-07-06 19:25:59,225\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:26:09,217\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:26:09,220\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n", + "2026-07-06 19:26:09,222\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n", + "2026-07-06 19:26:09,224\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:26:09,224\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:26:09,225\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:26:09,225\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:26:09,226\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:26:09,227\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:26:09,227\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:26:09,228\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:26:09,229\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:26:09,229\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:26:09,230\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:26:09,231\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n", + "2026-07-06 19:26:09,232\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:26:09,233\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n", + "2026-07-06 19:26:09,235\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n", + "2026-07-06 19:26:09,236\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:26:19,225\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:26:19,229\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n", + "2026-07-06 19:26:19,231\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n", + "2026-07-06 19:26:19,233\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:26:19,233\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:26:19,234\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:26:19,235\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:26:19,235\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:26:19,236\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:26:19,236\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:26:19,237\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:26:19,237\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:26:19,238\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:26:19,238\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:26:19,238\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n", + "2026-07-06 19:26:19,241\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:26:19,241\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n", + "2026-07-06 19:26:19,242\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n", + "2026-07-06 19:26:19,242\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:26:29,227\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:26:29,229\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n", + "2026-07-06 19:26:29,230\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n", + "2026-07-06 19:26:29,231\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:26:29,233\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:26:29,234\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:26:29,235\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:26:29,236\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:26:29,236\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:26:29,238\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:26:29,239\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:26:29,239\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:26:29,240\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:26:29,241\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:26:29,242\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n", + "2026-07-06 19:26:29,243\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:26:29,243\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n", + "2026-07-06 19:26:29,243\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n", + "2026-07-06 19:26:29,243\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:26:39,234\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:26:39,237\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n", + "2026-07-06 19:26:39,239\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n", + "2026-07-06 19:26:39,240\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:26:39,241\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:26:39,241\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:26:39,242\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:26:39,242\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:26:39,243\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:26:39,243\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:26:39,244\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:26:39,244\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:26:39,245\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:26:39,245\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:26:39,246\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n", + "2026-07-06 19:26:39,246\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:26:39,246\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n", + "2026-07-06 19:26:39,247\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n", + "2026-07-06 19:26:39,247\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:26:49,240\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:26:49,243\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n", + "2026-07-06 19:26:49,245\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n", + "2026-07-06 19:26:49,245\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:26:49,246\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:26:49,246\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:26:49,247\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:26:49,248\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:26:49,248\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:26:49,250\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:26:49,251\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:26:49,254\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:26:49,255\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:26:49,257\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:26:49,257\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n", + "2026-07-06 19:26:49,258\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:26:49,259\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n", + "2026-07-06 19:26:49,260\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n", + "2026-07-06 19:26:49,260\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:26:59,246\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:26:59,248\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n", + "2026-07-06 19:26:59,250\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n", + "2026-07-06 19:26:59,252\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:26:59,252\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:26:59,253\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:26:59,253\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:26:59,254\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:26:59,255\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:26:59,255\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:26:59,255\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:26:59,256\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:26:59,256\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:26:59,257\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:26:59,258\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n", + "2026-07-06 19:26:59,258\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:26:59,259\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n", + "2026-07-06 19:26:59,259\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n", + "2026-07-06 19:26:59,260\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:27:09,250\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:27:09,252\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n", + "2026-07-06 19:27:09,253\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n", + "2026-07-06 19:27:09,254\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:27:09,255\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:27:09,255\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:27:09,256\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:27:09,258\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:27:09,258\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:27:09,259\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:27:09,260\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:27:09,262\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:27:09,262\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:27:09,263\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:27:09,263\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n", + "2026-07-06 19:27:09,264\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:27:09,265\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n", + "2026-07-06 19:27:09,266\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n", + "2026-07-06 19:27:09,267\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:27:19,264\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:27:19,266\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n", + "2026-07-06 19:27:19,267\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n", + "2026-07-06 19:27:19,268\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:27:19,271\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:27:19,273\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:27:19,276\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:27:19,278\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:27:19,280\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:27:19,281\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:27:19,282\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:27:19,283\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:27:19,284\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:27:19,285\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:27:19,285\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n", + "2026-07-06 19:27:19,286\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:27:19,286\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n", + "2026-07-06 19:27:19,287\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n", + "2026-07-06 19:27:19,287\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:27:29,273\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:27:29,275\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n", + "2026-07-06 19:27:29,276\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n", + "2026-07-06 19:27:29,277\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:27:29,279\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:27:29,280\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:27:29,280\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:27:29,281\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:27:29,281\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:27:29,281\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:27:29,282\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:27:29,282\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:27:29,282\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:27:29,283\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:27:29,283\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n", + "2026-07-06 19:27:29,283\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:27:29,284\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n", + "2026-07-06 19:27:29,284\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n", + "2026-07-06 19:27:29,284\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:27:39,280\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:27:39,282\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n", + "2026-07-06 19:27:39,283\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n", + "2026-07-06 19:27:39,287\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:27:39,288\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:27:39,289\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:27:39,290\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:27:39,291\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:27:39,291\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:27:39,292\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:27:39,293\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:27:39,293\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:27:39,295\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:27:39,296\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:27:39,296\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n", + "2026-07-06 19:27:39,298\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:27:39,298\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n", + "2026-07-06 19:27:39,299\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n", + "2026-07-06 19:27:39,299\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:27:49,289\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:27:49,291\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n", + "2026-07-06 19:27:49,294\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n", + "2026-07-06 19:27:49,295\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:27:49,297\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:27:49,298\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:27:49,299\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:27:49,299\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:27:49,300\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:27:49,300\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:27:49,301\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:27:49,301\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:27:49,301\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:27:49,302\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:27:49,303\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n", + "2026-07-06 19:27:49,303\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:27:49,303\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n", + "2026-07-06 19:27:49,304\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n", + "2026-07-06 19:27:49,304\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:27:59,290\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:27:59,293\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n", + "2026-07-06 19:27:59,295\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n", + "2026-07-06 19:27:59,298\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:27:59,299\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:27:59,301\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:27:59,302\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:27:59,303\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:27:59,304\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:27:59,305\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:27:59,306\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:27:59,308\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:27:59,308\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:27:59,309\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:27:59,309\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n", + "2026-07-06 19:27:59,309\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:27:59,310\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n", + "2026-07-06 19:27:59,310\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n", + "2026-07-06 19:27:59,310\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:28:09,291\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_15_0 =======\n", + "2026-07-06 19:28:09,293\tINFO logging_progress.py:225 -- Total Progress: 870/20000\n", + "2026-07-06 19:28:09,294\tINFO logging_progress.py:227 -- Active & requested resources: 20.25/64 CPU, 319.1MiB/93.1GiB object store\n", + "2026-07-06 19:28:09,295\tINFO logging_progress.py:181 -- \n", + "2026-07-06 19:28:09,296\tINFO logging_progress.py:231 -- MapBatches(ls_videos): 1000/1000\n", + "2026-07-06 19:28:09,296\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:28:09,297\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:28:09,298\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 1000 rows output\n", + "2026-07-06 19:28:09,298\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:28:09,299\tINFO logging_progress.py:231 -- MapBatches(read_and_probe)->MapBatches(split_fixed_stride): 1000/1000\n", + "2026-07-06 19:28:09,300\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n", + "2026-07-06 19:28:09,300\tINFO logging_progress.py:231 -- MapBatches(TranscodeActor): 1000/1000\n", + "2026-07-06 19:28:09,301\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n", + "2026-07-06 19:28:09,302\tINFO logging_progress.py:231 -- Repartition: 1000/1000\n", + "2026-07-06 19:28:09,302\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 319.1MiB object store; 1000 rows output\n", + "2026-07-06 19:28:09,303\tINFO logging_progress.py:231 -- - Split Repartition: 1000/1\n", + "2026-07-06 19:28:09,303\tINFO logging_progress.py:231 -- MapBatches(write_clips): 870/20000\n", + "2026-07-06 19:28:09,304\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 0; Queued blocks: 19000 (0.0B); Resources: 32.5 CPU, 17.1KiB object store\n", + "2026-07-06 19:28:09,304\tINFO logging_progress.py:192 -- =============================================\n", + "2026-07-06 19:28:17,072\tINFO streaming_executor.py:294 -- ✔️ Dataset dataset_15_0 execution finished in 331.89 seconds\n" + ] }, { "name": "stdout", "output_type": "stream", - "text": "[ActorPool(min=N, max=N)] 1000 videos, 1000 clip-chunks, 332.0s \u2014 3.01 vid/s\n" + "text": [ + "[ActorPool(min=N, max=N)] 1000 videos, 1000 clip-chunks, 332.0s — 3.01 vid/s\n" + ] } ], - "source": "# \u2500\u2500 Pipeline Runs \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\nimport threading\nfrom ray.data import ActorPoolStrategy, TaskPoolStrategy\n\nray.shutdown()\nray.init(num_cpus=64) # 64-CPU machine\n\ntotal_cpus = int(ray.cluster_resources().get(\"CPU\", 0))\nmax_transcode = MAX_TRANSCODE_OVERRIDE\nprint(f\"Total CPUs: {total_cpus}, max transcode workers: {max_transcode}\")\nprint(f\"CPU pressure: {max_transcode * TRANSCODE_CPUS:.0f}/{total_cpus} = \"\n f\"{max_transcode * TRANSCODE_CPUS / total_cpus * 100:.0f}%\")\n\nclass TranscodeActor:\n def __call__(self, batch):\n return transcode(batch)\n\ndef _monitor_actors(snapshots, stop_event, interval=1.0):\n # Track active TranscodeActor count via CPU utilization.\n total_cpu = ray.cluster_resources().get(\"CPU\", 64)\n t0 = time.perf_counter()\n while not stop_event.is_set():\n try:\n avail = ray.available_resources().get(\"CPU\", total_cpu)\n busy = max(0.0, total_cpu - avail)\n actor_est = int(round(busy / TRANSCODE_CPUS))\n ts = time.perf_counter() - t0\n snapshots.append((ts, busy, actor_est))\n except Exception:\n pass\n stop_event.wait(interval)\n\ndef run_pipeline(transcode_compute, label):\n shutil.rmtree(OUTPUT_DIR, ignore_errors=True)\n\n snapshots = []\n stop_event = threading.Event()\n monitor_thread = threading.Thread(\n target=_monitor_actors, args=(snapshots, stop_event), daemon=True\n )\n\n t0 = time.perf_counter()\n ds = (\n ray.data.from_items([{\"seed\": None}])\n .map_batches(ls_videos, batch_size=1) # single task\n .repartition(VIDEO_LIMIT)\n .map_batches(read_and_probe, batch_size=1, num_cpus=1)\n .map_batches(split_fixed_stride, batch_size=1, num_cpus=1)\n .map_batches(TranscodeActor, batch_size=1, num_cpus=TRANSCODE_CPUS,\n compute=transcode_compute)\n .repartition(VIDEO_LIMIT * 20)\n .map_batches(write_clips, batch_size=1, num_cpus=WRITE_CPUS)\n )\n monitor_thread.start()\n results = ds.take_all()\n stop_event.set()\n monitor_thread.join(timeout=3)\n elapsed = time.perf_counter() - t0\n\n n_chunks = len(results)\n n_videos = len(set(r[\"path\"] for r in results))\n print(f\"[{label}] {n_videos} videos, {n_chunks} clip-chunks, \"\n f\"{elapsed:.1f}s \u2014 {n_videos/elapsed:.2f} vid/s\")\n return elapsed, snapshots\n\nelapsed1, snaps1 = run_pipeline(\n ActorPoolStrategy(min_size=1, max_size=max_transcode, initial_size=max_transcode),\n label=\"ActorPool(min=1, max=N, initial=N)\"\n)\n\nelapsed2, snaps2 = run_pipeline(\n ActorPoolStrategy(min_size=max_transcode, max_size=max_transcode),\n label=\"ActorPool(min=N, max=N)\"\n)" + "source": [ + "# ── Pipeline Runs ────────────────────────────────────────────────────────────\n", + "from ray.data import ActorPoolStrategy\n", + "\n", + "ray.shutdown()\n", + "ray.init(num_cpus=64) # 64-CPU machine\n", + "\n", + "total_cpus = int(ray.cluster_resources().get(\"CPU\", 0))\n", + "max_transcode = MAX_TRANSCODE_OVERRIDE\n", + "print(f\"Total CPUs: {total_cpus}, max transcode workers: {max_transcode}\")\n", + "print(\n", + " f\"CPU pressure: {max_transcode * TRANSCODE_CPUS:.0f}/{total_cpus} = \"\n", + " f\"{max_transcode * TRANSCODE_CPUS / total_cpus * 100:.0f}%\"\n", + ")\n", + "\n", + "\n", + "class TranscodeActor:\n", + " def __call__(self, batch):\n", + " return transcode(batch)\n", + "\n", + "\n", + "def _monitor_actors(snapshots, stop_event, interval=1.0):\n", + " # Track active TranscodeActor count via CPU utilization.\n", + " total_cpu = ray.cluster_resources().get(\"CPU\", 64)\n", + " t0 = time.perf_counter()\n", + " while not stop_event.is_set():\n", + " try:\n", + " avail = ray.available_resources().get(\"CPU\", total_cpu)\n", + " busy = max(0.0, total_cpu - avail)\n", + " actor_est = int(round(busy / TRANSCODE_CPUS))\n", + " ts = time.perf_counter() - t0\n", + " snapshots.append((ts, busy, actor_est))\n", + " except Exception:\n", + " pass\n", + " stop_event.wait(interval)\n", + "\n", + "\n", + "def run_pipeline(transcode_compute, label):\n", + " shutil.rmtree(OUTPUT_DIR, ignore_errors=True)\n", + "\n", + " snapshots = []\n", + " stop_event = threading.Event()\n", + " monitor_thread = threading.Thread(target=_monitor_actors, args=(snapshots, stop_event), daemon=True)\n", + "\n", + " t0 = time.perf_counter()\n", + " ds = (\n", + " ray.data.from_items([{\"seed\": None}])\n", + " .map_batches(ls_videos, batch_size=1) # single task\n", + " .repartition(VIDEO_LIMIT)\n", + " .map_batches(read_and_probe, batch_size=1, num_cpus=1)\n", + " .map_batches(split_fixed_stride, batch_size=1, num_cpus=1)\n", + " .map_batches(TranscodeActor, batch_size=1, num_cpus=TRANSCODE_CPUS, compute=transcode_compute)\n", + " .repartition(VIDEO_LIMIT * 20)\n", + " .map_batches(write_clips, batch_size=1, num_cpus=WRITE_CPUS)\n", + " )\n", + " monitor_thread.start()\n", + " results = ds.take_all()\n", + " stop_event.set()\n", + " monitor_thread.join(timeout=3)\n", + " elapsed = time.perf_counter() - t0\n", + "\n", + " n_chunks = len(results)\n", + " n_videos = len(set(r[\"path\"] for r in results))\n", + " print(f\"[{label}] {n_videos} videos, {n_chunks} clip-chunks, {elapsed:.1f}s — {n_videos / elapsed:.2f} vid/s\")\n", + " return elapsed, snapshots\n", + "\n", + "\n", + "elapsed1, snaps1 = run_pipeline(\n", + " ActorPoolStrategy(min_size=1, max_size=max_transcode, initial_size=max_transcode),\n", + " label=\"ActorPool(min=1, max=N, initial=N)\",\n", + ")\n", + "\n", + "elapsed2, snaps2 = run_pipeline(\n", + " ActorPoolStrategy(min_size=max_transcode, max_size=max_transcode), label=\"ActorPool(min=N, max=N)\"\n", + ")" + ] }, { "cell_type": "code", @@ -78,10 +1921,767 @@ { "name": "stdout", "output_type": "stream", - "text": "\n=== Run 1: ActorPool(min=1, max=N, initial=N) ===\n 0.0s actors~ 0 cpu_busy= 0 \n 1.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 2.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 3.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 4.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 5.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 6.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 7.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 8.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 9.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 10.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 11.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 12.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 13.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 14.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 15.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 16.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 17.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 18.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 19.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 20.1s actors~ 0 cpu_busy= 0 \n 21.1s actors~ 9 cpu_busy= 52 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 22.1s actors~ 8 cpu_busy= 46 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 23.1s actors~ 7 cpu_busy= 43 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 24.1s actors~ 6 cpu_busy= 38 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 25.1s actors~ 6 cpu_busy= 39 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 26.1s actors~ 6 cpu_busy= 37 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 27.1s actors~ 6 cpu_busy= 36 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 28.1s actors~ 8 cpu_busy= 47 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 29.1s actors~ 8 cpu_busy= 51 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 30.1s actors~ 8 cpu_busy= 48 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 31.1s actors~ 6 cpu_busy= 37 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 32.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 33.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 34.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 35.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 36.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 37.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 38.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 39.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 40.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 41.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 42.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 43.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 44.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 45.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 46.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 47.1s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 48.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 49.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 50.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 51.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 52.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 53.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 54.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 55.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 56.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 57.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 58.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 59.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 60.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 61.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 62.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 63.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 64.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 65.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 66.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 67.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 68.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 69.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 70.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 71.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 72.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 73.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 74.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 75.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 76.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 77.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 78.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 79.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 80.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 81.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 82.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 83.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 84.2s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 85.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 86.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 87.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 88.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 89.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 90.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 91.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 92.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 93.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 94.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 95.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 96.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 97.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 98.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 99.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 100.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 101.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 102.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 103.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 104.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 105.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 106.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 107.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 108.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 109.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 110.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 111.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 112.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 113.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 114.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 115.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 116.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 117.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 118.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 119.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 120.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 121.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 122.3s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 123.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 124.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 125.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 126.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 127.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 128.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 129.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 130.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 131.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 132.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 133.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 134.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 135.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 136.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 137.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 138.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 139.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 140.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 141.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 142.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 143.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 144.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 145.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 146.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 147.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 148.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 149.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 150.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 151.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 152.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 153.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 154.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 155.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 156.4s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 157.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 158.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 159.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 160.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 161.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 162.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 163.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 164.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 165.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 166.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 167.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 168.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 169.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 170.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 171.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 172.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 173.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 174.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 175.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 176.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 177.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 178.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 179.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 180.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 181.5s actors~ 7 cpu_busy= 42 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 182.5s actors~ 4 cpu_busy= 24 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 183.5s actors~ 2 cpu_busy= 12 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 184.5s actors~ 1 cpu_busy= 6 \u2588\u2588\u2588\u2588\u2588\u2588\n 185.8s actors~ 2 cpu_busy= 13 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 186.9s actors~ 0 cpu_busy= 0 \n 187.9s actors~ 0 cpu_busy= 0 \n 188.9s actors~ 0 cpu_busy= 0 \n 189.9s actors~ 0 cpu_busy= 0 \n 190.9s actors~ 0 cpu_busy= 0 \n 191.9s actors~ 0 cpu_busy= 0 \n 192.9s actors~10 cpu_busy= 62 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 193.9s actors~10 cpu_busy= 58 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 194.9s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 195.9s actors~ 9 cpu_busy= 56 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 196.9s actors~ 8 cpu_busy= 47 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 197.9s actors~ 7 cpu_busy= 41 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 198.9s actors~ 6 cpu_busy= 37 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 199.9s actors~ 4 cpu_busy= 26 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 200.9s actors~ 4 cpu_busy= 22 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 202.0s actors~ 3 cpu_busy= 20 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 203.0s actors~ 1 cpu_busy= 6 \u2588\u2588\u2588\u2588\u2588\u2588\n 204.0s actors~ 0 cpu_busy= 0 \n 205.0s actors~ 0 cpu_busy= 0 \n 206.0s actors~ 0 cpu_busy= 0 \n 207.0s actors~ 0 cpu_busy= 0 \n 208.0s actors~ 0 cpu_busy= 0 \n 209.1s actors~ 0 cpu_busy= 0 \n 210.1s actors~ 0 cpu_busy= 0 \n 211.1s actors~ 0 cpu_busy= 0 \n 212.1s actors~ 0 cpu_busy= 0 \n 213.1s actors~ 0 cpu_busy= 0 \n 214.2s actors~ 0 cpu_busy= 0 \n 215.2s actors~ 0 cpu_busy= 0 \n 216.2s actors~ 0 cpu_busy= 0 \n 217.2s actors~ 0 cpu_busy= 0 \n 218.2s actors~ 0 cpu_busy= 0 \n 219.2s actors~ 0 cpu_busy= 0 \n 220.2s actors~ 0 cpu_busy= 0 \n 221.2s actors~ 0 cpu_busy= 0 \n 222.2s actors~ 0 cpu_busy= 0 \n 223.3s actors~ 0 cpu_busy= 0 \n 224.3s actors~ 0 cpu_busy= 0 \n 225.3s actors~ 0 cpu_busy= 0 \n 226.3s actors~ 0 cpu_busy= 0 \n 227.3s actors~ 0 cpu_busy= 0 \n 228.3s actors~ 0 cpu_busy= 0 \n 229.4s actors~ 0 cpu_busy= 0 \n 230.4s actors~ 0 cpu_busy= 0 \n 231.4s actors~ 0 cpu_busy= 0 \n 232.4s actors~ 0 cpu_busy= 0 \n 233.4s actors~ 0 cpu_busy= 0 \n 234.4s actors~ 0 cpu_busy= 0 \n 235.4s actors~ 0 cpu_busy= 0 \n 236.4s actors~ 0 cpu_busy= 0 \n 237.5s actors~ 0 cpu_busy= 0 \n 238.5s actors~ 0 cpu_busy= 0 \n 239.5s actors~ 0 cpu_busy= 0 \n 240.5s actors~ 0 cpu_busy= 0 \n 241.5s actors~ 0 cpu_busy= 0 \n 242.5s actors~ 0 cpu_busy= 0 \n 243.5s actors~ 0 cpu_busy= 0 \n 244.5s actors~ 0 cpu_busy= 0 \n 245.5s actors~ 0 cpu_busy= 0 \n 246.5s actors~ 0 cpu_busy= 0 \n 247.5s actors~ 0 cpu_busy= 0 \n 248.5s actors~ 0 cpu_busy= 0 \n 249.6s actors~ 0 cpu_busy= 0 \n 250.6s actors~ 0 cpu_busy= 0 \n 251.6s actors~ 0 cpu_busy= 0 \n 252.6s actors~ 0 cpu_busy= 0 \n 253.6s actors~ 0 cpu_busy= 0 \n 254.6s actors~ 0 cpu_busy= 0 \n 255.6s actors~ 0 cpu_busy= 0 \n 256.6s actors~ 0 cpu_busy= 0 \n 257.7s actors~ 0 cpu_busy= 0 \n 258.7s actors~ 0 cpu_busy= 0 \n 259.7s actors~ 0 cpu_busy= 0 \n 260.7s actors~ 0 cpu_busy= 0 \n 261.7s actors~ 0 cpu_busy= 0 \n 262.7s actors~ 0 cpu_busy= 0 \n 263.7s actors~ 0 cpu_busy= 0 \n 264.8s actors~ 0 cpu_busy= 0 \n 265.8s actors~ 0 cpu_busy= 0 \n 266.8s actors~ 0 cpu_busy= 0 \n 267.8s actors~ 0 cpu_busy= 0 \n 268.9s actors~ 0 cpu_busy= 0 \n 269.9s actors~ 0 cpu_busy= 0 \n 270.9s actors~ 0 cpu_busy= 0 \n 271.9s actors~ 0 cpu_busy= 0 \n 272.9s actors~ 0 cpu_busy= 0 \n 273.9s actors~ 0 cpu_busy= 0 \n 274.9s actors~ 0 cpu_busy= 0 \n 276.0s actors~ 0 cpu_busy= 0 \n 277.0s actors~ 0 cpu_busy= 0 \n 278.0s actors~ 0 cpu_busy= 0 \n 279.0s actors~ 0 cpu_busy= 0 \n 280.0s actors~ 0 cpu_busy= 0 \n 281.0s actors~ 0 cpu_busy= 0 \n 282.0s actors~ 0 cpu_busy= 0 \n 283.1s actors~ 0 cpu_busy= 0 \n 284.1s actors~ 0 cpu_busy= 0 \n 285.1s actors~ 0 cpu_busy= 0 \n 286.1s actors~ 0 cpu_busy= 0 \n 287.1s actors~ 0 cpu_busy= 0 \n 288.1s actors~ 0 cpu_busy= 0 \n 289.1s actors~ 0 cpu_busy= 0 \n 290.2s actors~ 0 cpu_busy= 0 \n 291.2s actors~ 0 cpu_busy= 0 \n 292.2s actors~ 0 cpu_busy= 0 \n 293.2s actors~ 0 cpu_busy= 0 \n 294.2s actors~ 0 cpu_busy= 0 \n 295.2s actors~ 0 cpu_busy= 0 \n 296.2s actors~ 0 cpu_busy= 0 \n 297.2s actors~ 0 cpu_busy= 0 \n 298.2s actors~ 0 cpu_busy= 0 \n 299.2s actors~ 0 cpu_busy= 0 \n 300.2s actors~ 0 cpu_busy= 0 \n 301.3s actors~ 0 cpu_busy= 0 \n 302.3s actors~ 0 cpu_busy= 0 \n 303.3s actors~ 0 cpu_busy= 0 \n 304.3s actors~ 0 cpu_busy= 0 \n 305.3s actors~ 0 cpu_busy= 0 \n 306.3s actors~ 0 cpu_busy= 0 \n 307.4s actors~ 0 cpu_busy= 0 \n 308.4s actors~ 0 cpu_busy= 0 \n 309.4s actors~ 0 cpu_busy= 0 \n 310.5s actors~ 0 cpu_busy= 0 \n 311.5s actors~ 0 cpu_busy= 0 \n 312.5s actors~ 0 cpu_busy= 0 \n 313.5s actors~ 0 cpu_busy= 0 \n 314.5s actors~ 0 cpu_busy= 0 \n 315.5s actors~ 0 cpu_busy= 0 \n 316.5s actors~ 0 cpu_busy= 0 \n 317.6s actors~ 0 cpu_busy= 0 \n 318.6s actors~ 0 cpu_busy= 0 \n 319.6s actors~ 0 cpu_busy= 0 \n 320.6s actors~ 0 cpu_busy= 0 \n 321.6s actors~ 0 cpu_busy= 0 \n 322.7s actors~ 0 cpu_busy= 0 \n 323.7s actors~ 0 cpu_busy= 0 \n 324.7s actors~ 0 cpu_busy= 0 \n 325.7s actors~ 0 cpu_busy= 0 \n 326.7s actors~ 0 cpu_busy= 0 \n 327.8s actors~ 0 cpu_busy= 0 \n 328.8s actors~ 0 cpu_busy= 0 \n 329.8s actors~ 0 cpu_busy= 0 \n 330.8s actors~ 0 cpu_busy= 0 \n 331.8s actors~ 0 cpu_busy= 0 \n 332.8s actors~ 0 cpu_busy= 0 \n 333.9s actors~ 0 cpu_busy= 0 \n 334.9s actors~ 0 cpu_busy= 0 \n 335.9s actors~ 0 cpu_busy= 0 \n 336.9s actors~ 0 cpu_busy= 0 \n 337.9s actors~ 0 cpu_busy= 0 \n 339.0s actors~ 0 cpu_busy= 0 \n 340.0s actors~ 0 cpu_busy= 0 \n 341.0s actors~ 0 cpu_busy= 0 \n 342.0s actors~ 0 cpu_busy= 0 \n 343.0s actors~ 0 cpu_busy= 0 \n 344.1s actors~ 0 cpu_busy= 0 \n 345.1s actors~ 0 cpu_busy= 0 \n 346.1s actors~ 0 cpu_busy= 0 \n 347.1s actors~ 0 cpu_busy= 0 \n 348.1s actors~ 0 cpu_busy= 0 \n 349.1s actors~ 0 cpu_busy= 0 \n 350.1s actors~ 0 cpu_busy= 0 \n 351.1s actors~ 0 cpu_busy= 0 \n 352.2s actors~ 0 cpu_busy= 0 \n 353.2s actors~ 0 cpu_busy= 0 \n 354.2s actors~ 0 cpu_busy= 0 \n 355.2s actors~ 0 cpu_busy= 0 \n 356.2s actors~ 0 cpu_busy= 0 \n 357.2s actors~ 0 cpu_busy= 0 \n 358.2s actors~ 0 cpu_busy= 0 \n 359.2s actors~ 0 cpu_busy= 0 \n peak=10 avg=3.9 zero-actor-samples=162/357\n\n=== Run 2: ActorPool(min=N, max=N) ===\n 0.0s actors~ 0 cpu_busy= 0 \n 1.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 2.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 3.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 4.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 5.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 6.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 7.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 8.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 9.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 10.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 11.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 12.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 13.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 14.0s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 15.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 16.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 17.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 18.1s actors~ 0 cpu_busy= 0 \n 19.1s actors~10 cpu_busy= 57 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 20.1s actors~ 0 cpu_busy= 0 \n 21.1s actors~10 cpu_busy= 57 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 22.1s actors~ 0 cpu_busy= 0 \n 23.1s actors~ 9 cpu_busy= 56 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 24.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 25.1s actors~ 9 cpu_busy= 56 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 26.1s actors~ 9 cpu_busy= 56 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 27.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 28.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 29.1s actors~ 9 cpu_busy= 55 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 30.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 31.1s actors~ 9 cpu_busy= 56 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 32.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 33.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 34.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 35.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 36.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 37.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 38.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 39.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 40.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 41.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 42.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 43.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 44.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 45.1s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 46.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 47.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 48.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 49.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 50.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 51.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 52.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 53.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 54.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 55.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 56.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 57.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 58.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 59.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 60.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 61.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 62.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 63.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 64.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 65.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 66.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 67.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 68.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 69.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 70.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 71.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 72.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 73.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 74.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 75.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 76.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 77.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 78.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 79.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 80.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 81.2s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 82.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 83.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 84.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 85.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 86.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 87.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 88.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 89.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 90.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 91.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 92.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 93.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 94.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 95.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 96.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 97.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 98.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 99.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 100.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 101.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 102.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 103.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 104.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 105.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 106.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 107.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 108.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 109.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 110.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 111.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 112.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 113.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 114.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 115.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 116.3s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 117.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 118.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 119.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 120.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 121.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 122.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 123.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 124.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 125.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 126.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 127.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 128.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 129.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 130.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 131.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 132.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 133.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 134.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 135.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 136.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 137.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 138.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 139.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 140.4s actors~ 9 cpu_busy= 54 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 141.4s actors~ 8 cpu_busy= 48 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 142.4s actors~ 3 cpu_busy= 18 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 143.4s actors~ 1 cpu_busy= 6 \u2588\u2588\u2588\u2588\u2588\n 144.4s actors~ 1 cpu_busy= 6 \u2588\u2588\u2588\u2588\u2588\n 145.4s actors~ 0 cpu_busy= 0 \n 146.4s actors~ 0 cpu_busy= 0 \n 147.4s actors~ 1 cpu_busy= 4 \u2588\u2588\u2588\u2588\u2588\n 148.5s actors~ 0 cpu_busy= 0 \n 149.5s actors~ 0 cpu_busy= 0 \n 150.5s actors~ 0 cpu_busy= 0 \n 151.5s actors~ 0 cpu_busy= 0 \n 152.5s actors~ 0 cpu_busy= 0 \n 153.5s actors~ 0 cpu_busy= 0 \n 154.5s actors~ 0 cpu_busy= 0 \n 155.5s actors~ 4 cpu_busy= 23 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 156.5s actors~11 cpu_busy= 64 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 157.5s actors~ 0 cpu_busy= 0 \n 158.5s actors~10 cpu_busy= 60 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 159.5s actors~ 8 cpu_busy= 50 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 160.5s actors~ 4 cpu_busy= 26 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 161.5s actors~ 5 cpu_busy= 28 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 162.5s actors~ 3 cpu_busy= 19 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 163.5s actors~ 3 cpu_busy= 18 \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\n 164.5s actors~ 1 cpu_busy= 4 \u2588\u2588\u2588\u2588\u2588\n 165.5s actors~ 0 cpu_busy= 0 \n 166.6s actors~ 0 cpu_busy= 0 \n 167.6s actors~ 0 cpu_busy= 0 \n 168.6s actors~ 0 cpu_busy= 0 \n 169.6s actors~ 0 cpu_busy= 0 \n 170.6s actors~ 0 cpu_busy= 0 \n 171.6s actors~ 0 cpu_busy= 0 \n 172.6s actors~ 0 cpu_busy= 0 \n 173.6s actors~ 0 cpu_busy= 0 \n 174.6s actors~ 0 cpu_busy= 0 \n 175.7s actors~ 0 cpu_busy= 0 \n 176.7s actors~ 0 cpu_busy= 0 \n 177.7s actors~ 0 cpu_busy= 0 \n 178.7s actors~ 0 cpu_busy= 0 \n 179.7s actors~ 0 cpu_busy= 0 \n 180.7s actors~ 0 cpu_busy= 0 \n 181.7s actors~ 0 cpu_busy= 0 \n 182.7s actors~ 0 cpu_busy= 0 \n 183.8s actors~ 0 cpu_busy= 0 \n 184.8s actors~ 0 cpu_busy= 0 \n 185.8s actors~ 0 cpu_busy= 0 \n 186.8s actors~ 0 cpu_busy= 0 \n 187.8s actors~ 0 cpu_busy= 0 \n 188.8s actors~ 0 cpu_busy= 0 \n 189.8s actors~ 0 cpu_busy= 0 \n 190.8s actors~ 0 cpu_busy= 0 \n 191.9s actors~ 0 cpu_busy= 0 \n 192.9s actors~ 0 cpu_busy= 0 \n 193.9s actors~ 0 cpu_busy= 0 \n 194.9s actors~ 0 cpu_busy= 0 \n 195.9s actors~ 0 cpu_busy= 0 \n 196.9s actors~ 0 cpu_busy= 0 \n 197.9s actors~ 0 cpu_busy= 0 \n 198.9s actors~ 0 cpu_busy= 0 \n 200.0s actors~ 0 cpu_busy= 0 \n 201.0s actors~ 0 cpu_busy= 0 \n 202.0s actors~ 0 cpu_busy= 0 \n 203.0s actors~ 0 cpu_busy= 0 \n 204.0s actors~ 0 cpu_busy= 0 \n 205.0s actors~ 0 cpu_busy= 0 \n 206.0s actors~ 0 cpu_busy= 0 \n 207.0s actors~ 0 cpu_busy= 0 \n 208.1s actors~ 0 cpu_busy= 0 \n 209.1s actors~ 0 cpu_busy= 0 \n 210.1s actors~ 0 cpu_busy= 0 \n 211.1s actors~ 0 cpu_busy= 0 \n 212.1s actors~ 0 cpu_busy= 0 \n 213.1s actors~ 0 cpu_busy= 0 \n 214.1s actors~ 0 cpu_busy= 0 \n 215.1s actors~ 0 cpu_busy= 0 \n 216.2s actors~ 0 cpu_busy= 0 \n 217.2s actors~ 0 cpu_busy= 0 \n 218.2s actors~ 0 cpu_busy= 0 \n 219.2s actors~ 0 cpu_busy= 0 \n 220.2s actors~ 0 cpu_busy= 0 \n 221.2s actors~ 0 cpu_busy= 0 \n 222.2s actors~ 0 cpu_busy= 0 \n 223.2s actors~ 0 cpu_busy= 0 \n 224.3s actors~ 0 cpu_busy= 0 \n 225.3s actors~ 0 cpu_busy= 0 \n 226.3s actors~ 0 cpu_busy= 0 \n 227.3s actors~ 0 cpu_busy= 0 \n 228.3s actors~ 0 cpu_busy= 0 \n 229.3s actors~ 0 cpu_busy= 0 \n 230.3s actors~ 0 cpu_busy= 0 \n 231.3s actors~ 0 cpu_busy= 0 \n 232.3s actors~ 0 cpu_busy= 0 \n 233.4s actors~ 0 cpu_busy= 0 \n 234.4s actors~ 0 cpu_busy= 0 \n 235.4s actors~ 0 cpu_busy= 0 \n 236.4s actors~ 0 cpu_busy= 0 \n 237.4s actors~ 0 cpu_busy= 0 \n 238.4s actors~ 0 cpu_busy= 0 \n 239.4s actors~ 0 cpu_busy= 0 \n 240.4s actors~ 0 cpu_busy= 0 \n 241.5s actors~ 0 cpu_busy= 0 \n 242.5s actors~ 0 cpu_busy= 0 \n 243.5s actors~ 0 cpu_busy= 0 \n 244.5s actors~ 0 cpu_busy= 0 \n 245.5s actors~ 0 cpu_busy= 0 \n 246.5s actors~ 0 cpu_busy= 0 \n 247.5s actors~ 0 cpu_busy= 0 \n 248.6s actors~ 0 cpu_busy= 0 \n 249.6s actors~ 0 cpu_busy= 0 \n 250.6s actors~ 0 cpu_busy= 0 \n 251.6s actors~ 0 cpu_busy= 0 \n 252.6s actors~ 0 cpu_busy= 0 \n 253.6s actors~ 0 cpu_busy= 0 \n 254.6s actors~ 0 cpu_busy= 0 \n 255.6s actors~ 0 cpu_busy= 0 \n 256.6s actors~ 0 cpu_busy= 0 \n 257.7s actors~ 0 cpu_busy= 0 \n 258.7s actors~ 0 cpu_busy= 0 \n 259.7s actors~ 0 cpu_busy= 0 \n 260.7s actors~ 0 cpu_busy= 0 \n 261.7s actors~ 0 cpu_busy= 0 \n 262.7s actors~ 0 cpu_busy= 0 \n 263.7s actors~ 0 cpu_busy= 0 \n 264.8s actors~ 0 cpu_busy= 0 \n 265.8s actors~ 0 cpu_busy= 0 \n 266.8s actors~ 0 cpu_busy= 0 \n 267.8s actors~ 0 cpu_busy= 0 \n 268.8s actors~ 0 cpu_busy= 0 \n 269.8s actors~ 0 cpu_busy= 0 \n 270.8s actors~ 0 cpu_busy= 0 \n 271.8s actors~ 0 cpu_busy= 0 \n 272.9s actors~ 0 cpu_busy= 0 \n 273.9s actors~ 0 cpu_busy= 0 \n 274.9s actors~ 0 cpu_busy= 0 \n 275.9s actors~ 0 cpu_busy= 0 \n 276.9s actors~ 0 cpu_busy= 0 \n 277.9s actors~ 0 cpu_busy= 0 \n 278.9s actors~ 0 cpu_busy= 0 \n 279.9s actors~ 0 cpu_busy= 0 \n 280.9s actors~ 0 cpu_busy= 0 \n 281.9s actors~ 0 cpu_busy= 0 \n 282.9s actors~ 0 cpu_busy= 0 \n 284.0s actors~ 0 cpu_busy= 0 \n 285.0s actors~ 0 cpu_busy= 0 \n 286.0s actors~ 0 cpu_busy= 0 \n 287.0s actors~ 0 cpu_busy= 0 \n 288.0s actors~ 0 cpu_busy= 0 \n 289.0s actors~ 0 cpu_busy= 0 \n 290.0s actors~ 0 cpu_busy= 0 \n 291.0s actors~ 0 cpu_busy= 0 \n 292.0s actors~ 0 cpu_busy= 0 \n 293.0s actors~ 0 cpu_busy= 0 \n 294.0s actors~ 0 cpu_busy= 0 \n 295.0s actors~ 0 cpu_busy= 0 \n 296.0s actors~ 0 cpu_busy= 0 \n 297.0s actors~ 0 cpu_busy= 0 \n 298.0s actors~ 0 cpu_busy= 0 \n 299.0s actors~ 0 cpu_busy= 0 \n 300.1s actors~ 0 cpu_busy= 0 \n 301.1s actors~ 0 cpu_busy= 0 \n 302.1s actors~ 0 cpu_busy= 0 \n 303.1s actors~ 0 cpu_busy= 0 \n 304.1s actors~ 0 cpu_busy= 0 \n 305.1s actors~ 0 cpu_busy= 0 \n 306.1s actors~ 0 cpu_busy= 0 \n 307.1s actors~ 0 cpu_busy= 0 \n 308.2s actors~ 0 cpu_busy= 0 \n 309.2s actors~ 0 cpu_busy= 0 \n 310.2s actors~ 0 cpu_busy= 0 \n 311.2s actors~ 0 cpu_busy= 0 \n 312.2s actors~ 0 cpu_busy= 0 \n 313.2s actors~ 0 cpu_busy= 0 \n 314.2s actors~ 0 cpu_busy= 0 \n 315.2s actors~ 0 cpu_busy= 0 \n 316.3s actors~ 0 cpu_busy= 0 \n 317.3s actors~ 0 cpu_busy= 0 \n 318.3s actors~ 0 cpu_busy= 0 \n 319.3s actors~ 0 cpu_busy= 0 \n 320.3s actors~ 0 cpu_busy= 0 \n 321.3s actors~ 0 cpu_busy= 0 \n 322.3s actors~ 0 cpu_busy= 0 \n 323.3s actors~ 0 cpu_busy= 0 \n 324.4s actors~ 0 cpu_busy= 0 \n 325.4s actors~ 0 cpu_busy= 0 \n 326.4s actors~ 0 cpu_busy= 0 \n 327.4s actors~ 0 cpu_busy= 0 \n 328.4s actors~ 0 cpu_busy= 0 \n 329.4s actors~ 0 cpu_busy= 0 \n 330.4s actors~ 0 cpu_busy= 0 \n 331.4s actors~ 0 cpu_busy= 0 \n peak=11 avg=3.9 zero-actor-samples=179/330\n\n========================================================================\n SUMMARY\n========================================================================\n Strategy time(s) peak avg zero%\n ----------------------------------- -------- ------ ------ -------\n ActorPool(min=1, max=N, initial=N) 360.6 10 3.9 45.4%\n ActorPool(min=N, max=N) 332.0 11 3.9 54.2%\n\n Speedup (min=N vs min=1): 1.09x\n" + "text": [ + "\n", + "=== Run 1: ActorPool(min=1, max=N, initial=N) ===\n", + " 0.0s actors~ 0 cpu_busy= 0 \n", + " 1.0s actors~ 9 cpu_busy= 55 ██████████████████████████████████████████████████████\n", + " 2.0s actors~ 9 cpu_busy= 55 ██████████████████████████████████████████████████████\n", + " 3.0s actors~ 9 cpu_busy= 55 ██████████████████████████████████████████████████████\n", + " 4.0s actors~ 9 cpu_busy= 55 ██████████████████████████████████████████████████████\n", + " 5.0s actors~ 9 cpu_busy= 55 ██████████████████████████████████████████████████████\n", + " 6.0s actors~ 9 cpu_busy= 55 ██████████████████████████████████████████████████████\n", + " 7.0s actors~ 9 cpu_busy= 55 ██████████████████████████████████████████████████████\n", + " 8.0s actors~ 9 cpu_busy= 55 ██████████████████████████████████████████████████████\n", + " 9.0s actors~ 9 cpu_busy= 55 ██████████████████████████████████████████████████████\n", + " 10.0s actors~ 9 cpu_busy= 55 ██████████████████████████████████████████████████████\n", + " 11.0s actors~ 9 cpu_busy= 55 ██████████████████████████████████████████████████████\n", + " 12.0s actors~ 9 cpu_busy= 55 ██████████████████████████████████████████████████████\n", + " 13.0s actors~ 9 cpu_busy= 55 ██████████████████████████████████████████████████████\n", + " 14.0s actors~ 9 cpu_busy= 55 ██████████████████████████████████████████████████████\n", + " 15.1s actors~ 9 cpu_busy= 55 ██████████████████████████████████████████████████████\n", + " 16.1s actors~ 9 cpu_busy= 55 ██████████████████████████████████████████████████████\n", + " 17.1s actors~ 9 cpu_busy= 55 ██████████████████████████████████████████████████████\n", + " 18.1s actors~ 9 cpu_busy= 55 ██████████████████████████████████████████████████████\n", + " 19.1s actors~ 9 cpu_busy= 55 ██████████████████████████████████████████████████████\n", + " 20.1s actors~ 0 cpu_busy= 0 \n", + " 21.1s actors~ 9 cpu_busy= 52 ██████████████████████████████████████████████████████\n", + " 22.1s actors~ 8 cpu_busy= 46 ████████████████████████████████████████████████\n", + " 23.1s actors~ 7 cpu_busy= 43 ██████████████████████████████████████████\n", + " 24.1s actors~ 6 cpu_busy= 38 ████████████████████████████████████\n", + " 25.1s actors~ 6 cpu_busy= 39 ████████████████████████████████████\n", + " 26.1s actors~ 6 cpu_busy= 37 ████████████████████████████████████\n", + " 27.1s actors~ 6 cpu_busy= 36 ████████████████████████████████████\n", + " 28.1s actors~ 8 cpu_busy= 47 ████████████████████████████████████████████████\n", + " 29.1s actors~ 8 cpu_busy= 51 ████████████████████████████████████████████████\n", + " 30.1s actors~ 8 cpu_busy= 48 ████████████████████████████████████████████████\n", + " 31.1s actors~ 6 cpu_busy= 37 ████████████████████████████████████\n", + " 32.1s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 33.1s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 34.1s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 35.1s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 36.1s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 37.1s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 38.1s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 39.1s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 40.1s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 41.1s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 42.1s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 43.1s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 44.1s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 45.1s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 46.1s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 47.1s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 48.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 49.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 50.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 51.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 52.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 53.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 54.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 55.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 56.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 57.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 58.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 59.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 60.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 61.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 62.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 63.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 64.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 65.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 66.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 67.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 68.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 69.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 70.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 71.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 72.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 73.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 74.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 75.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 76.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 77.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 78.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 79.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 80.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 81.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 82.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 83.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 84.2s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 85.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 86.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 87.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 88.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 89.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 90.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 91.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 92.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 93.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 94.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 95.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 96.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 97.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 98.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 99.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 100.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 101.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 102.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 103.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 104.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 105.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 106.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 107.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 108.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 109.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 110.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 111.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 112.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 113.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 114.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 115.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 116.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 117.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 118.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 119.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 120.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 121.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 122.3s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 123.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 124.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 125.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 126.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 127.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 128.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 129.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 130.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 131.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 132.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 133.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 134.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 135.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 136.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 137.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 138.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 139.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 140.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 141.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 142.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 143.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 144.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 145.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 146.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 147.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 148.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 149.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 150.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 151.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 152.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 153.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 154.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 155.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 156.4s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 157.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 158.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 159.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 160.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 161.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 162.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 163.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 164.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 165.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 166.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 167.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 168.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 169.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 170.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 171.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 172.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 173.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 174.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 175.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 176.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 177.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 178.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 179.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 180.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 181.5s actors~ 7 cpu_busy= 42 ██████████████████████████████████████████\n", + " 182.5s actors~ 4 cpu_busy= 24 ████████████████████████\n", + " 183.5s actors~ 2 cpu_busy= 12 ████████████\n", + " 184.5s actors~ 1 cpu_busy= 6 ██████\n", + " 185.8s actors~ 2 cpu_busy= 13 ████████████\n", + " 186.9s actors~ 0 cpu_busy= 0 \n", + " 187.9s actors~ 0 cpu_busy= 0 \n", + " 188.9s actors~ 0 cpu_busy= 0 \n", + " 189.9s actors~ 0 cpu_busy= 0 \n", + " 190.9s actors~ 0 cpu_busy= 0 \n", + " 191.9s actors~ 0 cpu_busy= 0 \n", + " 192.9s actors~10 cpu_busy= 62 ████████████████████████████████████████████████████████████\n", + " 193.9s actors~10 cpu_busy= 58 ████████████████████████████████████████████████████████████\n", + " 194.9s actors~ 9 cpu_busy= 55 ██████████████████████████████████████████████████████\n", + " 195.9s actors~ 9 cpu_busy= 56 ██████████████████████████████████████████████████████\n", + " 196.9s actors~ 8 cpu_busy= 47 ████████████████████████████████████████████████\n", + " 197.9s actors~ 7 cpu_busy= 41 ██████████████████████████████████████████\n", + " 198.9s actors~ 6 cpu_busy= 37 ████████████████████████████████████\n", + " 199.9s actors~ 4 cpu_busy= 26 ████████████████████████\n", + " 200.9s actors~ 4 cpu_busy= 22 ████████████████████████\n", + " 202.0s actors~ 3 cpu_busy= 20 ██████████████████\n", + " 203.0s actors~ 1 cpu_busy= 6 ██████\n", + " 204.0s actors~ 0 cpu_busy= 0 \n", + " 205.0s actors~ 0 cpu_busy= 0 \n", + " 206.0s actors~ 0 cpu_busy= 0 \n", + " 207.0s actors~ 0 cpu_busy= 0 \n", + " 208.0s actors~ 0 cpu_busy= 0 \n", + " 209.1s actors~ 0 cpu_busy= 0 \n", + " 210.1s actors~ 0 cpu_busy= 0 \n", + " 211.1s actors~ 0 cpu_busy= 0 \n", + " 212.1s actors~ 0 cpu_busy= 0 \n", + " 213.1s actors~ 0 cpu_busy= 0 \n", + " 214.2s actors~ 0 cpu_busy= 0 \n", + " 215.2s actors~ 0 cpu_busy= 0 \n", + " 216.2s actors~ 0 cpu_busy= 0 \n", + " 217.2s actors~ 0 cpu_busy= 0 \n", + " 218.2s actors~ 0 cpu_busy= 0 \n", + " 219.2s actors~ 0 cpu_busy= 0 \n", + " 220.2s actors~ 0 cpu_busy= 0 \n", + " 221.2s actors~ 0 cpu_busy= 0 \n", + " 222.2s actors~ 0 cpu_busy= 0 \n", + " 223.3s actors~ 0 cpu_busy= 0 \n", + " 224.3s actors~ 0 cpu_busy= 0 \n", + " 225.3s actors~ 0 cpu_busy= 0 \n", + " 226.3s actors~ 0 cpu_busy= 0 \n", + " 227.3s actors~ 0 cpu_busy= 0 \n", + " 228.3s actors~ 0 cpu_busy= 0 \n", + " 229.4s actors~ 0 cpu_busy= 0 \n", + " 230.4s actors~ 0 cpu_busy= 0 \n", + " 231.4s actors~ 0 cpu_busy= 0 \n", + " 232.4s actors~ 0 cpu_busy= 0 \n", + " 233.4s actors~ 0 cpu_busy= 0 \n", + " 234.4s actors~ 0 cpu_busy= 0 \n", + " 235.4s actors~ 0 cpu_busy= 0 \n", + " 236.4s actors~ 0 cpu_busy= 0 \n", + " 237.5s actors~ 0 cpu_busy= 0 \n", + " 238.5s actors~ 0 cpu_busy= 0 \n", + " 239.5s actors~ 0 cpu_busy= 0 \n", + " 240.5s actors~ 0 cpu_busy= 0 \n", + " 241.5s actors~ 0 cpu_busy= 0 \n", + " 242.5s actors~ 0 cpu_busy= 0 \n", + " 243.5s actors~ 0 cpu_busy= 0 \n", + " 244.5s actors~ 0 cpu_busy= 0 \n", + " 245.5s actors~ 0 cpu_busy= 0 \n", + " 246.5s actors~ 0 cpu_busy= 0 \n", + " 247.5s actors~ 0 cpu_busy= 0 \n", + " 248.5s actors~ 0 cpu_busy= 0 \n", + " 249.6s actors~ 0 cpu_busy= 0 \n", + " 250.6s actors~ 0 cpu_busy= 0 \n", + " 251.6s actors~ 0 cpu_busy= 0 \n", + " 252.6s actors~ 0 cpu_busy= 0 \n", + " 253.6s actors~ 0 cpu_busy= 0 \n", + " 254.6s actors~ 0 cpu_busy= 0 \n", + " 255.6s actors~ 0 cpu_busy= 0 \n", + " 256.6s actors~ 0 cpu_busy= 0 \n", + " 257.7s actors~ 0 cpu_busy= 0 \n", + " 258.7s actors~ 0 cpu_busy= 0 \n", + " 259.7s actors~ 0 cpu_busy= 0 \n", + " 260.7s actors~ 0 cpu_busy= 0 \n", + " 261.7s actors~ 0 cpu_busy= 0 \n", + " 262.7s actors~ 0 cpu_busy= 0 \n", + " 263.7s actors~ 0 cpu_busy= 0 \n", + " 264.8s actors~ 0 cpu_busy= 0 \n", + " 265.8s actors~ 0 cpu_busy= 0 \n", + " 266.8s actors~ 0 cpu_busy= 0 \n", + " 267.8s actors~ 0 cpu_busy= 0 \n", + " 268.9s actors~ 0 cpu_busy= 0 \n", + " 269.9s actors~ 0 cpu_busy= 0 \n", + " 270.9s actors~ 0 cpu_busy= 0 \n", + " 271.9s actors~ 0 cpu_busy= 0 \n", + " 272.9s actors~ 0 cpu_busy= 0 \n", + " 273.9s actors~ 0 cpu_busy= 0 \n", + " 274.9s actors~ 0 cpu_busy= 0 \n", + " 276.0s actors~ 0 cpu_busy= 0 \n", + " 277.0s actors~ 0 cpu_busy= 0 \n", + " 278.0s actors~ 0 cpu_busy= 0 \n", + " 279.0s actors~ 0 cpu_busy= 0 \n", + " 280.0s actors~ 0 cpu_busy= 0 \n", + " 281.0s actors~ 0 cpu_busy= 0 \n", + " 282.0s actors~ 0 cpu_busy= 0 \n", + " 283.1s actors~ 0 cpu_busy= 0 \n", + " 284.1s actors~ 0 cpu_busy= 0 \n", + " 285.1s actors~ 0 cpu_busy= 0 \n", + " 286.1s actors~ 0 cpu_busy= 0 \n", + " 287.1s actors~ 0 cpu_busy= 0 \n", + " 288.1s actors~ 0 cpu_busy= 0 \n", + " 289.1s actors~ 0 cpu_busy= 0 \n", + " 290.2s actors~ 0 cpu_busy= 0 \n", + " 291.2s actors~ 0 cpu_busy= 0 \n", + " 292.2s actors~ 0 cpu_busy= 0 \n", + " 293.2s actors~ 0 cpu_busy= 0 \n", + " 294.2s actors~ 0 cpu_busy= 0 \n", + " 295.2s actors~ 0 cpu_busy= 0 \n", + " 296.2s actors~ 0 cpu_busy= 0 \n", + " 297.2s actors~ 0 cpu_busy= 0 \n", + " 298.2s actors~ 0 cpu_busy= 0 \n", + " 299.2s actors~ 0 cpu_busy= 0 \n", + " 300.2s actors~ 0 cpu_busy= 0 \n", + " 301.3s actors~ 0 cpu_busy= 0 \n", + " 302.3s actors~ 0 cpu_busy= 0 \n", + " 303.3s actors~ 0 cpu_busy= 0 \n", + " 304.3s actors~ 0 cpu_busy= 0 \n", + " 305.3s actors~ 0 cpu_busy= 0 \n", + " 306.3s actors~ 0 cpu_busy= 0 \n", + " 307.4s actors~ 0 cpu_busy= 0 \n", + " 308.4s actors~ 0 cpu_busy= 0 \n", + " 309.4s actors~ 0 cpu_busy= 0 \n", + " 310.5s actors~ 0 cpu_busy= 0 \n", + " 311.5s actors~ 0 cpu_busy= 0 \n", + " 312.5s actors~ 0 cpu_busy= 0 \n", + " 313.5s actors~ 0 cpu_busy= 0 \n", + " 314.5s actors~ 0 cpu_busy= 0 \n", + " 315.5s actors~ 0 cpu_busy= 0 \n", + " 316.5s actors~ 0 cpu_busy= 0 \n", + " 317.6s actors~ 0 cpu_busy= 0 \n", + " 318.6s actors~ 0 cpu_busy= 0 \n", + " 319.6s actors~ 0 cpu_busy= 0 \n", + " 320.6s actors~ 0 cpu_busy= 0 \n", + " 321.6s actors~ 0 cpu_busy= 0 \n", + " 322.7s actors~ 0 cpu_busy= 0 \n", + " 323.7s actors~ 0 cpu_busy= 0 \n", + " 324.7s actors~ 0 cpu_busy= 0 \n", + " 325.7s actors~ 0 cpu_busy= 0 \n", + " 326.7s actors~ 0 cpu_busy= 0 \n", + " 327.8s actors~ 0 cpu_busy= 0 \n", + " 328.8s actors~ 0 cpu_busy= 0 \n", + " 329.8s actors~ 0 cpu_busy= 0 \n", + " 330.8s actors~ 0 cpu_busy= 0 \n", + " 331.8s actors~ 0 cpu_busy= 0 \n", + " 332.8s actors~ 0 cpu_busy= 0 \n", + " 333.9s actors~ 0 cpu_busy= 0 \n", + " 334.9s actors~ 0 cpu_busy= 0 \n", + " 335.9s actors~ 0 cpu_busy= 0 \n", + " 336.9s actors~ 0 cpu_busy= 0 \n", + " 337.9s actors~ 0 cpu_busy= 0 \n", + " 339.0s actors~ 0 cpu_busy= 0 \n", + " 340.0s actors~ 0 cpu_busy= 0 \n", + " 341.0s actors~ 0 cpu_busy= 0 \n", + " 342.0s actors~ 0 cpu_busy= 0 \n", + " 343.0s actors~ 0 cpu_busy= 0 \n", + " 344.1s actors~ 0 cpu_busy= 0 \n", + " 345.1s actors~ 0 cpu_busy= 0 \n", + " 346.1s actors~ 0 cpu_busy= 0 \n", + " 347.1s actors~ 0 cpu_busy= 0 \n", + " 348.1s actors~ 0 cpu_busy= 0 \n", + " 349.1s actors~ 0 cpu_busy= 0 \n", + " 350.1s actors~ 0 cpu_busy= 0 \n", + " 351.1s actors~ 0 cpu_busy= 0 \n", + " 352.2s actors~ 0 cpu_busy= 0 \n", + " 353.2s actors~ 0 cpu_busy= 0 \n", + " 354.2s actors~ 0 cpu_busy= 0 \n", + " 355.2s actors~ 0 cpu_busy= 0 \n", + " 356.2s actors~ 0 cpu_busy= 0 \n", + " 357.2s actors~ 0 cpu_busy= 0 \n", + " 358.2s actors~ 0 cpu_busy= 0 \n", + " 359.2s actors~ 0 cpu_busy= 0 \n", + " peak=10 avg=3.9 zero-actor-samples=162/357\n", + "\n", + "=== Run 2: ActorPool(min=N, max=N) ===\n", + " 0.0s actors~ 0 cpu_busy= 0 \n", + " 1.0s actors~ 9 cpu_busy= 55 █████████████████████████████████████████████████\n", + " 2.0s actors~ 9 cpu_busy= 55 █████████████████████████████████████████████████\n", + " 3.0s actors~ 9 cpu_busy= 55 █████████████████████████████████████████████████\n", + " 4.0s actors~ 9 cpu_busy= 55 █████████████████████████████████████████████████\n", + " 5.0s actors~ 9 cpu_busy= 55 █████████████████████████████████████████████████\n", + " 6.0s actors~ 9 cpu_busy= 55 █████████████████████████████████████████████████\n", + " 7.0s actors~ 9 cpu_busy= 55 █████████████████████████████████████████████████\n", + " 8.0s actors~ 9 cpu_busy= 55 █████████████████████████████████████████████████\n", + " 9.0s actors~ 9 cpu_busy= 55 █████████████████████████████████████████████████\n", + " 10.0s actors~ 9 cpu_busy= 55 █████████████████████████████████████████████████\n", + " 11.0s actors~ 9 cpu_busy= 55 █████████████████████████████████████████████████\n", + " 12.0s actors~ 9 cpu_busy= 55 █████████████████████████████████████████████████\n", + " 13.0s actors~ 9 cpu_busy= 55 █████████████████████████████████████████████████\n", + " 14.0s actors~ 9 cpu_busy= 55 █████████████████████████████████████████████████\n", + " 15.1s actors~ 9 cpu_busy= 55 █████████████████████████████████████████████████\n", + " 16.1s actors~ 9 cpu_busy= 55 █████████████████████████████████████████████████\n", + " 17.1s actors~ 9 cpu_busy= 55 █████████████████████████████████████████████████\n", + " 18.1s actors~ 0 cpu_busy= 0 \n", + " 19.1s actors~10 cpu_busy= 57 ██████████████████████████████████████████████████████\n", + " 20.1s actors~ 0 cpu_busy= 0 \n", + " 21.1s actors~10 cpu_busy= 57 ██████████████████████████████████████████████████████\n", + " 22.1s actors~ 0 cpu_busy= 0 \n", + " 23.1s actors~ 9 cpu_busy= 56 █████████████████████████████████████████████████\n", + " 24.1s actors~ 9 cpu_busy= 55 █████████████████████████████████████████████████\n", + " 25.1s actors~ 9 cpu_busy= 56 █████████████████████████████████████████████████\n", + " 26.1s actors~ 9 cpu_busy= 56 █████████████████████████████████████████████████\n", + " 27.1s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 28.1s actors~ 9 cpu_busy= 55 █████████████████████████████████████████████████\n", + " 29.1s actors~ 9 cpu_busy= 55 █████████████████████████████████████████████████\n", + " 30.1s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 31.1s actors~ 9 cpu_busy= 56 █████████████████████████████████████████████████\n", + " 32.1s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 33.1s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 34.1s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 35.1s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 36.1s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 37.1s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 38.1s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 39.1s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 40.1s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 41.1s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 42.1s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 43.1s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 44.1s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 45.1s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 46.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 47.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 48.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 49.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 50.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 51.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 52.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 53.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 54.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 55.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 56.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 57.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 58.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 59.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 60.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 61.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 62.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 63.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 64.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 65.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 66.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 67.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 68.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 69.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 70.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 71.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 72.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 73.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 74.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 75.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 76.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 77.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 78.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 79.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 80.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 81.2s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 82.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 83.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 84.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 85.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 86.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 87.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 88.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 89.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 90.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 91.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 92.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 93.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 94.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 95.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 96.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 97.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 98.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 99.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 100.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 101.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 102.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 103.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 104.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 105.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 106.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 107.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 108.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 109.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 110.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 111.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 112.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 113.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 114.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 115.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 116.3s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 117.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 118.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 119.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 120.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 121.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 122.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 123.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 124.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 125.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 126.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 127.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 128.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 129.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 130.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 131.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 132.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 133.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 134.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 135.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 136.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 137.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 138.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 139.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 140.4s actors~ 9 cpu_busy= 54 █████████████████████████████████████████████████\n", + " 141.4s actors~ 8 cpu_busy= 48 ███████████████████████████████████████████\n", + " 142.4s actors~ 3 cpu_busy= 18 ████████████████\n", + " 143.4s actors~ 1 cpu_busy= 6 █████\n", + " 144.4s actors~ 1 cpu_busy= 6 █████\n", + " 145.4s actors~ 0 cpu_busy= 0 \n", + " 146.4s actors~ 0 cpu_busy= 0 \n", + " 147.4s actors~ 1 cpu_busy= 4 █████\n", + " 148.5s actors~ 0 cpu_busy= 0 \n", + " 149.5s actors~ 0 cpu_busy= 0 \n", + " 150.5s actors~ 0 cpu_busy= 0 \n", + " 151.5s actors~ 0 cpu_busy= 0 \n", + " 152.5s actors~ 0 cpu_busy= 0 \n", + " 153.5s actors~ 0 cpu_busy= 0 \n", + " 154.5s actors~ 0 cpu_busy= 0 \n", + " 155.5s actors~ 4 cpu_busy= 23 █████████████████████\n", + " 156.5s actors~11 cpu_busy= 64 ███████████████████████████████████████████████████████████\n", + " 157.5s actors~ 0 cpu_busy= 0 \n", + " 158.5s actors~10 cpu_busy= 60 ██████████████████████████████████████████████████████\n", + " 159.5s actors~ 8 cpu_busy= 50 ███████████████████████████████████████████\n", + " 160.5s actors~ 4 cpu_busy= 26 █████████████████████\n", + " 161.5s actors~ 5 cpu_busy= 28 ███████████████████████████\n", + " 162.5s actors~ 3 cpu_busy= 19 ████████████████\n", + " 163.5s actors~ 3 cpu_busy= 18 ████████████████\n", + " 164.5s actors~ 1 cpu_busy= 4 █████\n", + " 165.5s actors~ 0 cpu_busy= 0 \n", + " 166.6s actors~ 0 cpu_busy= 0 \n", + " 167.6s actors~ 0 cpu_busy= 0 \n", + " 168.6s actors~ 0 cpu_busy= 0 \n", + " 169.6s actors~ 0 cpu_busy= 0 \n", + " 170.6s actors~ 0 cpu_busy= 0 \n", + " 171.6s actors~ 0 cpu_busy= 0 \n", + " 172.6s actors~ 0 cpu_busy= 0 \n", + " 173.6s actors~ 0 cpu_busy= 0 \n", + " 174.6s actors~ 0 cpu_busy= 0 \n", + " 175.7s actors~ 0 cpu_busy= 0 \n", + " 176.7s actors~ 0 cpu_busy= 0 \n", + " 177.7s actors~ 0 cpu_busy= 0 \n", + " 178.7s actors~ 0 cpu_busy= 0 \n", + " 179.7s actors~ 0 cpu_busy= 0 \n", + " 180.7s actors~ 0 cpu_busy= 0 \n", + " 181.7s actors~ 0 cpu_busy= 0 \n", + " 182.7s actors~ 0 cpu_busy= 0 \n", + " 183.8s actors~ 0 cpu_busy= 0 \n", + " 184.8s actors~ 0 cpu_busy= 0 \n", + " 185.8s actors~ 0 cpu_busy= 0 \n", + " 186.8s actors~ 0 cpu_busy= 0 \n", + " 187.8s actors~ 0 cpu_busy= 0 \n", + " 188.8s actors~ 0 cpu_busy= 0 \n", + " 189.8s actors~ 0 cpu_busy= 0 \n", + " 190.8s actors~ 0 cpu_busy= 0 \n", + " 191.9s actors~ 0 cpu_busy= 0 \n", + " 192.9s actors~ 0 cpu_busy= 0 \n", + " 193.9s actors~ 0 cpu_busy= 0 \n", + " 194.9s actors~ 0 cpu_busy= 0 \n", + " 195.9s actors~ 0 cpu_busy= 0 \n", + " 196.9s actors~ 0 cpu_busy= 0 \n", + " 197.9s actors~ 0 cpu_busy= 0 \n", + " 198.9s actors~ 0 cpu_busy= 0 \n", + " 200.0s actors~ 0 cpu_busy= 0 \n", + " 201.0s actors~ 0 cpu_busy= 0 \n", + " 202.0s actors~ 0 cpu_busy= 0 \n", + " 203.0s actors~ 0 cpu_busy= 0 \n", + " 204.0s actors~ 0 cpu_busy= 0 \n", + " 205.0s actors~ 0 cpu_busy= 0 \n", + " 206.0s actors~ 0 cpu_busy= 0 \n", + " 207.0s actors~ 0 cpu_busy= 0 \n", + " 208.1s actors~ 0 cpu_busy= 0 \n", + " 209.1s actors~ 0 cpu_busy= 0 \n", + " 210.1s actors~ 0 cpu_busy= 0 \n", + " 211.1s actors~ 0 cpu_busy= 0 \n", + " 212.1s actors~ 0 cpu_busy= 0 \n", + " 213.1s actors~ 0 cpu_busy= 0 \n", + " 214.1s actors~ 0 cpu_busy= 0 \n", + " 215.1s actors~ 0 cpu_busy= 0 \n", + " 216.2s actors~ 0 cpu_busy= 0 \n", + " 217.2s actors~ 0 cpu_busy= 0 \n", + " 218.2s actors~ 0 cpu_busy= 0 \n", + " 219.2s actors~ 0 cpu_busy= 0 \n", + " 220.2s actors~ 0 cpu_busy= 0 \n", + " 221.2s actors~ 0 cpu_busy= 0 \n", + " 222.2s actors~ 0 cpu_busy= 0 \n", + " 223.2s actors~ 0 cpu_busy= 0 \n", + " 224.3s actors~ 0 cpu_busy= 0 \n", + " 225.3s actors~ 0 cpu_busy= 0 \n", + " 226.3s actors~ 0 cpu_busy= 0 \n", + " 227.3s actors~ 0 cpu_busy= 0 \n", + " 228.3s actors~ 0 cpu_busy= 0 \n", + " 229.3s actors~ 0 cpu_busy= 0 \n", + " 230.3s actors~ 0 cpu_busy= 0 \n", + " 231.3s actors~ 0 cpu_busy= 0 \n", + " 232.3s actors~ 0 cpu_busy= 0 \n", + " 233.4s actors~ 0 cpu_busy= 0 \n", + " 234.4s actors~ 0 cpu_busy= 0 \n", + " 235.4s actors~ 0 cpu_busy= 0 \n", + " 236.4s actors~ 0 cpu_busy= 0 \n", + " 237.4s actors~ 0 cpu_busy= 0 \n", + " 238.4s actors~ 0 cpu_busy= 0 \n", + " 239.4s actors~ 0 cpu_busy= 0 \n", + " 240.4s actors~ 0 cpu_busy= 0 \n", + " 241.5s actors~ 0 cpu_busy= 0 \n", + " 242.5s actors~ 0 cpu_busy= 0 \n", + " 243.5s actors~ 0 cpu_busy= 0 \n", + " 244.5s actors~ 0 cpu_busy= 0 \n", + " 245.5s actors~ 0 cpu_busy= 0 \n", + " 246.5s actors~ 0 cpu_busy= 0 \n", + " 247.5s actors~ 0 cpu_busy= 0 \n", + " 248.6s actors~ 0 cpu_busy= 0 \n", + " 249.6s actors~ 0 cpu_busy= 0 \n", + " 250.6s actors~ 0 cpu_busy= 0 \n", + " 251.6s actors~ 0 cpu_busy= 0 \n", + " 252.6s actors~ 0 cpu_busy= 0 \n", + " 253.6s actors~ 0 cpu_busy= 0 \n", + " 254.6s actors~ 0 cpu_busy= 0 \n", + " 255.6s actors~ 0 cpu_busy= 0 \n", + " 256.6s actors~ 0 cpu_busy= 0 \n", + " 257.7s actors~ 0 cpu_busy= 0 \n", + " 258.7s actors~ 0 cpu_busy= 0 \n", + " 259.7s actors~ 0 cpu_busy= 0 \n", + " 260.7s actors~ 0 cpu_busy= 0 \n", + " 261.7s actors~ 0 cpu_busy= 0 \n", + " 262.7s actors~ 0 cpu_busy= 0 \n", + " 263.7s actors~ 0 cpu_busy= 0 \n", + " 264.8s actors~ 0 cpu_busy= 0 \n", + " 265.8s actors~ 0 cpu_busy= 0 \n", + " 266.8s actors~ 0 cpu_busy= 0 \n", + " 267.8s actors~ 0 cpu_busy= 0 \n", + " 268.8s actors~ 0 cpu_busy= 0 \n", + " 269.8s actors~ 0 cpu_busy= 0 \n", + " 270.8s actors~ 0 cpu_busy= 0 \n", + " 271.8s actors~ 0 cpu_busy= 0 \n", + " 272.9s actors~ 0 cpu_busy= 0 \n", + " 273.9s actors~ 0 cpu_busy= 0 \n", + " 274.9s actors~ 0 cpu_busy= 0 \n", + " 275.9s actors~ 0 cpu_busy= 0 \n", + " 276.9s actors~ 0 cpu_busy= 0 \n", + " 277.9s actors~ 0 cpu_busy= 0 \n", + " 278.9s actors~ 0 cpu_busy= 0 \n", + " 279.9s actors~ 0 cpu_busy= 0 \n", + " 280.9s actors~ 0 cpu_busy= 0 \n", + " 281.9s actors~ 0 cpu_busy= 0 \n", + " 282.9s actors~ 0 cpu_busy= 0 \n", + " 284.0s actors~ 0 cpu_busy= 0 \n", + " 285.0s actors~ 0 cpu_busy= 0 \n", + " 286.0s actors~ 0 cpu_busy= 0 \n", + " 287.0s actors~ 0 cpu_busy= 0 \n", + " 288.0s actors~ 0 cpu_busy= 0 \n", + " 289.0s actors~ 0 cpu_busy= 0 \n", + " 290.0s actors~ 0 cpu_busy= 0 \n", + " 291.0s actors~ 0 cpu_busy= 0 \n", + " 292.0s actors~ 0 cpu_busy= 0 \n", + " 293.0s actors~ 0 cpu_busy= 0 \n", + " 294.0s actors~ 0 cpu_busy= 0 \n", + " 295.0s actors~ 0 cpu_busy= 0 \n", + " 296.0s actors~ 0 cpu_busy= 0 \n", + " 297.0s actors~ 0 cpu_busy= 0 \n", + " 298.0s actors~ 0 cpu_busy= 0 \n", + " 299.0s actors~ 0 cpu_busy= 0 \n", + " 300.1s actors~ 0 cpu_busy= 0 \n", + " 301.1s actors~ 0 cpu_busy= 0 \n", + " 302.1s actors~ 0 cpu_busy= 0 \n", + " 303.1s actors~ 0 cpu_busy= 0 \n", + " 304.1s actors~ 0 cpu_busy= 0 \n", + " 305.1s actors~ 0 cpu_busy= 0 \n", + " 306.1s actors~ 0 cpu_busy= 0 \n", + " 307.1s actors~ 0 cpu_busy= 0 \n", + " 308.2s actors~ 0 cpu_busy= 0 \n", + " 309.2s actors~ 0 cpu_busy= 0 \n", + " 310.2s actors~ 0 cpu_busy= 0 \n", + " 311.2s actors~ 0 cpu_busy= 0 \n", + " 312.2s actors~ 0 cpu_busy= 0 \n", + " 313.2s actors~ 0 cpu_busy= 0 \n", + " 314.2s actors~ 0 cpu_busy= 0 \n", + " 315.2s actors~ 0 cpu_busy= 0 \n", + " 316.3s actors~ 0 cpu_busy= 0 \n", + " 317.3s actors~ 0 cpu_busy= 0 \n", + " 318.3s actors~ 0 cpu_busy= 0 \n", + " 319.3s actors~ 0 cpu_busy= 0 \n", + " 320.3s actors~ 0 cpu_busy= 0 \n", + " 321.3s actors~ 0 cpu_busy= 0 \n", + " 322.3s actors~ 0 cpu_busy= 0 \n", + " 323.3s actors~ 0 cpu_busy= 0 \n", + " 324.4s actors~ 0 cpu_busy= 0 \n", + " 325.4s actors~ 0 cpu_busy= 0 \n", + " 326.4s actors~ 0 cpu_busy= 0 \n", + " 327.4s actors~ 0 cpu_busy= 0 \n", + " 328.4s actors~ 0 cpu_busy= 0 \n", + " 329.4s actors~ 0 cpu_busy= 0 \n", + " 330.4s actors~ 0 cpu_busy= 0 \n", + " 331.4s actors~ 0 cpu_busy= 0 \n", + " peak=11 avg=3.9 zero-actor-samples=179/330\n", + "\n", + "========================================================================\n", + " SUMMARY\n", + "========================================================================\n", + " Strategy time(s) peak avg zero%\n", + " ----------------------------------- -------- ------ ------ -------\n", + " ActorPool(min=1, max=N, initial=N) 360.6 10 3.9 45.4%\n", + " ActorPool(min=N, max=N) 332.0 11 3.9 54.2%\n", + "\n", + " Speedup (min=N vs min=1): 1.09x\n" + ] } ], - "source": "def print_actor_trace(label, snapshots, width=60):\n if not snapshots:\n print(f\"[{label}] no snapshots captured\")\n return\n times = [s[0] for s in snapshots]\n busy = [s[1] for s in snapshots]\n actors = [s[2] for s in snapshots]\n peak = max(actors) if actors else 0\n if peak == 0:\n print(f\"[{label}] all snapshots show 0 actors (busy CPU always 0?)\")\n # show busy cpu trace anyway\n peak_b = max(busy) if busy else 1\n scale = width / max(peak_b, 1)\n for ts, b, a in zip(times, busy, actors):\n bar = \"\u2588\" * int(b * scale)\n print(f\" {ts:7.1f}s cpu_busy={b:4.0f} {bar}\")\n return\n scale = width / peak\n for ts, b, a in zip(times, busy, actors):\n bar = \"\u2588\" * int(a * scale)\n print(f\" {ts:7.1f}s actors~{a:2d} cpu_busy={b:4.0f} {bar}\")\n avg = sum(actors) / len(actors)\n zeros = sum(1 for a in actors if a == 0)\n print(f\" peak={peak} avg={avg:.1f} zero-actor-samples={zeros}/{len(actors)}\")\n\nprint(\"\\n=== Run 1: ActorPool(min=1, max=N, initial=N) ===\")\nprint_actor_trace(\"min=1\", snaps1)\n\nprint(\"\\n=== Run 2: ActorPool(min=N, max=N) ===\")\nprint_actor_trace(\"min=N\", snaps2)\n\nprint()\nprint(\"=\" * 72)\nprint(\" SUMMARY\")\nprint(\"=\" * 72)\npeak1 = max((s[2] for s in snaps1), default=0)\npeak2 = max((s[2] for s in snaps2), default=0)\navg1 = sum(s[2] for s in snaps1) / len(snaps1) if snaps1 else 0\navg2 = sum(s[2] for s in snaps2) / len(snaps2) if snaps2 else 0\nzero1 = sum(1 for s in snaps1 if s[2] == 0)\nzero2 = sum(1 for s in snaps2 if s[2] == 0)\nprint(f\" {'Strategy':<35} {'time(s)':>8} {'peak':>6} {'avg':>6} {'zero%':>7}\")\nprint(f\" {'-'*35} {'-'*8} {'-'*6} {'-'*6} {'-'*7}\")\nprint(f\" {'ActorPool(min=1, max=N, initial=N)':<35} {elapsed1:>8.1f} {peak1:>6} {avg1:>6.1f} {100*zero1/len(snaps1) if snaps1 else 0:>6.1f}%\")\nprint(f\" {'ActorPool(min=N, max=N)':<35} {elapsed2:>8.1f} {peak2:>6} {avg2:>6.1f} {100*zero2/len(snaps2) if snaps2 else 0:>6.1f}%\")\nspeedup = elapsed1 / elapsed2 if elapsed2 else 0\nprint(f\"\\n Speedup (min=N vs min=1): {speedup:.2f}x\")\n" + "source": [ + "def print_actor_trace(label, snapshots, width=60):\n", + " if not snapshots:\n", + " print(f\"[{label}] no snapshots captured\")\n", + " return\n", + " times = [s[0] for s in snapshots]\n", + " busy = [s[1] for s in snapshots]\n", + " actors = [s[2] for s in snapshots]\n", + " peak = max(actors) if actors else 0\n", + " if peak == 0:\n", + " print(f\"[{label}] all snapshots show 0 actors (busy CPU always 0?)\")\n", + " # show busy cpu trace anyway\n", + " peak_b = max(busy) if busy else 1\n", + " scale = width / max(peak_b, 1)\n", + " for ts, b, a in zip(times, busy, actors):\n", + " bar = \"█\" * int(b * scale)\n", + " print(f\" {ts:7.1f}s cpu_busy={b:4.0f} {bar}\")\n", + " return\n", + " scale = width / peak\n", + " for ts, b, a in zip(times, busy, actors):\n", + " bar = \"█\" * int(a * scale)\n", + " print(f\" {ts:7.1f}s actors~{a:2d} cpu_busy={b:4.0f} {bar}\")\n", + " avg = sum(actors) / len(actors)\n", + " zeros = sum(1 for a in actors if a == 0)\n", + " print(f\" peak={peak} avg={avg:.1f} zero-actor-samples={zeros}/{len(actors)}\")\n", + "\n", + "\n", + "print(\"\\n=== Run 1: ActorPool(min=1, max=N, initial=N) ===\")\n", + "print_actor_trace(\"min=1\", snaps1)\n", + "\n", + "print(\"\\n=== Run 2: ActorPool(min=N, max=N) ===\")\n", + "print_actor_trace(\"min=N\", snaps2)\n", + "\n", + "print()\n", + "print(\"=\" * 72)\n", + "print(\" SUMMARY\")\n", + "print(\"=\" * 72)\n", + "peak1 = max((s[2] for s in snaps1), default=0)\n", + "peak2 = max((s[2] for s in snaps2), default=0)\n", + "avg1 = sum(s[2] for s in snaps1) / len(snaps1) if snaps1 else 0\n", + "avg2 = sum(s[2] for s in snaps2) / len(snaps2) if snaps2 else 0\n", + "zero1 = sum(1 for s in snaps1 if s[2] == 0)\n", + "zero2 = sum(1 for s in snaps2 if s[2] == 0)\n", + "print(f\" {'Strategy':<35} {'time(s)':>8} {'peak':>6} {'avg':>6} {'zero%':>7}\")\n", + "print(f\" {'-' * 35} {'-' * 8} {'-' * 6} {'-' * 6} {'-' * 7}\")\n", + "print(\n", + " f\" {'ActorPool(min=1, max=N, initial=N)':<35} {elapsed1:>8.1f} {peak1:>6} {avg1:>6.1f} {100 * zero1 / len(snaps1) if snaps1 else 0:>6.1f}%\"\n", + ")\n", + "print(\n", + " f\" {'ActorPool(min=N, max=N)':<35} {elapsed2:>8.1f} {peak2:>6} {avg2:>6.1f} {100 * zero2 / len(snaps2) if snaps2 else 0:>6.1f}%\"\n", + ")\n", + "speedup = elapsed1 / elapsed2 if elapsed2 else 0\n", + "print(f\"\\n Speedup (min=N vs min=1): {speedup:.2f}x\")" + ] }, { "cell_type": "code", @@ -90,12 +2690,64 @@ "metadata": {}, "outputs": [ { - "output_type": "stream", "name": "stdout", - "text": "========================================================================\n OBSERVATION SUMMARY\n========================================================================\n\n Run 1 ActorPoolStrategy(initial_size=N, min_size=1, max_size=N):\n - Actor count dropped from 9 and stabilized around 7\n - Throughput: 2.77 vid/s (360.6s total)\n\n Run 2 ActorPoolStrategy(min_size=N, max_size=N):\n - Actor count stable at 9 throughout\n - Throughput: 3.01 vid/s (332.0s total)\n\n Expected: Run 1 >= Run 2 (same max actors).\n Observed: Run 1 ~9% slower.\n\n" + "output_type": "stream", + "text": [ + "========================================================================\n", + " OBSERVATION SUMMARY\n", + "========================================================================\n", + "\n", + " Run 1 ActorPoolStrategy(initial_size=N, min_size=1, max_size=N):\n", + " - Actor count dropped from 9 and stabilized around 7\n", + " - Throughput: 2.77 vid/s (360.6s total)\n", + "\n", + " Run 2 ActorPoolStrategy(min_size=N, max_size=N):\n", + " - Actor count stable at 9 throughout\n", + " - Throughput: 3.01 vid/s (332.0s total)\n", + "\n", + " Expected: Run 1 >= Run 2 (same max actors).\n", + " Observed: Run 1 ~9% slower.\n", + "\n" + ] } ], - "source": "# \u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\n# OBSERVATION\n# \u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\n#\n# We ran two configurations on a video transcoding pipeline:\n# Run 1: ActorPoolStrategy(initial_size=9, min_size=1, max_size=9)\n# Run 2: ActorPoolStrategy(min_size=9, max_size=9)\n#\n# Run 1 was slower despite having the same max actor count.\n# The actor trace shows the pool drops from 9 and stabilizes around 7,\n# while Run 2 stays at 9 throughout.\n#\n# We expect Run 1 to perform at least as well as Run 2.\n#\n# \u2500\u2500 Autoscaler log (Run 1, from ray-data debug log) \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n#\n# Scaled up actor pool by 9\n# Scaled down actor pool by 1 (running=8, then further to ~7)\n\nprint(\"=\" * 72)\nprint(\" OBSERVATION SUMMARY\")\nprint(\"=\" * 72)\nsummary = \"\"\"\n Run 1 ActorPoolStrategy(initial_size=N, min_size=1, max_size=N):\n - Actor count dropped from 9 and stabilized around 7\n - Throughput: 2.77 vid/s (360.6s total)\n\n Run 2 ActorPoolStrategy(min_size=N, max_size=N):\n - Actor count stable at 9 throughout\n - Throughput: 3.01 vid/s (332.0s total)\n\n Expected: Run 1 >= Run 2 (same max actors).\n Observed: Run 1 ~9% slower.\n\"\"\"\nprint(summary)\n" + "source": [ + "# ══════════════════════════════════════════════════════════════════════════════\n", + "# OBSERVATION\n", + "# ══════════════════════════════════════════════════════════════════════════════\n", + "#\n", + "# We ran two configurations on a video transcoding pipeline:\n", + "# Run 1: ActorPoolStrategy(initial_size=9, min_size=1, max_size=9)\n", + "# Run 2: ActorPoolStrategy(min_size=9, max_size=9)\n", + "#\n", + "# Run 1 was slower despite having the same max actor count.\n", + "# The actor trace shows the pool drops from 9 and stabilizes around 7,\n", + "# while Run 2 stays at 9 throughout.\n", + "#\n", + "# We expect Run 1 to perform at least as well as Run 2.\n", + "#\n", + "# ── Autoscaler log (Run 1, from ray-data debug log) ─────────────────────────\n", + "#\n", + "# Scaled up actor pool by 9\n", + "# Scaled down actor pool by 1 (running=8, then further to ~7)\n", + "\n", + "print(\"=\" * 72)\n", + "print(\" OBSERVATION SUMMARY\")\n", + "print(\"=\" * 72)\n", + "summary = \"\"\"\n", + " Run 1 ActorPoolStrategy(initial_size=N, min_size=1, max_size=N):\n", + " - Actor count dropped from 9 and stabilized around 7\n", + " - Throughput: 2.77 vid/s (360.6s total)\n", + "\n", + " Run 2 ActorPoolStrategy(min_size=N, max_size=N):\n", + " - Actor count stable at 9 throughout\n", + " - Throughput: 3.01 vid/s (332.0s total)\n", + "\n", + " Expected: Run 1 >= Run 2 (same max actors).\n", + " Observed: Run 1 ~9% slower.\n", + "\"\"\"\n", + "print(summary)" + ] } ], "metadata": { @@ -119,4 +2771,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} \ No newline at end of file +} From 8a621ebfd01cfce5dbcb1e2f94ca685f64df4d1d Mon Sep 17 00:00:00 2001 From: Weijia Chen Date: Tue, 7 Jul 2026 02:41:11 +0000 Subject: [PATCH 3/6] min repro --- ray_actorpool_minimal_repro.ipynb | 1136 +++++++++++++++++++++++++++++ 1 file changed, 1136 insertions(+) create mode 100644 ray_actorpool_minimal_repro.ipynb diff --git a/ray_actorpool_minimal_repro.ipynb b/ray_actorpool_minimal_repro.ipynb new file mode 100644 index 0000000000..7e9878222c --- /dev/null +++ b/ray_actorpool_minimal_repro.ipynb @@ -0,0 +1,1136 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "ff034cc5", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-07T02:23:13.964975Z", + "iopub.status.busy": "2026-07-07T02:23:13.964511Z", + "iopub.status.idle": "2026-07-07T02:23:15.598865Z", + "shell.execute_reply": "2026-07-07T02:23:15.597137Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Ray version: 2.55.1\n" + ] + } + ], + "source": [ + "# Ray Data ActorPool Underutilization -- Minimal Reproducer\n", + "# ==========================================================\n", + "# Shows that ActorPoolStrategy(initial_size=N, min_size=1) underutilizes\n", + "# the actor pool and delivers lower throughput than\n", + "# ActorPoolStrategy(min_size=N, max_size=N), even though both\n", + "# configurations have the same maximum number of actors.\n", + "#\n", + "# No external dependencies -- uses only sleep() to simulate work.\n", + "# Tested on: Ray 2.55.1\n", + "\n", + "import ray\n", + "import ray.data\n", + "import time, threading, random\n", + "\n", + "print(f\"Ray version: {ray.__version__}\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "aa465035", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-07T02:23:15.605383Z", + "iopub.status.busy": "2026-07-07T02:23:15.604971Z", + "iopub.status.idle": "2026-07-07T02:23:15.609034Z", + "shell.execute_reply": "2026-07-07T02:23:15.607794Z" + } + }, + "outputs": [], + "source": [ + "NUM_ITEMS = 100 # total items to process\n", + "ACTOR_CPUS = 6.0 # CPUs reserved per WorkActor\n", + "NUM_ACTORS = 9 # max actor pool size\n", + "WORK_DELAY = 1.0 # seconds per item (simulates actor work)\n", + "UPSTREAM_DELAY = 15 # seconds before first item is ready (> 10s debounce)\n", + "DELIVERY_INTERVAL = 0.3 # seconds between the first NUM_ACTORS items;\n", + " # slow delivery gives autoscaler time to fire between items\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "82a6f5c1", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-07T02:23:15.613516Z", + "iopub.status.busy": "2026-07-07T02:23:15.613218Z", + "iopub.status.idle": "2026-07-07T02:23:15.617625Z", + "shell.execute_reply": "2026-07-07T02:23:15.616487Z" + } + }, + "outputs": [], + "source": [ + "class SlowSource:\n", + " \"\"\"Delivers items with a long initial delay, then slowly for the first\n", + " NUM_ACTORS items (giving the autoscaler time to fire), then bursts.\"\"\"\n", + " def __init__(self):\n", + " self._count = 0\n", + " def __call__(self, batch):\n", + " if self._count == 0:\n", + " # Simulate slow upstream I/O (e.g. S3/NFS file listing).\n", + " # The initial delay lets the actor scale-down debounce (10s) expire.\n", + " time.sleep(UPSTREAM_DELAY)\n", + " if self._count < NUM_ACTORS:\n", + " # Slow delivery for the first N items: gives the autoscaler time to\n", + " # observe low utilization (1 busy / N actors = 0.11) and scale down.\n", + " time.sleep(DELIVERY_INTERVAL)\n", + " self._count += 1\n", + " return batch\n", + "\n", + "class WorkActor:\n", + " def __call__(self, batch):\n", + " # Jitter breaks synchronized batch completion.\n", + " time.sleep(WORK_DELAY + random.uniform(-0.4, 0.4))\n", + " return batch\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "4dd83683", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-07T02:23:15.620485Z", + "iopub.status.busy": "2026-07-07T02:23:15.620260Z", + "iopub.status.idle": "2026-07-07T02:24:59.350526Z", + "shell.execute_reply": "2026-07-07T02:24:59.348671Z" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:28,335\tINFO worker.py:2003 -- Started a local Ray instance. View the dashboard at \u001b[1m\u001b[32mhttp://127.0.0.1:8269 \u001b[39m\u001b[22m\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/raid/weijiac/Curator/.venv/lib/python3.12/site-packages/ray/_private/worker.py:2051: FutureWarning: Tip: In future versions of Ray, Ray will no longer override accelerator visible devices env var if num_gpus=0 or num_gpus=None (default). To enable this behavior and turn off this error message, set RAY_ACCEL_ENV_VAR_OVERRIDE_ON_ZERO=0\n", + " warnings.warn(\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:30,780\tINFO logging.py:416 -- Registered dataset logger for dataset dataset_2_0\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:30,798\tINFO streaming_executor.py:166 -- Starting execution of Dataset dataset_2_0. Full logs are in /tmp/ray/session_2026-07-07_02-23-15_847817_3368973/logs/ray-data\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:30,800\tINFO streaming_executor.py:167 -- Execution plan of Dataset dataset_2_0: InputDataBuffer[Input] -> ActorPoolMapOperator[MapBatches(SlowSource)] -> ActorPoolMapOperator[MapBatches(WorkActor)]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[2026-07-07 02:23:30,834 E 3368973 3368973] core_worker.cc:2194: Actor with class name: 'MapWorker(MapBatches(SlowSource))' and ID: '94b6548935f5b3d1bd204e9701000000' has constructor arguments in the object store and max_restarts > 0. If the arguments in the object store go out of scope or are lost, the actor restart will fail. See https://github.com/ray-project/ray/issues/53727 for more details.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:30,991\tWARNING resource_manager.py:169 -- ⚠️ Ray's object store is configured to use only 9.6% of available memory (186.3GiB out of 1947.4GiB total). For optimal Ray Data performance, we recommend setting the object store to at least 50% of available memory. You can do this by setting the 'object_store_memory' parameter when calling ray.init() or by setting the RAY_DEFAULT_OBJECT_STORE_MEMORY_PROPORTION environment variable.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:30,995\tINFO __init__.py:56 -- Progress will be logged because stdout is a non-interactive terminal.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:31,619\tWARNING default_actor_autoscaler.py:214 -- ⚠️ Actor Pool configuration of the ActorPoolMapOperator[MapBatches(WorkActor)] will not allow it to scale up: configured utilization threshold (175.0%) couldn't be reached with configured max_concurrency=1 and max_tasks_in_flight_per_actor=1 (max utilization will be max_tasks_in_flight_per_actor / max_concurrency = 100%)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:31,757\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_2_0 =======\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:31,759\tINFO logging_progress.py:225 -- Total Progress: 0/?\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:31,760\tINFO logging_progress.py:227 -- Active & requested resources: 42.5/64 CPU, 0.0B/93.1GiB object store (pending: 12 CPU)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:31,760\tINFO logging_progress.py:181 -- \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:31,761\tINFO logging_progress.py:231 -- MapBatches(SlowSource): 0/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:31,761\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 1; Queued blocks: 99 (0.0B); Resources: 0.5 CPU, 0.0B object store; [all objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:31,762\tINFO logging_progress.py:231 -- MapBatches(WorkActor): 0/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:31,762\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 9 (running=7, restarting=0, pending=2); Queued blocks: 0 (0.0B); Resources: 42.0 CPU, 0.0B object store; [all objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:31,762\tINFO logging_progress.py:192 -- ============================================\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:41,793\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_2_0 =======\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:41,795\tINFO logging_progress.py:225 -- Total Progress: 0/?\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:41,797\tINFO logging_progress.py:227 -- Active & requested resources: 54.5/64 CPU, 0.0B/93.1GiB object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:41,798\tINFO logging_progress.py:181 -- \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:41,800\tINFO logging_progress.py:231 -- MapBatches(SlowSource): 0/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:23:41,801\tINFO logging_progress.py:233 -- Tasks: 2; 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Full logs are in /tmp/ray/session_2026-07-07_02-23-15_847817_3368973/logs/ray-data\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:24:26,580\tINFO streaming_executor.py:167 -- Execution plan of Dataset dataset_5_0: InputDataBuffer[Input] -> ActorPoolMapOperator[MapBatches(SlowSource)] -> ActorPoolMapOperator[MapBatches(WorkActor)]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ActorPool(min=1, max=N, initial=N)] 56.6s\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:24:26,868\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:24:26,869\tINFO logging_progress.py:225 -- Total Progress: 0/?\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:24:26,870\tINFO logging_progress.py:227 -- Active & requested resources: 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Tasks: 9; Actors: 9; Queued blocks: 8 (64.0B); Resources: 54.0 CPU, 80.0B object store; [0/92 objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:24:56,971\tINFO logging_progress.py:192 -- ============================================\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-07 02:24:59,325\tINFO streaming_executor.py:294 -- ✔️ Dataset dataset_5_0 execution finished in 32.74 seconds\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ActorPool(min=N, max=N)] 32.9s\n" + ] + } + ], + "source": [ + "ray.shutdown()\n", + "ray.init(num_cpus=64)\n", + "\n", + "def _monitor(snapshots, stop_event, interval=1.0):\n", + " # Track active actor count via CPU utilization.\n", + " total = ray.cluster_resources().get(\"CPU\", 64)\n", + " t0 = time.perf_counter()\n", + " while not stop_event.is_set():\n", + " try:\n", + " avail = ray.available_resources().get(\"CPU\", 0) # 0 = all CPUs allocated (key absent when oversubscribed)\n", + " busy = max(0.0, total - avail)\n", + " # Cap at actor pool CPUs: other pipeline stages also consume CPUs\n", + " actor_busy = min(busy, NUM_ACTORS * ACTOR_CPUS)\n", + " snapshots.append((time.perf_counter() - t0, actor_busy, round(actor_busy / ACTOR_CPUS)))\n", + " except Exception:\n", + " pass\n", + " stop_event.wait(interval)\n", + "\n", + "def run_pipeline(compute, label):\n", + " snapshots, stop_event = [], threading.Event()\n", + " t = threading.Thread(target=_monitor, args=(snapshots, stop_event), daemon=True)\n", + " t0 = time.perf_counter()\n", + " ds = (\n", + " ray.data.from_items([{\"id\": i} for i in range(NUM_ITEMS)])\n", + " .map_batches(SlowSource, batch_size=1,\n", + " compute=ActorPoolStrategy(size=1), num_cpus=0.5)\n", + " .map_batches(WorkActor, batch_size=1, num_cpus=ACTOR_CPUS, compute=compute)\n", + " )\n", + " t.start()\n", + " ds.take_all()\n", + " stop_event.set(); t.join(timeout=3)\n", + " elapsed = time.perf_counter() - t0\n", + " print(f\"[{label}] {elapsed:.1f}s\")\n", + " return elapsed, snapshots\n", + "\n", + "from ray.data import ActorPoolStrategy\n", + "\n", + "elapsed1, snaps1 = run_pipeline(\n", + " ActorPoolStrategy(min_size=1, max_size=NUM_ACTORS, initial_size=NUM_ACTORS,\n", + " max_tasks_in_flight_per_actor=1),\n", + " \"ActorPool(min=1, max=N, initial=N)\"\n", + ")\n", + "elapsed2, snaps2 = run_pipeline(\n", + " ActorPoolStrategy(min_size=NUM_ACTORS, max_size=NUM_ACTORS,\n", + " max_tasks_in_flight_per_actor=1),\n", + " \"ActorPool(min=N, max=N)\"\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "b29cae17", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-07T02:24:59.357711Z", + "iopub.status.busy": "2026-07-07T02:24:59.357420Z", + "iopub.status.idle": "2026-07-07T02:24:59.365911Z", + "shell.execute_reply": "2026-07-07T02:24:59.364004Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "=== Run 1: ActorPool(min=1, max=N, initial=N) ===\n", + " 0.0s actors~ 0 \n", + " 1.0s actors~ 9 ############################################################\n", + " 2.0s actors~ 9 ############################################################\n", + " 3.0s actors~ 9 ############################################################\n", + " 4.0s actors~ 9 ############################################################\n", + " 5.0s actors~ 9 ############################################################\n", + " 6.0s actors~ 9 ############################################################\n", + " 7.0s actors~ 9 ############################################################\n", + " 8.0s actors~ 9 ############################################################\n", + " 9.0s actors~ 9 ############################################################\n", + " 10.0s actors~ 9 ############################################################\n", + " 11.0s actors~ 9 ############################################################\n", + " 12.0s actors~ 9 ############################################################\n", + " 13.0s actors~ 9 ############################################################\n", + " 14.0s actors~ 9 ############################################################\n", + " 15.0s actors~ 9 ############################################################\n", + " 16.1s actors~ 9 ############################################################\n", + " 17.1s actors~ 9 ############################################################\n", + " 18.1s actors~ 4 ##########################\n", + " 19.1s actors~ 3 ####################\n", + " 20.1s actors~ 3 ####################\n", + " 21.1s actors~ 3 ####################\n", + " 22.1s actors~ 3 ####################\n", + " 23.1s actors~ 3 ####################\n", + " 24.1s actors~ 3 ####################\n", + " 25.1s actors~ 3 ####################\n", + " 26.1s actors~ 3 ####################\n", + " 27.1s actors~ 3 ####################\n", + " 28.1s actors~ 3 ####################\n", + " 29.1s actors~ 3 ####################\n", + " 30.1s actors~ 3 ####################\n", + " 31.1s actors~ 3 ####################\n", + " 32.1s actors~ 3 ####################\n", + " 33.1s actors~ 3 ####################\n", + " 34.1s actors~ 3 ####################\n", + " 35.1s actors~ 3 ####################\n", + " 36.1s actors~ 3 ####################\n", + " 37.1s actors~ 3 ####################\n", + " 38.1s actors~ 3 ####################\n", + " 39.1s actors~ 3 ####################\n", + " 40.1s actors~ 3 ####################\n", + " 41.1s actors~ 3 ####################\n", + " 42.1s actors~ 3 ####################\n", + " 43.1s actors~ 3 ####################\n", + " 44.1s actors~ 3 ####################\n", + " 45.2s actors~ 3 ####################\n", + " 46.2s actors~ 3 ####################\n", + " 47.2s actors~ 3 ####################\n", + " 48.2s actors~ 3 ####################\n", + " 49.2s actors~ 3 ####################\n", + " 50.2s actors~ 3 ####################\n", + " 51.2s actors~ 3 ####################\n", + " 52.2s actors~ 3 ####################\n", + " 53.2s actors~ 3 ####################\n", + " 54.2s actors~ 3 ####################\n", + " 55.2s actors~ 3 ####################\n", + " peak=9 avg=4.8\n", + "\n", + "=== Run 2: ActorPool(min=N, max=N) ===\n", + " 0.0s actors~ 0 \n", + " 1.0s actors~ 9 ############################################################\n", + " 2.0s actors~ 9 ############################################################\n", + " 3.0s actors~ 9 ############################################################\n", + " 4.0s actors~ 9 ############################################################\n", + " 5.0s actors~ 9 ############################################################\n", + " 6.0s actors~ 9 ############################################################\n", + " 7.0s actors~ 9 ############################################################\n", + " 8.0s actors~ 9 ############################################################\n", + " 9.0s actors~ 9 ############################################################\n", + " 10.0s actors~ 9 ############################################################\n", + " 11.0s actors~ 9 ############################################################\n", + " 12.0s actors~ 9 ############################################################\n", + " 13.0s actors~ 9 ############################################################\n", + " 14.0s actors~ 9 ############################################################\n", + " 15.1s actors~ 9 ############################################################\n", + " 16.1s actors~ 9 ############################################################\n", + " 17.1s actors~ 9 ############################################################\n", + " 18.1s actors~ 9 ############################################################\n", + " 19.1s actors~ 9 ############################################################\n", + " 20.1s actors~ 9 ############################################################\n", + " 21.1s actors~ 9 ############################################################\n", + " 22.1s actors~ 9 ############################################################\n", + " 23.1s actors~ 9 ############################################################\n", + " 24.1s actors~ 9 ############################################################\n", + " 25.1s actors~ 9 ############################################################\n", + " 26.1s actors~ 9 ############################################################\n", + " 27.1s actors~ 9 ############################################################\n", + " 28.1s actors~ 9 ############################################################\n", + " 29.1s actors~ 9 ############################################################\n", + " 30.1s actors~ 9 ############################################################\n", + " 31.1s actors~ 9 ############################################################\n", + " 32.1s actors~ 6 ########################################\n", + " peak=9 avg=8.6\n", + "\n", + "==================================================\n", + " Run 1: 56.6s\n", + " Run 2: 32.9s\n", + " Run 2 is 1.72x faster\n", + "==================================================\n" + ] + } + ], + "source": [ + "def print_trace(snapshots, width=60):\n", + " peak = max((s[2] for s in snapshots), default=0) or 1\n", + " for ts, busy, actors in snapshots:\n", + " bar = \"#\" * int(actors * width / peak)\n", + " print(f\" {ts:7.1f}s actors~{actors:2d} {bar}\")\n", + " avg = sum(s[2] for s in snapshots) / len(snapshots) if snapshots else 0\n", + " print(f\" peak={peak} avg={avg:.1f}\")\n", + "\n", + "print(\"\\n=== Run 1: ActorPool(min=1, max=N, initial=N) ===\")\n", + "print_trace(snaps1)\n", + "print(\"\\n=== Run 2: ActorPool(min=N, max=N) ===\")\n", + "print_trace(snaps2)\n", + "print()\n", + "print(\"=\" * 50)\n", + "print(f\" Run 1: {elapsed1:.1f}s\")\n", + "print(f\" Run 2: {elapsed2:.1f}s\")\n", + "print(f\" Run 2 is {elapsed1/elapsed2:.2f}x faster\")\n", + "print(\"=\" * 50)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "ec50c62c", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-07T02:24:59.369087Z", + "iopub.status.busy": "2026-07-07T02:24:59.368908Z", + "iopub.status.idle": "2026-07-07T02:24:59.373628Z", + "shell.execute_reply": "2026-07-07T02:24:59.371870Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + " Run 1 ActorPoolStrategy(initial_size=9, min_size=1, max_size=9):\n", + " - Pool cascades down during slow delivery window; stays there (never recovers)\n", + " - Slower throughput (fewer actors processing items)\n", + " Run 2 ActorPoolStrategy(min_size=9, max_size=9):\n", + " - Pool stays at 9 throughout (min_size prevents scale-down)\n", + " - Faster throughput\n", + " Expected: Run 1 >= Run 2 (same max actors).\n", + " Observed: Run 1 is significantly slower.\n", + "\n" + ] + } + ], + "source": [ + "# ======================================================================\n", + "# OBSERVATION\n", + "# ======================================================================\n", + "#\n", + "# We ran two configurations with 9 actors (6 CPUs each) on a 64-CPU machine:\n", + "# Run 1: ActorPoolStrategy(initial_size=9, min_size=1, max_size=9)\n", + "# Run 2: ActorPoolStrategy(min_size=9, max_size=9)\n", + "#\n", + "# Run 1 was slower despite having the same max actor count.\n", + "#\n", + "# The actor trace shows that in Run 1, the pool cascades down during the\n", + "# initial slow-delivery window (first items arrive slowly after a 15s upstream\n", + "# delay, letting the autoscaler observe low utilization and scale down repeatedly).\n", + "# The pool stabilizes at a reduced count and never recovers to 9.\n", + "# Run 2 (min_size=9) blocks scale-down and stays at 9 throughout.\n", + "#\n", + "# We expect Run 1 to perform at least as well as Run 2.\n", + "\n", + "summary = \"\"\"\n", + " Run 1 ActorPoolStrategy(initial_size=9, min_size=1, max_size=9):\n", + " - Pool cascades down during slow delivery window; stays there (never recovers)\n", + " - Slower throughput (fewer actors processing items)\n", + " Run 2 ActorPoolStrategy(min_size=9, max_size=9):\n", + " - Pool stays at 9 throughout (min_size prevents scale-down)\n", + " - Faster throughput\n", + " Expected: Run 1 >= Run 2 (same max actors).\n", + " Observed: Run 1 is significantly slower.\n", + "\"\"\"\n", + "print(summary)\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.11" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 7311be5eba18e493101e686841af758bf81994e2 Mon Sep 17 00:00:00 2001 From: Weijia Chen Date: Tue, 14 Jul 2026 18:58:46 +0000 Subject: [PATCH 4/6] repro download --- reservation_ratio_test.ipynb | 1159 ++++++++++++++++++++++++++++++++++ 1 file changed, 1159 insertions(+) create mode 100644 reservation_ratio_test.ipynb diff --git a/reservation_ratio_test.ipynb b/reservation_ratio_test.ipynb new file mode 100644 index 0000000000..22b923d8cd --- /dev/null +++ b/reservation_ratio_test.ipynb @@ -0,0 +1,1159 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "c00", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-14T18:42:13.294047Z", + "iopub.status.busy": "2026-07-14T18:42:13.293687Z", + "iopub.status.idle": "2026-07-14T18:42:15.146250Z", + "shell.execute_reply": "2026-07-14T18:42:15.143234Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Ray version: 2.56.0\n" + ] + } + ], + "source": [ + "# Repro: Download steals shared CPU pool, starving Iterate|Extract\n", + "#\n", + "# Pipeline: list_files (instant) -> Download (ActorPool) -> Iterate (ActorPool) -> write\n", + "#\n", + "# Budget: 16 CPUs, reservation_ratio=0.5, 2 eligible ops\n", + "# reserved/op = 4 CPUs | shared pool = 8 CPUs\n", + "# Download ramps to 12 actors before producing any output -> exhausts shared pool\n", + "# Iterate starts with 0 input and can never exceed its reserved 4 CPUs\n", + "#\n", + "# Bandwidth saturation (Praateek's \"worst part\"):\n", + "# Node egress is fixed. With N download actors, each gets 1/N bandwidth.\n", + "# 12 actors x 10s = 1 actor x 0.83s = same 1.2 files/sec throughput.\n", + "# Extra actors provide zero throughput gain but steal Iterate's shared budget.\n", + "\n", + "import time, threading, collections\n", + "import ray, ray.data\n", + "from ray.data import ActorPoolStrategy\n", + "\n", + "print(f\"Ray version: {ray.__version__}\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "c01", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-14T18:42:15.154020Z", + "iopub.status.busy": "2026-07-14T18:42:15.153609Z", + "iopub.status.idle": "2026-07-14T18:42:15.160212Z", + "shell.execute_reply": "2026-07-14T18:42:15.158293Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Download: 12 actors x 10s = 1.2 files/sec\n", + " 1 actor x 0.83s = 1.2 files/sec (same throughput!)\n", + "Iterate starved (4 actors): 0.8 files/sec\n", + "Iterate potential(12 actors): 2.4 files/sec (3x loss from starvation)\n" + ] + } + ], + "source": [ + "NUM_FILES = 32\n", + "\n", + "# Bandwidth saturation model: simulate peak (12 actors sharing node egress)\n", + "# 1 actor alone: DOWNLOAD_DELAY_SOLO = 0.83s => 1.2 files/sec\n", + "# 12 actors peak: each takes 12 x 0.83 = 10s => still 1.2 files/sec (same!)\n", + "DOWNLOAD_DELAY_SOLO = 10.0 / 12 # ~0.83s with full bandwidth\n", + "DOWNLOAD_PEAK = 12 # actors that exhaust shared pool (reserved=4 + shared=8)\n", + "DOWNLOAD_DELAY = DOWNLOAD_DELAY_SOLO * DOWNLOAD_PEAK # 10s (saturated case)\n", + "\n", + "ITERATE_DELAY = 5.0 # per-item work; 4 reserved actors => 0.8 files/sec (vs 2.4 with 12)\n", + "\n", + "print(f\"Download: {DOWNLOAD_PEAK} actors x {DOWNLOAD_DELAY:.0f}s = {DOWNLOAD_PEAK/DOWNLOAD_DELAY:.1f} files/sec\")\n", + "print(f\" 1 actor x {DOWNLOAD_DELAY_SOLO:.2f}s = {1/DOWNLOAD_DELAY_SOLO:.1f} files/sec (same throughput!)\")\n", + "print(f\"Iterate starved (4 actors): {4/ITERATE_DELAY:.1f} files/sec\")\n", + "print(f\"Iterate potential(12 actors): {12/ITERATE_DELAY:.1f} files/sec ({12//4}x loss from starvation)\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "c02", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-14T18:42:15.164574Z", + "iopub.status.busy": "2026-07-14T18:42:15.164339Z", + "iopub.status.idle": "2026-07-14T18:42:15.173360Z", + "shell.execute_reply": "2026-07-14T18:42:15.171829Z" + } + }, + "outputs": [], + "source": [ + "import ray as _ray\n", + "\n", + "@_ray.remote(num_cpus=0)\n", + "class _Counter:\n", + " def __init__(self):\n", + " self._alloc = collections.defaultdict(int)\n", + " self._active = collections.defaultdict(int)\n", + " self._peak_alloc = collections.defaultdict(int)\n", + " self._peak_active = collections.defaultdict(int)\n", + " def alloc(self, s):\n", + " self._alloc[s] += 1\n", + " self._peak_alloc[s] = max(self._peak_alloc[s], self._alloc[s])\n", + " def dealloc(self, s):\n", + " self._alloc[s] = max(0, self._alloc[s] - 1)\n", + " def enter(self, s):\n", + " self._active[s] += 1\n", + " self._peak_active[s] = max(self._peak_active[s], self._active[s])\n", + " def exit(self, s):\n", + " self._active[s] = max(0, self._active[s] - 1)\n", + " def snapshot(self):\n", + " return {\n", + " \"alloc\": dict(self._alloc),\n", + " \"active\": dict(self._active),\n", + " \"peak_alloc\": dict(self._peak_alloc),\n", + " \"peak_active\": dict(self._peak_active),\n", + " }\n", + "\n", + "def list_files(batch):\n", + " return {\"file_id\": list(range(NUM_FILES))}\n", + "\n", + "def write(batch):\n", + " return batch\n", + "\n", + "class DownloadActor:\n", + " def __init__(self):\n", + " _ray.get_actor(\"_ctr\").alloc.remote(\"dl\")\n", + " def __del__(self):\n", + " try: _ray.get_actor(\"_ctr\").dealloc.remote(\"dl\")\n", + " except Exception: pass\n", + " def __call__(self, batch):\n", + " ctr = _ray.get_actor(\"_ctr\")\n", + " ctr.enter.remote(\"dl\")\n", + " try:\n", + " time.sleep(DOWNLOAD_DELAY)\n", + " return batch\n", + " finally:\n", + " ctr.exit.remote(\"dl\")\n", + "\n", + "class IterateExtractActor:\n", + " def __init__(self):\n", + " _ray.get_actor(\"_ctr\").alloc.remote(\"it\")\n", + " def __del__(self):\n", + " try: _ray.get_actor(\"_ctr\").dealloc.remote(\"it\")\n", + " except Exception: pass\n", + " def __call__(self, batch):\n", + " ctr = _ray.get_actor(\"_ctr\")\n", + " ctr.enter.remote(\"it\")\n", + " try:\n", + " time.sleep(ITERATE_DELAY)\n", + " return batch\n", + " finally:\n", + " ctr.exit.remote(\"it\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "c03", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-14T18:42:15.177939Z", + "iopub.status.busy": "2026-07-14T18:42:15.177750Z", + "iopub.status.idle": "2026-07-14T18:43:24.794726Z", + "shell.execute_reply": "2026-07-14T18:43:24.792511Z" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:31,156\tINFO worker.py:2015 -- Started a local Ray instance. View the dashboard at \u001b[1m\u001b[32mhttp://127.0.0.1:8269 \u001b[39m\u001b[22m\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:33,493\tINFO streaming_executor.py:193 -- Starting execution of Dataset dataset_5_0. Full logs are in /tmp/ray/session_2026-07-14_18-42-15_415223_1786482/logs/ray-data\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:33,494\tINFO streaming_executor.py:194 -- Execution plan of Dataset dataset_5_0: InputDataBuffer[Input] -> TaskPoolMapOperator[MapBatches(list_files)] -> AllToAllOperator[Repartition] -> ActorPoolMapOperator[MapBatches(DownloadActor)] -> ActorPoolMapOperator[MapBatches(IterateExtractActor)] -> TaskPoolMapOperator[MapBatches(write)]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[2026-07-14 18:42:33,529 E 1786482 1786482] core_worker.cc:2149: Actor with class name: 'MapWorker(MapBatches(DownloadActor))' and ID: '35bc8bf4f5733602567622b601000000' has constructor arguments in the object store and max_restarts > 0. If the arguments in the object store go out of scope or are lost, the actor restart will fail. See https://github.com/ray-project/ray/issues/53727 for more details.\n", + "2026-07-14 18:42:33,555\tINFO __init__.py:56 -- Progress will be logged because stdout is a non-interactive terminal.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:33,590\tWARNING resource_manager.py:766 -- Cluster resources are not enough to run any task from TaskPoolMapOperator[MapBatches(list_files)]. The job may hang forever unless the cluster scales up.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:33,712\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:33,713\tINFO logging_progress.py:225 -- Total Progress: 0/?\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:33,715\tINFO logging_progress.py:227 -- Active & requested resources: 0/0 CPU, 0.0B/0.0B object store (pending: 2 CPU)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:33,716\tINFO logging_progress.py:181 -- \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:33,717\tINFO logging_progress.py:231 -- MapBatches(list_files): 0/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:33,718\tINFO logging_progress.py:233 -- Tasks: 1 [backpressured:tasks(ResourceBudget)]; Actors: 0; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:33,719\tINFO logging_progress.py:231 -- Repartition: 0/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:33,719\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:33,720\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:33,720\tINFO logging_progress.py:231 -- MapBatches(DownloadActor): 0/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:33,720\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 1 (running=0, restarting=0, pending=1, active=0, idle=0, util=0.000, tasks_in_flight=0); Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:33,721\tINFO logging_progress.py:231 -- MapBatches(IterateExtractActor): 0/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:33,721\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 1 (running=0, restarting=0, pending=1, active=0, idle=0, util=0.000, tasks_in_flight=0); Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:33,722\tINFO logging_progress.py:231 -- MapBatches(write): 0/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:33,722\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:33,722\tINFO logging_progress.py:192 -- ============================================\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[33m(raylet)\u001b[0m [2026-07-14 18:42:35,063 E 1787769 1787801] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_18-42-15_415223_1786482 is over 95% full, available space: 0.0778694 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:43,741\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:43,745\tINFO logging_progress.py:225 -- Total Progress: 0/?\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:43,746\tINFO logging_progress.py:227 -- Active & requested resources: 8/16 CPU, 256.0B/93.1GiB object store (pending: 2 CPU)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:43,748\tINFO logging_progress.py:181 -- \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:43,749\tINFO logging_progress.py:231 -- MapBatches(list_files): 32/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:43,750\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:43,750\tINFO logging_progress.py:231 -- Repartition: 32/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:43,751\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 256.0B object store; 32 rows output\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:43,752\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:43,753\tINFO logging_progress.py:231 -- MapBatches(DownloadActor): 0/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:43,753\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 9 (running=7, restarting=0, pending=2, active=7, idle=0, util=1.556, tasks_in_flight=14); Queued blocks: 18 (144.0B); Resources: 7.0 CPU, 0.0B object store; [0/14 objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:43,754\tINFO logging_progress.py:231 -- MapBatches(IterateExtractActor): 0/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:43,754\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 1; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store; [all objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:43,754\tINFO logging_progress.py:231 -- MapBatches(write): 0/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:43,754\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:43,754\tINFO logging_progress.py:192 -- ============================================\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[33m(raylet)\u001b[0m [2026-07-14 18:42:45,085 E 1787769 1787801] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_18-42-15_415223_1786482 is over 95% full, available space: 0.0775299 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:53,788\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:53,791\tINFO logging_progress.py:225 -- Total Progress: 1/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:53,794\tINFO logging_progress.py:227 -- Active & requested resources: 15/16 CPU, 16.0B/1.9TiB memory, 376.0B/93.1GiB object store (pending: 1 CPU, 8.0B memory)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:53,795\tINFO logging_progress.py:181 -- \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:53,796\tINFO logging_progress.py:231 -- MapBatches(list_files): 32/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:53,797\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:53,797\tINFO logging_progress.py:231 -- Repartition: 32/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:53,798\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 200.0B object store; 32 rows output\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:53,799\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:53,800\tINFO logging_progress.py:231 -- MapBatches(DownloadActor): 7/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:53,801\tINFO logging_progress.py:233 -- Tasks: 24; Actors: 12; Queued blocks: 1 (8.0B); Resources: 12.0 CPU, 8.0B memory, 136.0B object store; [0/31 objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:53,802\tINFO logging_progress.py:231 -- MapBatches(IterateExtractActor): 2/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:53,803\tINFO logging_progress.py:233 -- Tasks: 5; Actors: 4 (running=3, restarting=0, pending=1, active=3, idle=0, util=1.250, tasks_in_flight=5); Queued blocks: 0 (0.0B); Resources: 3.0 CPU, 32.0B object store; [0/7 objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:53,803\tINFO logging_progress.py:231 -- MapBatches(write): 1/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:53,804\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B memory, 8.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:42:53,805\tINFO logging_progress.py:192 -- ============================================\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[33m(raylet)\u001b[0m [2026-07-14 18:42:55,107 E 1787769 1787801] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_18-42-15_415223_1786482 is over 95% full, available space: 0.0772705 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:03,649\tWARNING issue_detector_manager.py:69 -- \n", + "\n", + "Operator 'MapBatches(write)' uses 114.8MiB of memory per task on\n", + "average, but Ray only requests 0.0B per task at the start of the\n", + "pipeline.\n", + "\n", + "To avoid out-of-memory errors, consider setting `memory=114.8MiB` in\n", + "the appropriate function or method call. (This might be unnecessary if\n", + "the number of concurrent tasks is low.)\n", + "\n", + "To change the frequency of this warning, set\n", + "`DataContext.get_current().issue_detectors_config.high_memory_detector_config.detection_time_interval_s`,\n", + "or disable the warning by setting value to -1. (current value: 30)\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:03,652\tWARNING issue_detector_manager.py:96 -- Found 1 issues. To disable issue detection, run DataContext.get_current().issue_detectors_config.detectors = [].\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:03,870\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:03,872\tINFO logging_progress.py:225 -- Total Progress: 8/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:03,874\tINFO logging_progress.py:227 -- Active & requested resources: 16/16 CPU, 24.0B/1.9TiB memory, 336.0B/93.1GiB object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:03,876\tINFO logging_progress.py:181 -- \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:03,876\tINFO logging_progress.py:231 -- MapBatches(list_files): 32/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:03,877\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:03,877\tINFO logging_progress.py:231 -- Repartition: 32/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:03,878\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 104.0B object store; 32 rows output\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:03,880\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:03,881\tINFO logging_progress.py:231 -- MapBatches(DownloadActor): 19/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:03,884\tINFO logging_progress.py:233 -- Tasks: 13; Actors: 12; Queued blocks: 0 (0.0B); Resources: 12.0 CPU, 8.0B memory, 176.0B object store; [0/32 objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:03,885\tINFO logging_progress.py:231 -- MapBatches(IterateExtractActor): 9/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:03,886\tINFO logging_progress.py:233 -- Tasks: 8; Actors: 4; Queued blocks: 2 (16.0B); Resources: 4.0 CPU, 8.0B memory, 40.0B object store; [0/17 objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:03,886\tINFO logging_progress.py:231 -- MapBatches(write): 8/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:03,887\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B memory, 16.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:03,888\tINFO logging_progress.py:192 -- ============================================\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[33m(raylet)\u001b[0m [2026-07-14 18:43:05,128 E 1787769 1787801] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_18-42-15_415223_1786482 is over 95% full, available space: 0.0770836 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:13,959\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:13,961\tINFO logging_progress.py:225 -- Total Progress: 19/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:13,963\tINFO logging_progress.py:227 -- Active & requested resources: 11/16 CPU, 56.0B/1.9TiB memory, 200.0B/93.1GiB object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:13,964\tINFO logging_progress.py:181 -- \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:13,964\tINFO logging_progress.py:231 -- MapBatches(list_files): 32/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:13,964\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:13,965\tINFO logging_progress.py:231 -- Repartition: 32/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:13,965\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B object store; 32 rows output\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:13,965\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:13,967\tINFO logging_progress.py:231 -- MapBatches(DownloadActor): 31/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:13,969\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 1; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 96.0B object store; [0/32 objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:13,969\tINFO logging_progress.py:231 -- MapBatches(IterateExtractActor): 20/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:13,970\tINFO logging_progress.py:233 -- Tasks: 11; Actors: 10; Queued blocks: 0 (0.0B); Resources: 10.0 CPU, 56.0B memory, 88.0B object store; [0/31 objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:13,971\tINFO logging_progress.py:231 -- MapBatches(write): 19/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:13,971\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B memory, 16.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:13,971\tINFO logging_progress.py:192 -- ============================================\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[33m(raylet)\u001b[0m [2026-07-14 18:43:15,149 E 1787769 1787801] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_18-42-15_415223_1786482 is over 95% full, available space: 0.0767822 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:23,988\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:23,991\tINFO logging_progress.py:225 -- Total Progress: 31/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:23,993\tINFO logging_progress.py:227 -- Active & requested resources: 1/16 CPU, 8.0B/1.9TiB memory, 24.0B/93.1GiB object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:23,995\tINFO logging_progress.py:181 -- \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:23,996\tINFO logging_progress.py:231 -- MapBatches(list_files): 32/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:23,997\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:23,997\tINFO logging_progress.py:231 -- Repartition: 32/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:24,999\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 32 rows output\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:24,001\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:24,003\tINFO logging_progress.py:231 -- MapBatches(DownloadActor): 32/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:24,004\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B object store; [0/32 objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:24,004\tINFO logging_progress.py:231 -- MapBatches(IterateExtractActor): 31/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:24,005\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 1; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 8.0B memory, 8.0B object store; [0/32 objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:24,006\tINFO logging_progress.py:231 -- MapBatches(write): 31/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:24,006\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:24,007\tINFO logging_progress.py:192 -- ============================================\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 18:43:24,765\tINFO streaming_executor.py:327 -- ✔️ Dataset dataset_5_0 execution finished in 51.27 seconds\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Done: 32 items in 52.1s\n", + "Peak actors — download: 12 iterate: 10\n" + ] + } + ], + "source": [ + "ray.shutdown()\n", + "ray.init(num_cpus=16)\n", + "\n", + "ctr = _Counter.options(name=\"_ctr\").remote()\n", + "snapshots = []\n", + "_stop = threading.Event()\n", + "\n", + "def _monitor():\n", + " t0 = time.perf_counter()\n", + " total = ray.cluster_resources().get(\"CPU\", 16)\n", + " while not _stop.is_set():\n", + " snap = ray.get(ctr.snapshot.remote())\n", + " snapshots.append((\n", + " time.perf_counter() - t0,\n", + " snap[\"alloc\"],\n", + " snap[\"active\"],\n", + " total - ray.available_resources().get(\"CPU\", total),\n", + " ))\n", + " _stop.wait(1.0)\n", + "\n", + "t0 = time.perf_counter()\n", + "ds = (\n", + " ray.data.from_items([{\"seed\": 0}])\n", + " .map_batches(list_files, batch_size=1)\n", + " .repartition(NUM_FILES)\n", + " .map_batches(DownloadActor, batch_size=1, num_cpus=1,\n", + " compute=ActorPoolStrategy(min_size=1, max_size=NUM_FILES))\n", + " .map_batches(IterateExtractActor, batch_size=1, num_cpus=1,\n", + " compute=ActorPoolStrategy(min_size=1, max_size=NUM_FILES))\n", + " .map_batches(write, batch_size=1, num_cpus=0)\n", + ")\n", + "\n", + "monitor = threading.Thread(target=_monitor, daemon=True)\n", + "monitor.start()\n", + "results = ds.take_all()\n", + "_stop.set()\n", + "monitor.join(timeout=3)\n", + "\n", + "peaks = ray.get(ctr.snapshot.remote())\n", + "print(f\"Done: {len(results)} items in {time.perf_counter()-t0:.1f}s\")\n", + "print(f\"Peak actors — download: {peaks['peak_alloc'].get('dl',0)} iterate: {peaks['peak_alloc'].get('it',0)}\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "c04", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-14T18:43:24.800708Z", + "iopub.status.busy": "2026-07-14T18:43:24.800321Z", + "iopub.status.idle": "2026-07-14T18:43:24.811373Z", + "shell.execute_reply": "2026-07-14T18:43:24.810320Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Timeline (1s samples) ===\n", + " t dl_alloc dl_active it_alloc it_active cpu note\n", + " -------------------------------------------------------------------------------------\n", + " 0.2s 0 0 0 0 2 \n", + " 1.2s 1 0 1 0 11 \n", + " 2.2s 1 1 1 0 3 \n", + " 3.2s 2 2 1 0 4 \n", + " 4.2s 3 3 1 0 5 \n", + " 5.2s 5 5 1 0 7 \n", + " 6.2s 5 5 1 0 7 \n", + " 7.2s 5 5 1 0 7 \n", + " 8.2s 6 6 1 0 8 \n", + " 9.2s 7 6 1 0 8 \n", + " 10.3s 7 7 1 0 10 \n", + " 11.3s 7 7 1 0 10 \n", + " 12.3s 9 9 1 1 12 <- iterate FIRST task (dl=9, shared stolen=5)\n", + " 13.3s 9 9 1 1 13 \n", + " 14.3s 11 11 1 1 14 \n", + " 15.3s 11 11 2 2 15 \n", + " 16.3s 12 12 2 2 15 <- STARVED: iterate capped at reserved=4\n", + " 17.3s 12 12 3 2 15 <- STARVED: iterate capped at reserved=4\n", + " 18.3s 12 12 3 3 15 <- STARVED: iterate capped at reserved=4\n", + " 19.3s 12 12 3 3 15 <- STARVED: iterate capped at reserved=4\n", + " 20.3s 12 12 3 3 0 <- STARVED: iterate capped at reserved=4\n", + " 21.4s 12 12 3 3 0 <- STARVED: iterate capped at reserved=4\n", + " 22.4s 12 12 4 4 0 <- STARVED: iterate capped at reserved=4\n", + " 23.4s 12 12 4 4 0 <- STARVED: iterate capped at reserved=4\n", + " 24.4s 12 11 4 4 0 <- STARVED: iterate capped at reserved=4\n", + " 25.4s 12 12 4 4 0 <- STARVED: iterate capped at reserved=4\n", + " 26.4s 12 12 4 4 0 <- STARVED: iterate capped at reserved=4\n", + " 27.4s 12 12 4 4 0 <- STARVED: iterate capped at reserved=4\n", + " 28.4s 12 12 4 4 0 <- STARVED: iterate capped at reserved=4\n", + " 29.4s 12 12 4 4 0 <- STARVED: iterate capped at reserved=4\n", + " 30.4s 12 12 4 4 0 <- STARVED: iterate capped at reserved=4\n", + " 31.4s 12 12 4 4 0 <- STARVED: iterate capped at reserved=4\n", + " 32.5s 10 10 4 4 15 \n", + " 33.5s 9 9 4 4 14 \n", + " 34.5s 6 5 5 5 12 \n", + " 35.5s 4 3 7 6 11 \n", + " 36.5s 3 3 8 8 13 \n", + " 37.5s 3 2 8 8 13 \n", + " 38.5s 2 2 10 9 12 \n", + " 39.5s 2 1 10 10 12 \n", + " 40.5s 1 1 10 10 11 \n", + " 41.5s 1 1 10 10 11 \n", + " 42.5s 0 0 8 7 8 \n", + " 43.5s 0 0 6 6 6 \n", + " 44.6s 0 0 5 4 5 \n", + " 45.6s 0 0 2 1 2 \n", + " 46.6s 0 0 1 1 1 \n", + " 47.6s 0 0 1 1 1 \n", + " 48.6s 0 0 1 1 1 \n", + " 49.6s 0 0 1 1 1 \n", + " 50.6s 0 0 1 1 1 \n", + "\n", + "Download peak: 12 actors (exhausts shared when >= 12)\n", + "Iterate during starvation: 4 actors (reserved=4, could use 12 without stealing)\n", + "Throughput loss: 2.4 vs 0.8 files/sec => 3x slower\n", + "\n", + "Bandwidth saturation: 12 download actors x 10s = 1.2 files/sec (same as 1 actor x 0.83s = 1.2 files/sec)\n", + "=> 12 actors wasted for zero throughput gain, starving Iterate\n" + ] + } + ], + "source": [ + "# Budget constants (16 CPUs, ratio=0.5, 2 ops)\n", + "RESERVED = 4\n", + "SHARED = 8\n", + "STARVED_AT = RESERVED + SHARED # download actors needed to exhaust shared pool = 12\n", + "\n", + "print(\"=== Timeline (1s samples) ===\")\n", + "print(f\" {'t':>5} {'dl_alloc':>8} {'dl_active':>9} {'it_alloc':>8} {'it_active':>9} {'cpu':>5} note\")\n", + "print(\" \" + \"-\"*85)\n", + "\n", + "it_started = False\n", + "for ts, alloc, active, cpu in snapshots:\n", + " dl = alloc.get(\"dl\", 0)\n", + " it = alloc.get(\"it\", 0)\n", + " dl_t = active.get(\"dl\", 0)\n", + " it_t = active.get(\"it\", 0)\n", + "\n", + " note = \"\"\n", + " if it == 0 and dl > 0:\n", + " note = \"<- iterate: 0 input\"\n", + " elif not it_started and it_t > 0:\n", + " it_started = True\n", + " stolen = max(0, dl - RESERVED)\n", + " note = f\"<- iterate FIRST task (dl={dl}, shared stolen={stolen})\"\n", + " elif dl >= STARVED_AT and it <= RESERVED:\n", + " note = f\"<- STARVED: iterate capped at reserved={RESERVED}\"\n", + "\n", + " print(f\" {ts:5.1f}s {dl:>8d} {dl_t:>9d} {it:>8d} {it_t:>9d} {cpu:>4.0f} {note}\")\n", + "\n", + "print()\n", + "\n", + "# Summary\n", + "peak_dl = max((s[1].get(\"dl\", 0) for s in snapshots), default=0)\n", + "it_at_starvation = [s[1].get(\"it\", 0) for s in snapshots if s[1].get(\"dl\", 0) >= STARVED_AT]\n", + "peak_it_starved = max(it_at_starvation, default=0)\n", + "\n", + "print(f\"Download peak: {peak_dl} actors (exhausts shared when >= {STARVED_AT})\")\n", + "print(f\"Iterate during starvation: {peak_it_starved} actors (reserved={RESERVED}, could use {STARVED_AT} without stealing)\")\n", + "print(f\"Throughput loss: {STARVED_AT/ITERATE_DELAY:.1f} vs {peak_it_starved/ITERATE_DELAY:.1f} files/sec\"\n", + " f\" => {STARVED_AT/max(1,peak_it_starved):.0f}x slower\")\n", + "print()\n", + "print(f\"Bandwidth saturation: {peak_dl} download actors x {DOWNLOAD_DELAY:.0f}s\"\n", + " f\" = {peak_dl/DOWNLOAD_DELAY:.1f} files/sec\"\n", + " f\" (same as 1 actor x {DOWNLOAD_DELAY_SOLO:.2f}s = {1/DOWNLOAD_DELAY_SOLO:.1f} files/sec)\")\n", + "print(f\"=> {peak_dl} actors wasted for zero throughput gain, starving Iterate\")\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.11" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From f82450c1d47c54afebaf7c5aaf840288e7a7125d Mon Sep 17 00:00:00 2001 From: Weijia Chen Date: Tue, 14 Jul 2026 21:59:01 +0000 Subject: [PATCH 5/6] repro download --- reservation_ratio_test.ipynb | 851 +++++++++++++++++++++++------------ 1 file changed, 571 insertions(+), 280 deletions(-) diff --git a/reservation_ratio_test.ipynb b/reservation_ratio_test.ipynb index 22b923d8cd..e0b854b2db 100644 --- a/reservation_ratio_test.ipynb +++ b/reservation_ratio_test.ipynb @@ -6,10 +6,10 @@ "id": "c00", "metadata": { "execution": { - "iopub.execute_input": "2026-07-14T18:42:13.294047Z", - "iopub.status.busy": "2026-07-14T18:42:13.293687Z", - "iopub.status.idle": "2026-07-14T18:42:15.146250Z", - "shell.execute_reply": "2026-07-14T18:42:15.143234Z" + "iopub.execute_input": "2026-07-14T21:51:24.430727Z", + "iopub.status.busy": "2026-07-14T21:51:24.430449Z", + "iopub.status.idle": "2026-07-14T21:51:26.398913Z", + "shell.execute_reply": "2026-07-14T21:51:26.395811Z" } }, "outputs": [ @@ -22,19 +22,26 @@ } ], "source": [ - "# Repro: Download steals shared CPU pool, starving Iterate|Extract\n", + "# Ray Data Fair Scheduler — Shared Pool Starvation Repro\n", "#\n", - "# Pipeline: list_files (instant) -> Download (ActorPool) -> Iterate (ActorPool) -> write\n", + "# Pipeline:\n", + "# instant_source (0s) -> SlowActor (15s) -> SlowerActor (10s) -> fast_sink (0s)\n", "#\n", - "# Budget: 16 CPUs, reservation_ratio=0.5, 2 eligible ops\n", - "# reserved/op = 4 CPUs | shared pool = 8 CPUs\n", - "# Download ramps to 12 actors before producing any output -> exhausts shared pool\n", - "# Iterate starts with 0 input and can never exceed its reserved 4 CPUs\n", + "# Issue:\n", + "# instant_source finishes immediately. All 32 items queue for SlowActor at once.\n", + "# Autoscaler ramps SlowActor every few ms (util=2.0 >= 1.75) before it produces\n", + "# any output. After ~12s the shared CPU pool is fully exhausted by SlowActor.\n", + "# SlowerActor starts with 0 input until t~15s. By then SlowActor holds all shared\n", + "# CPUs, and SlowerActor is capped at its reserved allocation only.\n", "#\n", - "# Bandwidth saturation (Praateek's \"worst part\"):\n", - "# Node egress is fixed. With N download actors, each gets 1/N bandwidth.\n", - "# 12 actors x 10s = 1 actor x 0.83s = same 1.2 files/sec throughput.\n", - "# Extra actors provide zero throughput gain but steal Iterate's shared budget.\n", + "# Even though SlowerActor is the true bottleneck (highest per-actor latency when\n", + "# capped at 4 actors), util >= 1.75 passes Gate 1 but Gate 3 blocks scale-up:\n", + "# budget = reserved = 4 CPUs => 3x throughput loss on the critical path.\n", + "#\n", + "# Budget (16 CPUs, reservation_ratio=0.5, 2 eligible ActorPool ops):\n", + "# reserved/op = 4 | shared = 8\n", + "# SlowActor steals shared when it exceeds 4 actors (reserved)\n", + "# At 12 actors: shared fully exhausted -> SlowerActor capped at 4\n", "\n", "import time, threading, collections\n", "import ray, ray.data\n", @@ -49,10 +56,10 @@ "id": "c01", "metadata": { "execution": { - "iopub.execute_input": "2026-07-14T18:42:15.154020Z", - "iopub.status.busy": "2026-07-14T18:42:15.153609Z", - "iopub.status.idle": "2026-07-14T18:42:15.160212Z", - "shell.execute_reply": "2026-07-14T18:42:15.158293Z" + "iopub.execute_input": "2026-07-14T21:51:26.405223Z", + "iopub.status.busy": "2026-07-14T21:51:26.404858Z", + "iopub.status.idle": "2026-07-14T21:51:26.410669Z", + "shell.execute_reply": "2026-07-14T21:51:26.408793Z" } }, "outputs": [ @@ -60,29 +67,25 @@ "name": "stdout", "output_type": "stream", "text": [ - "Download: 12 actors x 10s = 1.2 files/sec\n", - " 1 actor x 0.83s = 1.2 files/sec (same throughput!)\n", - "Iterate starved (4 actors): 0.8 files/sec\n", - "Iterate potential(12 actors): 2.4 files/sec (3x loss from starvation)\n" + "SlowerActor if NOT starved: 12 actors / 10s = 1.20 files/sec\n", + "SlowerActor when starved : 4 actors / 10s = 0.40 files/sec\n", + "=> 3x throughput loss on the critical path\n" ] } ], "source": [ - "NUM_FILES = 32\n", - "\n", - "# Bandwidth saturation model: simulate peak (12 actors sharing node egress)\n", - "# 1 actor alone: DOWNLOAD_DELAY_SOLO = 0.83s => 1.2 files/sec\n", - "# 12 actors peak: each takes 12 x 0.83 = 10s => still 1.2 files/sec (same!)\n", - "DOWNLOAD_DELAY_SOLO = 10.0 / 12 # ~0.83s with full bandwidth\n", - "DOWNLOAD_PEAK = 12 # actors that exhaust shared pool (reserved=4 + shared=8)\n", - "DOWNLOAD_DELAY = DOWNLOAD_DELAY_SOLO * DOWNLOAD_PEAK # 10s (saturated case)\n", + "NUM_FILES = 32\n", + "SLOW_DELAY = 15.0 # SlowActor: 15s/item; with 32 tasks, util=32/12=2.67>=1.75 all the way to budget cap\n", + "SLOWER_DELAY = 10.0 # SlowerActor: true bottleneck, starved at reserved CPUs only\n", "\n", - "ITERATE_DELAY = 5.0 # per-item work; 4 reserved actors => 0.8 files/sec (vs 2.4 with 12)\n", + "# Budget (16 CPUs, ratio=0.5, 2 ops):\n", + "RESERVED = 4 # CPUs per op\n", + "SHARED = 8 # shared pool\n", + "STARVED_AT = RESERVED + SHARED # slow actors needed to exhaust shared = 12\n", "\n", - "print(f\"Download: {DOWNLOAD_PEAK} actors x {DOWNLOAD_DELAY:.0f}s = {DOWNLOAD_PEAK/DOWNLOAD_DELAY:.1f} files/sec\")\n", - "print(f\" 1 actor x {DOWNLOAD_DELAY_SOLO:.2f}s = {1/DOWNLOAD_DELAY_SOLO:.1f} files/sec (same throughput!)\")\n", - "print(f\"Iterate starved (4 actors): {4/ITERATE_DELAY:.1f} files/sec\")\n", - "print(f\"Iterate potential(12 actors): {12/ITERATE_DELAY:.1f} files/sec ({12//4}x loss from starvation)\")\n" + "print(f\"SlowerActor if NOT starved: {STARVED_AT} actors / {SLOWER_DELAY:.0f}s = {STARVED_AT/SLOWER_DELAY:.2f} files/sec\")\n", + "print(f\"SlowerActor when starved : {RESERVED} actors / {SLOWER_DELAY:.0f}s = {RESERVED/SLOWER_DELAY:.2f} files/sec\")\n", + "print(f\"=> {STARVED_AT//RESERVED}x throughput loss on the critical path\")\n" ] }, { @@ -91,10 +94,10 @@ "id": "c02", "metadata": { "execution": { - "iopub.execute_input": "2026-07-14T18:42:15.164574Z", - "iopub.status.busy": "2026-07-14T18:42:15.164339Z", - "iopub.status.idle": "2026-07-14T18:42:15.173360Z", - "shell.execute_reply": "2026-07-14T18:42:15.171829Z" + "iopub.execute_input": "2026-07-14T21:51:26.414628Z", + "iopub.status.busy": "2026-07-14T21:51:26.414441Z", + "iopub.status.idle": "2026-07-14T21:51:26.423500Z", + "shell.execute_reply": "2026-07-14T21:51:26.421497Z" } }, "outputs": [], @@ -104,8 +107,8 @@ "@_ray.remote(num_cpus=0)\n", "class _Counter:\n", " def __init__(self):\n", - " self._alloc = collections.defaultdict(int)\n", - " self._active = collections.defaultdict(int)\n", + " self._alloc = collections.defaultdict(int)\n", + " self._active = collections.defaultdict(int)\n", " self._peak_alloc = collections.defaultdict(int)\n", " self._peak_active = collections.defaultdict(int)\n", " def alloc(self, s):\n", @@ -119,48 +122,44 @@ " def exit(self, s):\n", " self._active[s] = max(0, self._active[s] - 1)\n", " def snapshot(self):\n", - " return {\n", - " \"alloc\": dict(self._alloc),\n", - " \"active\": dict(self._active),\n", - " \"peak_alloc\": dict(self._peak_alloc),\n", - " \"peak_active\": dict(self._peak_active),\n", - " }\n", + " return {\"alloc\": dict(self._alloc), \"active\": dict(self._active),\n", + " \"peak_alloc\": dict(self._peak_alloc), \"peak_active\": dict(self._peak_active)}\n", "\n", - "def list_files(batch):\n", - " return {\"file_id\": list(range(NUM_FILES))}\n", + "def instant_source(batch):\n", + " return {\"item_id\": list(range(NUM_FILES))}\n", "\n", - "def write(batch):\n", + "def fast_sink(batch):\n", " return batch\n", "\n", - "class DownloadActor:\n", + "class SlowActor:\n", " def __init__(self):\n", - " _ray.get_actor(\"_ctr\").alloc.remote(\"dl\")\n", + " _ray.get_actor(\"_ctr\").alloc.remote(\"slow\")\n", " def __del__(self):\n", - " try: _ray.get_actor(\"_ctr\").dealloc.remote(\"dl\")\n", + " try: _ray.get_actor(\"_ctr\").dealloc.remote(\"slow\")\n", " except Exception: pass\n", " def __call__(self, batch):\n", " ctr = _ray.get_actor(\"_ctr\")\n", - " ctr.enter.remote(\"dl\")\n", + " ctr.enter.remote(\"slow\")\n", " try:\n", - " time.sleep(DOWNLOAD_DELAY)\n", + " time.sleep(SLOW_DELAY)\n", " return batch\n", " finally:\n", - " ctr.exit.remote(\"dl\")\n", + " ctr.exit.remote(\"slow\")\n", "\n", - "class IterateExtractActor:\n", + "class SlowerActor:\n", " def __init__(self):\n", - " _ray.get_actor(\"_ctr\").alloc.remote(\"it\")\n", + " _ray.get_actor(\"_ctr\").alloc.remote(\"slower\")\n", " def __del__(self):\n", - " try: _ray.get_actor(\"_ctr\").dealloc.remote(\"it\")\n", + " try: _ray.get_actor(\"_ctr\").dealloc.remote(\"slower\")\n", " except Exception: pass\n", " def __call__(self, batch):\n", " ctr = _ray.get_actor(\"_ctr\")\n", - " ctr.enter.remote(\"it\")\n", + " ctr.enter.remote(\"slower\")\n", " try:\n", - " time.sleep(ITERATE_DELAY)\n", + " time.sleep(SLOWER_DELAY)\n", " return batch\n", " finally:\n", - " ctr.exit.remote(\"it\")\n" + " ctr.exit.remote(\"slower\")\n" ] }, { @@ -169,10 +168,10 @@ "id": "c03", "metadata": { "execution": { - "iopub.execute_input": "2026-07-14T18:42:15.177939Z", - "iopub.status.busy": "2026-07-14T18:42:15.177750Z", - "iopub.status.idle": "2026-07-14T18:43:24.794726Z", - "shell.execute_reply": "2026-07-14T18:43:24.792511Z" + "iopub.execute_input": "2026-07-14T21:51:26.426647Z", + "iopub.status.busy": "2026-07-14T21:51:26.426506Z", + "iopub.status.idle": "2026-07-14T21:52:58.267915Z", + "shell.execute_reply": "2026-07-14T21:52:58.265146Z" } }, "outputs": [ @@ -180,402 +179,402 @@ "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:31,156\tINFO worker.py:2015 -- Started a local Ray instance. View the dashboard at \u001b[1m\u001b[32mhttp://127.0.0.1:8269 \u001b[39m\u001b[22m\n" + "2026-07-14 21:51:40,178\tINFO worker.py:2015 -- Started a local Ray instance. View the dashboard at \u001b[1m\u001b[32mhttp://127.0.0.1:8269 \u001b[39m\u001b[22m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:33,493\tINFO streaming_executor.py:193 -- Starting execution of Dataset dataset_5_0. Full logs are in /tmp/ray/session_2026-07-14_18-42-15_415223_1786482/logs/ray-data\n" + "2026-07-14 21:51:42,573\tINFO streaming_executor.py:193 -- Starting execution of Dataset dataset_5_0. Full logs are in /tmp/ray/session_2026-07-14_21-51-26_677860_2186124/logs/ray-data\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:33,494\tINFO streaming_executor.py:194 -- Execution plan of Dataset dataset_5_0: InputDataBuffer[Input] -> TaskPoolMapOperator[MapBatches(list_files)] -> AllToAllOperator[Repartition] -> ActorPoolMapOperator[MapBatches(DownloadActor)] -> ActorPoolMapOperator[MapBatches(IterateExtractActor)] -> TaskPoolMapOperator[MapBatches(write)]\n" + "2026-07-14 21:51:42,575\tINFO streaming_executor.py:194 -- Execution plan of Dataset dataset_5_0: InputDataBuffer[Input] -> TaskPoolMapOperator[MapBatches(instant_source)] -> AllToAllOperator[Repartition] -> ActorPoolMapOperator[MapBatches(SlowActor)] -> ActorPoolMapOperator[MapBatches(SlowerActor)] -> TaskPoolMapOperator[MapBatches(fast_sink)]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "[2026-07-14 18:42:33,529 E 1786482 1786482] core_worker.cc:2149: Actor with class name: 'MapWorker(MapBatches(DownloadActor))' and ID: '35bc8bf4f5733602567622b601000000' has constructor arguments in the object store and max_restarts > 0. If the arguments in the object store go out of scope or are lost, the actor restart will fail. See https://github.com/ray-project/ray/issues/53727 for more details.\n", - "2026-07-14 18:42:33,555\tINFO __init__.py:56 -- Progress will be logged because stdout is a non-interactive terminal.\n" + "[2026-07-14 21:51:42,617 E 2186124 2186124] core_worker.cc:2149: Actor with class name: 'MapWorker(MapBatches(SlowActor))' and ID: 'd714c01c220de29caff2d43501000000' has constructor arguments in the object store and max_restarts > 0. If the arguments in the object store go out of scope or are lost, the actor restart will fail. See https://github.com/ray-project/ray/issues/53727 for more details.\n", + "2026-07-14 21:51:42,643\tINFO __init__.py:56 -- Progress will be logged because stdout is a non-interactive terminal.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:33,590\tWARNING resource_manager.py:766 -- Cluster resources are not enough to run any task from TaskPoolMapOperator[MapBatches(list_files)]. The job may hang forever unless the cluster scales up.\n" + "2026-07-14 21:51:42,682\tWARNING resource_manager.py:766 -- Cluster resources are not enough to run any task from TaskPoolMapOperator[MapBatches(instant_source)]. The job may hang forever unless the cluster scales up.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:33,712\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + "2026-07-14 21:51:42,807\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:33,713\tINFO logging_progress.py:225 -- Total Progress: 0/?\n" + "2026-07-14 21:51:42,809\tINFO logging_progress.py:225 -- Total Progress: 0/?\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:33,715\tINFO logging_progress.py:227 -- Active & requested resources: 0/0 CPU, 0.0B/0.0B object store (pending: 2 CPU)\n" + "2026-07-14 21:51:42,811\tINFO logging_progress.py:227 -- Active & requested resources: 0/0 CPU, 0.0B/0.0B object store (pending: 2 CPU)\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:33,716\tINFO logging_progress.py:181 -- \n" + "2026-07-14 21:51:42,812\tINFO logging_progress.py:181 -- \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:33,717\tINFO logging_progress.py:231 -- MapBatches(list_files): 0/1\n" + "2026-07-14 21:51:42,813\tINFO logging_progress.py:231 -- MapBatches(instant_source): 0/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:33,718\tINFO logging_progress.py:233 -- Tasks: 1 [backpressured:tasks(ResourceBudget)]; Actors: 0; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store\n" + "2026-07-14 21:51:42,814\tINFO logging_progress.py:233 -- Tasks: 1 [backpressured:tasks(ResourceBudget)]; Actors: 0; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:33,719\tINFO logging_progress.py:231 -- Repartition: 0/1\n" + "2026-07-14 21:51:42,815\tINFO logging_progress.py:231 -- Repartition: 0/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:33,719\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n" + "2026-07-14 21:51:42,815\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:33,720\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n" + "2026-07-14 21:51:42,816\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:33,720\tINFO logging_progress.py:231 -- MapBatches(DownloadActor): 0/1\n" + "2026-07-14 21:51:42,816\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 0/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:33,720\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 1 (running=0, restarting=0, pending=1, active=0, idle=0, util=0.000, tasks_in_flight=0); Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n" + "2026-07-14 21:51:42,817\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 1 (running=0, restarting=0, pending=1, active=0, idle=0, util=0.000, tasks_in_flight=0); Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:33,721\tINFO logging_progress.py:231 -- MapBatches(IterateExtractActor): 0/1\n" + "2026-07-14 21:51:42,818\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 0/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:33,721\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 1 (running=0, restarting=0, pending=1, active=0, idle=0, util=0.000, tasks_in_flight=0); Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n" + "2026-07-14 21:51:42,818\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 1 (running=0, restarting=0, pending=1, active=0, idle=0, util=0.000, tasks_in_flight=0); Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:33,722\tINFO logging_progress.py:231 -- MapBatches(write): 0/1\n" + "2026-07-14 21:51:42,819\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 0/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:33,722\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + "2026-07-14 21:51:42,819\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:33,722\tINFO logging_progress.py:192 -- ============================================\n" + "2026-07-14 21:51:42,820\tINFO logging_progress.py:192 -- ============================================\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\u001b[33m(raylet)\u001b[0m [2026-07-14 18:42:35,063 E 1787769 1787801] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_18-42-15_415223_1786482 is over 95% full, available space: 0.0778694 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" + "\u001b[33m(raylet)\u001b[0m [2026-07-14 21:51:45,087 E 2187411 2187442] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_21-51-26_677860_2186124 is over 95% full, available space: 0.0276375 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:43,741\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + "2026-07-14 21:51:52,869\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:43,745\tINFO logging_progress.py:225 -- Total Progress: 0/?\n" + "2026-07-14 21:51:52,872\tINFO logging_progress.py:225 -- Total Progress: 0/?\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:43,746\tINFO logging_progress.py:227 -- Active & requested resources: 8/16 CPU, 256.0B/93.1GiB object store (pending: 2 CPU)\n" + "2026-07-14 21:51:52,874\tINFO logging_progress.py:227 -- Active & requested resources: 8/16 CPU, 256.0B/93.1GiB object store (pending: 2 CPU)\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:43,748\tINFO logging_progress.py:181 -- \n" + "2026-07-14 21:51:52,876\tINFO logging_progress.py:181 -- \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:43,749\tINFO logging_progress.py:231 -- MapBatches(list_files): 32/32\n" + "2026-07-14 21:51:52,877\tINFO logging_progress.py:231 -- MapBatches(instant_source): 32/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:43,750\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + "2026-07-14 21:51:52,878\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:43,750\tINFO logging_progress.py:231 -- Repartition: 32/32\n" + "2026-07-14 21:51:52,879\tINFO logging_progress.py:231 -- Repartition: 32/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:43,751\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 256.0B object store; 32 rows output\n" + "2026-07-14 21:51:52,880\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 256.0B object store; 32 rows output\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:43,752\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" + "2026-07-14 21:51:52,882\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:43,753\tINFO logging_progress.py:231 -- MapBatches(DownloadActor): 0/1\n" + "2026-07-14 21:51:52,882\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 0/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:43,753\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 9 (running=7, restarting=0, pending=2, active=7, idle=0, util=1.556, tasks_in_flight=14); Queued blocks: 18 (144.0B); Resources: 7.0 CPU, 0.0B object store; [0/14 objects local]\n" + "2026-07-14 21:51:52,884\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 9 (running=7, restarting=0, pending=2, active=7, idle=0, util=1.556, tasks_in_flight=14); Queued blocks: 18 (144.0B); Resources: 7.0 CPU, 0.0B object store; [0/14 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:43,754\tINFO logging_progress.py:231 -- MapBatches(IterateExtractActor): 0/1\n" + "2026-07-14 21:51:52,885\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 0/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:43,754\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 1; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store; [all objects local]\n" + "2026-07-14 21:51:52,885\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 1; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store; [all objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:43,754\tINFO logging_progress.py:231 -- MapBatches(write): 0/1\n" + "2026-07-14 21:51:52,886\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 0/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:43,754\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + "2026-07-14 21:51:52,887\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:43,754\tINFO logging_progress.py:192 -- ============================================\n" + "2026-07-14 21:51:52,888\tINFO logging_progress.py:192 -- ============================================\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\u001b[33m(raylet)\u001b[0m [2026-07-14 18:42:45,085 E 1787769 1787801] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_18-42-15_415223_1786482 is over 95% full, available space: 0.0775299 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" + "\u001b[33m(raylet)\u001b[0m [2026-07-14 21:51:55,109 E 2187411 2187442] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_21-51-26_677860_2186124 is over 95% full, available space: 0.0273285 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:53,788\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + "2026-07-14 21:52:02,891\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:53,791\tINFO logging_progress.py:225 -- Total Progress: 1/32\n" + "2026-07-14 21:52:02,894\tINFO logging_progress.py:225 -- Total Progress: 0/?\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:53,794\tINFO logging_progress.py:227 -- Active & requested resources: 15/16 CPU, 16.0B/1.9TiB memory, 376.0B/93.1GiB object store (pending: 1 CPU, 8.0B memory)\n" + "2026-07-14 21:52:02,896\tINFO logging_progress.py:227 -- Active & requested resources: 14/16 CPU, 352.0B/93.1GiB object store (pending: 1 CPU)\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:53,795\tINFO logging_progress.py:181 -- \n" + "2026-07-14 21:52:02,898\tINFO logging_progress.py:181 -- \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:53,796\tINFO logging_progress.py:231 -- MapBatches(list_files): 32/32\n" + "2026-07-14 21:52:02,899\tINFO logging_progress.py:231 -- MapBatches(instant_source): 32/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:53,797\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + "2026-07-14 21:52:02,900\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:53,797\tINFO logging_progress.py:231 -- Repartition: 32/32\n" + "2026-07-14 21:52:02,901\tINFO logging_progress.py:231 -- Repartition: 32/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:53,798\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 200.0B object store; 32 rows output\n" + "2026-07-14 21:52:02,901\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 216.0B object store; 32 rows output\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:53,799\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" + "2026-07-14 21:52:02,901\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:53,800\tINFO logging_progress.py:231 -- MapBatches(DownloadActor): 7/32\n" + "2026-07-14 21:52:02,902\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 5/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:53,801\tINFO logging_progress.py:233 -- Tasks: 24; Actors: 12; Queued blocks: 1 (8.0B); Resources: 12.0 CPU, 8.0B memory, 136.0B object store; [0/31 objects local]\n" + "2026-07-14 21:52:02,902\tINFO logging_progress.py:233 -- Tasks: 24; Actors: 12; Queued blocks: 3 (24.0B); Resources: 12.0 CPU, 136.0B object store; [0/29 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:53,802\tINFO logging_progress.py:231 -- MapBatches(IterateExtractActor): 2/32\n" + "2026-07-14 21:52:02,903\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 0/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:53,803\tINFO logging_progress.py:233 -- Tasks: 5; Actors: 4 (running=3, restarting=0, pending=1, active=3, idle=0, util=1.250, tasks_in_flight=5); Queued blocks: 0 (0.0B); Resources: 3.0 CPU, 32.0B object store; [0/7 objects local]\n" + "2026-07-14 21:52:02,904\tINFO logging_progress.py:233 -- Tasks: 4; Actors: 3 (running=2, restarting=0, pending=1, active=2, idle=0, util=1.333, tasks_in_flight=4); Queued blocks: 1 (8.0B); Resources: 2.0 CPU, 0.0B object store; [0/4 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:53,803\tINFO logging_progress.py:231 -- MapBatches(write): 1/32\n" + "2026-07-14 21:52:02,906\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 0/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:53,804\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B memory, 8.0B object store\n" + "2026-07-14 21:52:02,908\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:42:53,805\tINFO logging_progress.py:192 -- ============================================\n" + "2026-07-14 21:52:02,909\tINFO logging_progress.py:192 -- ============================================\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\u001b[33m(raylet)\u001b[0m [2026-07-14 18:42:55,107 E 1787769 1787801] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_18-42-15_415223_1786482 is over 95% full, available space: 0.0772705 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" + "\u001b[33m(raylet)\u001b[0m [2026-07-14 21:52:05,129 E 2187411 2187442] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_21-51-26_677860_2186124 is over 95% full, available space: 0.027092 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:03,649\tWARNING issue_detector_manager.py:69 -- \n", + "2026-07-14 21:52:12,776\tWARNING issue_detector_manager.py:69 -- \n", "\n", - "Operator 'MapBatches(write)' uses 114.8MiB of memory per task on\n", + "Operator 'MapBatches(fast_sink)' uses 114.8MiB of memory per task on\n", "average, but Ray only requests 0.0B per task at the start of the\n", "pipeline.\n", "\n", @@ -593,372 +592,644 @@ "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:03,652\tWARNING issue_detector_manager.py:96 -- Found 1 issues. To disable issue detection, run DataContext.get_current().issue_detectors_config.detectors = [].\n" + "2026-07-14 21:52:12,778\tWARNING issue_detector_manager.py:96 -- Found 1 issues. To disable issue detection, run DataContext.get_current().issue_detectors_config.detectors = [].\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:12,995\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:12,997\tINFO logging_progress.py:225 -- Total Progress: 2/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:12,999\tINFO logging_progress.py:227 -- Active & requested resources: 16/16 CPU, 376.0B/93.1GiB object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:13,000\tINFO logging_progress.py:181 -- \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:13,001\tINFO logging_progress.py:231 -- MapBatches(instant_source): 32/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:13,002\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:13,003\tINFO logging_progress.py:231 -- Repartition: 32/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:13,003\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 160.0B object store; 32 rows output\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:13,004\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:13,004\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 12/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:13,004\tINFO logging_progress.py:233 -- Tasks: 20; Actors: 12; Queued blocks: 0 (0.0B); Resources: 12.0 CPU, 176.0B object store; [0/32 objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:13,005\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 2/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:13,005\tINFO logging_progress.py:233 -- Tasks: 8; Actors: 4; Queued blocks: 2 (16.0B); Resources: 4.0 CPU, 32.0B object store; [0/10 objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:13,006\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 2/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:13,006\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:13,007\tINFO logging_progress.py:192 -- ============================================\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:03,870\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + "\u001b[33m(raylet)\u001b[0m [2026-07-14 21:52:15,152 E 2187411 2187442] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_21-51-26_677860_2186124 is over 95% full, available space: 0.0269051 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:03,872\tINFO logging_progress.py:225 -- Total Progress: 8/32\n" + "2026-07-14 21:52:23,091\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:03,874\tINFO logging_progress.py:227 -- Active & requested resources: 16/16 CPU, 24.0B/1.9TiB memory, 336.0B/93.1GiB object store\n" + "2026-07-14 21:52:23,093\tINFO logging_progress.py:225 -- Total Progress: 6/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:03,876\tINFO logging_progress.py:181 -- \n" + "2026-07-14 21:52:23,095\tINFO logging_progress.py:227 -- Active & requested resources: 16/16 CPU, 344.0B/93.1GiB object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:03,876\tINFO logging_progress.py:231 -- MapBatches(list_files): 32/32\n" + "2026-07-14 21:52:23,097\tINFO logging_progress.py:181 -- \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:03,877\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + "2026-07-14 21:52:23,098\tINFO logging_progress.py:231 -- MapBatches(instant_source): 32/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:03,877\tINFO logging_progress.py:231 -- Repartition: 32/32\n" + "2026-07-14 21:52:23,100\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:03,878\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 104.0B object store; 32 rows output\n" + "2026-07-14 21:52:23,101\tINFO logging_progress.py:231 -- Repartition: 32/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:03,880\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" + "2026-07-14 21:52:23,102\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 104.0B object store; 32 rows output\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:03,881\tINFO logging_progress.py:231 -- MapBatches(DownloadActor): 19/32\n" + "2026-07-14 21:52:23,102\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:03,884\tINFO logging_progress.py:233 -- Tasks: 13; Actors: 12; Queued blocks: 0 (0.0B); Resources: 12.0 CPU, 8.0B memory, 176.0B object store; [0/32 objects local]\n" + "2026-07-14 21:52:23,103\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 19/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:03,885\tINFO logging_progress.py:231 -- MapBatches(IterateExtractActor): 9/32\n" + "2026-07-14 21:52:23,104\tINFO logging_progress.py:233 -- Tasks: 13; Actors: 12; Queued blocks: 0 (0.0B); Resources: 12.0 CPU, 200.0B object store; [0/32 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:03,886\tINFO logging_progress.py:233 -- Tasks: 8; Actors: 4; Queued blocks: 2 (16.0B); Resources: 4.0 CPU, 8.0B memory, 40.0B object store; [0/17 objects local]\n" + "2026-07-14 21:52:23,104\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 6/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:03,886\tINFO logging_progress.py:231 -- MapBatches(write): 8/32\n" + "2026-07-14 21:52:23,105\tINFO logging_progress.py:233 -- Tasks: 8; Actors: 4; Queued blocks: 5 (40.0B); Resources: 4.0 CPU, 32.0B object store; [0/14 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:03,887\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B memory, 16.0B object store\n" + "2026-07-14 21:52:23,105\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 6/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:03,888\tINFO logging_progress.py:192 -- ============================================\n" + "2026-07-14 21:52:23,106\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\u001b[33m(raylet)\u001b[0m [2026-07-14 18:43:05,128 E 1787769 1787801] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_18-42-15_415223_1786482 is over 95% full, available space: 0.0770836 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" + "2026-07-14 21:52:23,106\tINFO logging_progress.py:192 -- ============================================\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:13,959\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + "\u001b[33m(raylet)\u001b[0m [2026-07-14 21:52:25,174 E 2187411 2187442] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_21-51-26_677860_2186124 is over 95% full, available space: 0.0267105 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:13,961\tINFO logging_progress.py:225 -- Total Progress: 19/32\n" + "2026-07-14 21:52:33,170\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:13,963\tINFO logging_progress.py:227 -- Active & requested resources: 11/16 CPU, 56.0B/1.9TiB memory, 200.0B/93.1GiB object store\n" + "2026-07-14 21:52:33,173\tINFO logging_progress.py:225 -- Total Progress: 9/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:13,964\tINFO logging_progress.py:181 -- \n" + "2026-07-14 21:52:33,175\tINFO logging_progress.py:227 -- Active & requested resources: 12/16 CPU, 48.0B/1.9TiB memory, 296.0B/93.1GiB object store (pending: 2 CPU, 16.0B memory)\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:13,964\tINFO logging_progress.py:231 -- MapBatches(list_files): 32/32\n" + "2026-07-14 21:52:33,177\tINFO logging_progress.py:181 -- \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:13,964\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + "2026-07-14 21:52:33,178\tINFO logging_progress.py:231 -- MapBatches(instant_source): 32/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:13,965\tINFO logging_progress.py:231 -- Repartition: 32/32\n" + "2026-07-14 21:52:33,179\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:13,965\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B object store; 32 rows output\n" + "2026-07-14 21:52:33,180\tINFO logging_progress.py:231 -- Repartition: 32/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:13,965\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" + "2026-07-14 21:52:33,180\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 24.0B object store; 32 rows output\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:13,967\tINFO logging_progress.py:231 -- MapBatches(DownloadActor): 31/32\n" + "2026-07-14 21:52:33,181\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:13,969\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 1; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 96.0B object store; [0/32 objects local]\n" + "2026-07-14 21:52:33,181\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 29/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:13,969\tINFO logging_progress.py:231 -- MapBatches(IterateExtractActor): 20/32\n" + "2026-07-14 21:52:33,182\tINFO logging_progress.py:233 -- Tasks: 3; Actors: 3; Queued blocks: 0 (0.0B); Resources: 3.0 CPU, 176.0B object store; [0/32 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:13,970\tINFO logging_progress.py:233 -- Tasks: 11; Actors: 10; Queued blocks: 0 (0.0B); Resources: 10.0 CPU, 56.0B memory, 88.0B object store; [0/31 objects local]\n" + "2026-07-14 21:52:33,183\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 10/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:13,971\tINFO logging_progress.py:231 -- MapBatches(write): 19/32\n" + "2026-07-14 21:52:33,184\tINFO logging_progress.py:233 -- Tasks: 18; Actors: 11 (running=9, restarting=0, pending=2, active=9, idle=0, util=1.636, tasks_in_flight=18); Queued blocks: 1 (8.0B); Resources: 9.0 CPU, 40.0B memory, 80.0B object store; [0/28 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:13,971\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B memory, 16.0B object store\n" + "2026-07-14 21:52:33,185\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 9/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:13,971\tINFO logging_progress.py:192 -- ============================================\n" + "2026-07-14 21:52:33,185\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B memory, 16.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\u001b[33m(raylet)\u001b[0m [2026-07-14 18:43:15,149 E 1787769 1787801] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_18-42-15_415223_1786482 is over 95% full, available space: 0.0767822 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" + "2026-07-14 21:52:33,186\tINFO logging_progress.py:192 -- ============================================\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:23,988\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + "\u001b[33m(raylet)\u001b[0m [2026-07-14 21:52:35,196 E 2187411 2187442] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_21-51-26_677860_2186124 is over 95% full, available space: 0.0263901 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:42,813\tWARNING issue_detector_manager.py:69 -- \n", + "\n", + "Operator 'MapBatches(fast_sink)' uses 108.4MiB of memory per task on\n", + "average, but Ray only requests 0.0B per task at the start of the\n", + "pipeline.\n", + "\n", + "To avoid out-of-memory errors, consider setting `memory=108.4MiB` in\n", + "the appropriate function or method call. (This might be unnecessary if\n", + "the number of concurrent tasks is low.)\n", + "\n", + "To change the frequency of this warning, set\n", + "`DataContext.get_current().issue_detectors_config.high_memory_detector_config.detection_time_interval_s`,\n", + "or disable the warning by setting value to -1. (current value: 30)\n", + "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:23,991\tINFO logging_progress.py:225 -- Total Progress: 31/32\n" + "2026-07-14 21:52:42,815\tWARNING issue_detector_manager.py:96 -- Found 1 issues. To disable issue detection, run DataContext.get_current().issue_detectors_config.detectors = [].\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:23,993\tINFO logging_progress.py:227 -- Active & requested resources: 1/16 CPU, 8.0B/1.9TiB memory, 24.0B/93.1GiB object store\n" + "2026-07-14 21:52:43,249\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:23,995\tINFO logging_progress.py:181 -- \n" + "2026-07-14 21:52:43,252\tINFO logging_progress.py:225 -- Total Progress: 19/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:23,996\tINFO logging_progress.py:231 -- MapBatches(list_files): 32/32\n" + "2026-07-14 21:52:43,254\tINFO logging_progress.py:227 -- Active & requested resources: 11/16 CPU, 56.0B/1.9TiB memory, 200.0B/93.1GiB object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:23,997\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + "2026-07-14 21:52:43,255\tINFO logging_progress.py:181 -- \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:23,997\tINFO logging_progress.py:231 -- Repartition: 32/32\n" + "2026-07-14 21:52:43,257\tINFO logging_progress.py:231 -- MapBatches(instant_source): 32/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:24,999\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 32 rows output\n" + "2026-07-14 21:52:43,259\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:24,001\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" + "2026-07-14 21:52:43,261\tINFO logging_progress.py:231 -- Repartition: 32/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:24,003\tINFO logging_progress.py:231 -- MapBatches(DownloadActor): 32/32\n" + "2026-07-14 21:52:43,262\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 32 rows output\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:24,004\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B object store; [0/32 objects local]\n" + "2026-07-14 21:52:43,263\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:24,004\tINFO logging_progress.py:231 -- MapBatches(IterateExtractActor): 31/32\n" + "2026-07-14 21:52:43,264\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 32/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:24,005\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 1; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 8.0B memory, 8.0B object store; [0/32 objects local]\n" + "2026-07-14 21:52:43,265\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 104.0B object store; [0/32 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:24,006\tINFO logging_progress.py:231 -- MapBatches(write): 31/32\n" + "2026-07-14 21:52:43,265\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 19/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:24,006\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B object store\n" + "2026-07-14 21:52:43,266\tINFO logging_progress.py:233 -- Tasks: 13; Actors: 11; Queued blocks: 0 (0.0B); Resources: 11.0 CPU, 56.0B memory, 88.0B object store; [0/32 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:24,007\tINFO logging_progress.py:192 -- ============================================\n" + "2026-07-14 21:52:43,267\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 19/32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 18:43:24,765\tINFO streaming_executor.py:327 -- ✔️ Dataset dataset_5_0 execution finished in 51.27 seconds\n" + "2026-07-14 21:52:43,267\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:43,268\tINFO logging_progress.py:192 -- ============================================\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[33m(raylet)\u001b[0m [2026-07-14 21:52:45,219 E 2187411 2187442] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_21-51-26_677860_2186124 is over 95% full, available space: 0.0261765 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:53,348\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:53,351\tINFO logging_progress.py:225 -- Total Progress: 30/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:53,353\tINFO logging_progress.py:227 -- Active & requested resources: 2/16 CPU, 8.0B/1.9TiB memory, 40.0B/93.1GiB object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:53,354\tINFO logging_progress.py:181 -- \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:53,355\tINFO logging_progress.py:231 -- MapBatches(instant_source): 32/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:53,356\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:53,357\tINFO logging_progress.py:231 -- Repartition: 32/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:53,357\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 32 rows output\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:53,358\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:53,359\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 32/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:53,360\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 16.0B object store; [0/32 objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:53,360\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 30/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:53,361\tINFO logging_progress.py:233 -- Tasks: 2; Actors: 2; Queued blocks: 0 (0.0B); Resources: 2.0 CPU, 8.0B memory, 16.0B object store; [0/32 objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:53,362\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 30/32\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:53,362\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:53,363\tINFO logging_progress.py:192 -- ============================================\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[33m(raylet)\u001b[0m [2026-07-14 21:52:55,240 E 2187411 2187442] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_21-51-26_677860_2186124 is over 95% full, available space: 0.0260582 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 21:52:58,244\tINFO streaming_executor.py:327 -- ✔️ Dataset dataset_5_0 execution finished in 75.67 seconds\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Done: 32 items in 52.1s\n", - "Peak actors — download: 12 iterate: 10\n" + "Done: 32 items in 76.5s\n", + "Peak actors — slow: 12 slower: 11\n" ] } ], @@ -986,13 +1257,13 @@ "t0 = time.perf_counter()\n", "ds = (\n", " ray.data.from_items([{\"seed\": 0}])\n", - " .map_batches(list_files, batch_size=1)\n", + " .map_batches(instant_source, batch_size=1)\n", " .repartition(NUM_FILES)\n", - " .map_batches(DownloadActor, batch_size=1, num_cpus=1,\n", + " .map_batches(SlowActor, batch_size=1, num_cpus=1,\n", " compute=ActorPoolStrategy(min_size=1, max_size=NUM_FILES))\n", - " .map_batches(IterateExtractActor, batch_size=1, num_cpus=1,\n", + " .map_batches(SlowerActor, batch_size=1, num_cpus=1,\n", " compute=ActorPoolStrategy(min_size=1, max_size=NUM_FILES))\n", - " .map_batches(write, batch_size=1, num_cpus=0)\n", + " .map_batches(fast_sink, batch_size=1, num_cpus=0)\n", ")\n", "\n", "monitor = threading.Thread(target=_monitor, daemon=True)\n", @@ -1003,7 +1274,7 @@ "\n", "peaks = ray.get(ctr.snapshot.remote())\n", "print(f\"Done: {len(results)} items in {time.perf_counter()-t0:.1f}s\")\n", - "print(f\"Peak actors — download: {peaks['peak_alloc'].get('dl',0)} iterate: {peaks['peak_alloc'].get('it',0)}\")\n" + "print(f\"Peak actors — slow: {peaks['peak_alloc'].get('slow',0)} slower: {peaks['peak_alloc'].get('slower',0)}\")\n" ] }, { @@ -1012,10 +1283,10 @@ "id": "c04", "metadata": { "execution": { - "iopub.execute_input": "2026-07-14T18:43:24.800708Z", - "iopub.status.busy": "2026-07-14T18:43:24.800321Z", - "iopub.status.idle": "2026-07-14T18:43:24.811373Z", - "shell.execute_reply": "2026-07-14T18:43:24.810320Z" + "iopub.execute_input": "2026-07-14T21:52:58.275549Z", + "iopub.status.busy": "2026-07-14T21:52:58.275151Z", + "iopub.status.idle": "2026-07-14T21:52:58.286702Z", + "shell.execute_reply": "2026-07-14T21:52:58.284536Z" } }, "outputs": [ @@ -1024,114 +1295,134 @@ "output_type": "stream", "text": [ "=== Timeline (1s samples) ===\n", - " t dl_alloc dl_active it_alloc it_active cpu note\n", - " -------------------------------------------------------------------------------------\n", - " 0.2s 0 0 0 0 2 \n", - " 1.2s 1 0 1 0 11 \n", - " 2.2s 1 1 1 0 3 \n", - " 3.2s 2 2 1 0 4 \n", - " 4.2s 3 3 1 0 5 \n", - " 5.2s 5 5 1 0 7 \n", - " 6.2s 5 5 1 0 7 \n", - " 7.2s 5 5 1 0 7 \n", - " 8.2s 6 6 1 0 8 \n", - " 9.2s 7 6 1 0 8 \n", - " 10.3s 7 7 1 0 10 \n", - " 11.3s 7 7 1 0 10 \n", - " 12.3s 9 9 1 1 12 <- iterate FIRST task (dl=9, shared stolen=5)\n", - " 13.3s 9 9 1 1 13 \n", - " 14.3s 11 11 1 1 14 \n", - " 15.3s 11 11 2 2 15 \n", - " 16.3s 12 12 2 2 15 <- STARVED: iterate capped at reserved=4\n", - " 17.3s 12 12 3 2 15 <- STARVED: iterate capped at reserved=4\n", - " 18.3s 12 12 3 3 15 <- STARVED: iterate capped at reserved=4\n", - " 19.3s 12 12 3 3 15 <- STARVED: iterate capped at reserved=4\n", - " 20.3s 12 12 3 3 0 <- STARVED: iterate capped at reserved=4\n", - " 21.4s 12 12 3 3 0 <- STARVED: iterate capped at reserved=4\n", - " 22.4s 12 12 4 4 0 <- STARVED: iterate capped at reserved=4\n", - " 23.4s 12 12 4 4 0 <- STARVED: iterate capped at reserved=4\n", - " 24.4s 12 11 4 4 0 <- STARVED: iterate capped at reserved=4\n", - " 25.4s 12 12 4 4 0 <- STARVED: iterate capped at reserved=4\n", - " 26.4s 12 12 4 4 0 <- STARVED: iterate capped at reserved=4\n", - " 27.4s 12 12 4 4 0 <- STARVED: iterate capped at reserved=4\n", - " 28.4s 12 12 4 4 0 <- STARVED: iterate capped at reserved=4\n", - " 29.4s 12 12 4 4 0 <- STARVED: iterate capped at reserved=4\n", - " 30.4s 12 12 4 4 0 <- STARVED: iterate capped at reserved=4\n", - " 31.4s 12 12 4 4 0 <- STARVED: iterate capped at reserved=4\n", - " 32.5s 10 10 4 4 15 \n", - " 33.5s 9 9 4 4 14 \n", - " 34.5s 6 5 5 5 12 \n", - " 35.5s 4 3 7 6 11 \n", - " 36.5s 3 3 8 8 13 \n", - " 37.5s 3 2 8 8 13 \n", - " 38.5s 2 2 10 9 12 \n", - " 39.5s 2 1 10 10 12 \n", - " 40.5s 1 1 10 10 11 \n", - " 41.5s 1 1 10 10 11 \n", - " 42.5s 0 0 8 7 8 \n", - " 43.5s 0 0 6 6 6 \n", - " 44.6s 0 0 5 4 5 \n", - " 45.6s 0 0 2 1 2 \n", - " 46.6s 0 0 1 1 1 \n", - " 47.6s 0 0 1 1 1 \n", - " 48.6s 0 0 1 1 1 \n", - " 49.6s 0 0 1 1 1 \n", - " 50.6s 0 0 1 1 1 \n", - "\n", - "Download peak: 12 actors (exhausts shared when >= 12)\n", - "Iterate during starvation: 4 actors (reserved=4, could use 12 without stealing)\n", - "Throughput loss: 2.4 vs 0.8 files/sec => 3x slower\n", + " t slow_alloc slow_active slower_alloc slower_active cpu note\n", + " ------------------------------------------------------------------------------------------\n", + " 0.2s 0 0 0 0 2 \n", + " 1.2s 1 0 1 0 0 \n", + " 2.2s 1 1 1 0 3 \n", + " 3.2s 2 2 1 0 4 \n", + " 4.2s 3 3 1 0 5 \n", + " 5.2s 5 4 1 0 6 \n", + " 6.2s 5 5 1 0 7 \n", + " 7.2s 6 6 1 0 8 \n", + " 8.3s 6 6 1 0 8 \n", + " 9.3s 7 7 1 0 9 \n", + " 10.3s 7 7 1 0 10 \n", + " 11.3s 8 8 1 0 10 \n", + " 12.3s 9 9 1 0 12 \n", + " 13.3s 11 9 1 0 12 \n", + " 14.3s 11 11 1 0 13 \n", + " 15.3s 12 12 1 0 13 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 16.3s 12 12 1 0 13 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 17.3s 12 12 1 1 13 <- slower FIRST task slow=12 actors, shared stolen=8, slower budget=4\n", + " 18.3s 12 12 1 1 14 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 19.4s 12 12 1 1 14 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 20.4s 12 12 2 2 15 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 21.4s 12 12 2 2 15 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 22.4s 12 12 3 3 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 23.4s 12 12 3 3 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 24.4s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 25.4s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 26.4s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 27.4s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 28.4s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 29.4s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 30.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 31.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 32.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 33.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 34.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 35.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 36.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 37.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 38.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 39.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 40.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 41.6s 12 11 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", + " 42.6s 11 11 4 4 0 \n", + " 43.6s 10 9 4 4 15 \n", + " 44.6s 9 9 5 5 15 \n", + " 45.6s 8 8 5 5 14 \n", + " 46.6s 8 8 6 6 15 \n", + " 47.6s 7 7 7 7 0 \n", + " 48.6s 6 6 7 7 15 \n", + " 49.6s 5 4 9 8 15 \n", + " 50.6s 3 3 9 9 14 \n", + " 51.6s 3 3 10 10 14 \n", + " 52.7s 2 2 11 11 13 \n", + " 53.7s 2 2 11 11 13 \n", + " 54.7s 1 1 11 11 12 \n", + " 55.7s 1 1 11 11 12 \n", + " 56.7s 0 0 11 11 11 \n", + " 57.7s 0 0 11 11 11 \n", + " 58.7s 0 0 11 11 11 \n", + " 59.7s 0 0 11 11 11 \n", + " 60.7s 0 0 11 11 11 \n", + " 61.7s 0 0 11 10 11 \n", + " 62.7s 0 0 8 8 8 \n", + " 63.7s 0 0 8 8 8 \n", + " 64.8s 0 0 7 7 7 \n", + " 65.8s 0 0 7 7 7 \n", + " 66.8s 0 0 7 7 7 \n", + " 67.8s 0 0 5 5 5 \n", + " 68.8s 0 0 5 5 5 \n", + " 69.8s 0 0 4 3 5 \n", + " 70.8s 0 0 2 2 2 \n", + " 71.8s 0 0 2 2 2 \n", + " 72.8s 0 0 2 2 2 \n", + " 73.8s 0 0 2 2 2 \n", + " 74.8s 0 0 1 1 1 \n", "\n", - "Bandwidth saturation: 12 download actors x 10s = 1.2 files/sec (same as 1 actor x 0.83s = 1.2 files/sec)\n", - "=> 12 actors wasted for zero throughput gain, starving Iterate\n" + "SlowActor peak: 12 actors (exhausts shared pool at >= 12)\n", + "SlowerActor during starvation: 4 actors (reserved=4, potential=12)\n", + "Throughput loss on critical path: 1.20 vs 0.40 files/sec => 3x slower\n" ] } ], "source": [ - "# Budget constants (16 CPUs, ratio=0.5, 2 ops)\n", - "RESERVED = 4\n", - "SHARED = 8\n", - "STARVED_AT = RESERVED + SHARED # download actors needed to exhaust shared pool = 12\n", - "\n", "print(\"=== Timeline (1s samples) ===\")\n", - "print(f\" {'t':>5} {'dl_alloc':>8} {'dl_active':>9} {'it_alloc':>8} {'it_active':>9} {'cpu':>5} note\")\n", - "print(\" \" + \"-\"*85)\n", + "print(f\" {'t':>5} {'slow_alloc':>10} {'slow_active':>11} \"\n", + " f\"{'slower_alloc':>12} {'slower_active':>13} {'cpu':>4} note\")\n", + "print(\" \" + \"-\"*90)\n", "\n", - "it_started = False\n", + "slower_started = False\n", "for ts, alloc, active, cpu in snapshots:\n", - " dl = alloc.get(\"dl\", 0)\n", - " it = alloc.get(\"it\", 0)\n", - " dl_t = active.get(\"dl\", 0)\n", - " it_t = active.get(\"it\", 0)\n", + " sl_a = alloc.get(\"slow\", 0)\n", + " sl_t = active.get(\"slow\", 0)\n", + " sr_a = alloc.get(\"slower\", 0)\n", + " sr_t = active.get(\"slower\",0)\n", + "\n", + " stolen = max(0, sl_a - RESERVED)\n", + " rem_shared = max(0, SHARED - stolen)\n", + " sr_budget = RESERVED + rem_shared\n", "\n", " note = \"\"\n", - " if it == 0 and dl > 0:\n", - " note = \"<- iterate: 0 input\"\n", - " elif not it_started and it_t > 0:\n", - " it_started = True\n", - " stolen = max(0, dl - RESERVED)\n", - " note = f\"<- iterate FIRST task (dl={dl}, shared stolen={stolen})\"\n", - " elif dl >= STARVED_AT and it <= RESERVED:\n", - " note = f\"<- STARVED: iterate capped at reserved={RESERVED}\"\n", + " if sr_a == 0 and sl_a > 0:\n", + " note = f\"<- slower: 0 input (slow stealing shared, slower budget if started={sr_budget})\"\n", + " elif not slower_started and sr_t > 0:\n", + " slower_started = True\n", + " note = f\"<- slower FIRST task slow={sl_a} actors, shared stolen={stolen}, slower budget={sr_budget}\"\n", + " elif sl_a >= STARVED_AT and sr_a <= RESERVED:\n", + " note = f\"<- STARVED: slower capped at reserved={RESERVED}, util>=1.75 but Gate 3 blocks\"\n", "\n", - " print(f\" {ts:5.1f}s {dl:>8d} {dl_t:>9d} {it:>8d} {it_t:>9d} {cpu:>4.0f} {note}\")\n", + " print(f\" {ts:5.1f}s {sl_a:>10d} {sl_t:>11d} \"\n", + " f\"{sr_a:>12d} {sr_t:>13d} {cpu:>3.0f} {note}\")\n", "\n", "print()\n", "\n", "# Summary\n", - "peak_dl = max((s[1].get(\"dl\", 0) for s in snapshots), default=0)\n", - "it_at_starvation = [s[1].get(\"it\", 0) for s in snapshots if s[1].get(\"dl\", 0) >= STARVED_AT]\n", - "peak_it_starved = max(it_at_starvation, default=0)\n", + "peak_slow = max((s[1].get(\"slow\", 0) for s in snapshots), default=0)\n", + "sr_starved = [s[1].get(\"slower\", 0) for s in snapshots if s[1].get(\"slow\", 0) >= STARVED_AT]\n", + "peak_sr_starved = max(sr_starved, default=0)\n", "\n", - "print(f\"Download peak: {peak_dl} actors (exhausts shared when >= {STARVED_AT})\")\n", - "print(f\"Iterate during starvation: {peak_it_starved} actors (reserved={RESERVED}, could use {STARVED_AT} without stealing)\")\n", - "print(f\"Throughput loss: {STARVED_AT/ITERATE_DELAY:.1f} vs {peak_it_starved/ITERATE_DELAY:.1f} files/sec\"\n", - " f\" => {STARVED_AT/max(1,peak_it_starved):.0f}x slower\")\n", - "print()\n", - "print(f\"Bandwidth saturation: {peak_dl} download actors x {DOWNLOAD_DELAY:.0f}s\"\n", - " f\" = {peak_dl/DOWNLOAD_DELAY:.1f} files/sec\"\n", - " f\" (same as 1 actor x {DOWNLOAD_DELAY_SOLO:.2f}s = {1/DOWNLOAD_DELAY_SOLO:.1f} files/sec)\")\n", - "print(f\"=> {peak_dl} actors wasted for zero throughput gain, starving Iterate\")\n" + "print(f\"SlowActor peak: {peak_slow} actors (exhausts shared pool at >= {STARVED_AT})\")\n", + "print(f\"SlowerActor during starvation: {peak_sr_starved} actors \"\n", + " f\"(reserved={RESERVED}, potential={STARVED_AT})\")\n", + "potential_tput = STARVED_AT / SLOWER_DELAY\n", + "actual_tput = max(1, peak_sr_starved) / SLOWER_DELAY\n", + "print(f\"Throughput loss on critical path: \"\n", + " f\"{potential_tput:.2f} vs {actual_tput:.2f} files/sec\"\n", + " f\" => {int(round(potential_tput / actual_tput))}x slower\")\n" ] } ], From 932ea66c592aaec0575c0c4b27168de77d0e29be Mon Sep 17 00:00:00 2001 From: Weijia Chen Date: Tue, 14 Jul 2026 23:34:25 +0000 Subject: [PATCH 6/6] 128 cpu, generic --- reservation_ratio_test.ipynb | 1151 +++++++++++++++++++++++++--------- 1 file changed, 859 insertions(+), 292 deletions(-) diff --git a/reservation_ratio_test.ipynb b/reservation_ratio_test.ipynb index e0b854b2db..e67974c2c1 100644 --- a/reservation_ratio_test.ipynb +++ b/reservation_ratio_test.ipynb @@ -6,10 +6,10 @@ "id": "c00", "metadata": { "execution": { - "iopub.execute_input": "2026-07-14T21:51:24.430727Z", - "iopub.status.busy": "2026-07-14T21:51:24.430449Z", - "iopub.status.idle": "2026-07-14T21:51:26.398913Z", - "shell.execute_reply": "2026-07-14T21:51:26.395811Z" + "iopub.execute_input": "2026-07-14T23:21:26.356462Z", + "iopub.status.busy": "2026-07-14T23:21:26.356195Z", + "iopub.status.idle": "2026-07-14T23:21:28.357666Z", + "shell.execute_reply": "2026-07-14T23:21:28.355588Z" } }, "outputs": [ @@ -22,26 +22,45 @@ } ], "source": [ - "# Ray Data Fair Scheduler — Shared Pool Starvation Repro\n", + "# ======================================================================================\n", + "# Ray Data Fair Scheduler — Shared Pool Lock-Stealing & Bottleneck Starvation Repro\n", + "# ======================================================================================\n", "#\n", - "# Pipeline:\n", - "# instant_source (0s) -> SlowActor (15s) -> SlowerActor (10s) -> fast_sink (0s)\n", + "# Pipeline Topology:\n", + "# instant_source (0s) -> SlowActor (10s) -> SlowerActor (15s) -> fast_sink (0s)\n", "#\n", - "# Issue:\n", - "# instant_source finishes immediately. All 32 items queue for SlowActor at once.\n", - "# Autoscaler ramps SlowActor every few ms (util=2.0 >= 1.75) before it produces\n", - "# any output. After ~12s the shared CPU pool is fully exhausted by SlowActor.\n", - "# SlowerActor starts with 0 input until t~15s. By then SlowActor holds all shared\n", - "# CPUs, and SlowerActor is capped at its reserved allocation only.\n", + "# Root Cause Theory:\n", + "# Ray Data's autoscaler evaluates scaling decisions independently for each stage\n", + "# based purely on instant local utilization, completely blind to downstream capacity\n", + "# or overall pipeline flow control.\n", "#\n", - "# Even though SlowerActor is the true bottleneck (highest per-actor latency when\n", - "# capped at 4 actors), util >= 1.75 passes Gate 1 but Gate 3 blocks scale-up:\n", - "# budget = reserved = 4 CPUs => 3x throughput loss on the critical path.\n", + "# Scenario Walkthrough:\n", + "# 1. `instant_source` populates the queue instantly. All 512 items queue for `SlowActor`.\n", + "# 2. Due to the initial 10s task latency, `SlowActor` produces zero output for the first 10s.\n", + "# 3. Consequently, the downstream critical bottleneck (`SlowerActor`) sits at 0 active inputs.\n", + "# 4. Meanwhile, the fair scheduler loop fires every few ms. It sees `SlowActor` has high local\n", + "# utilization (util >= 1.75) and aggressively ramps it up to 96 actors by t~30s,\n", + "# completely draining the 64-CPU shared pool.\n", + "# 5. When `SlowerActor` finally wakes up and yells for resources (util >= 1.75), it passes\n", + "# the local demand check, but the global shared pool is already entirely hijacked by the\n", + "# upstream. As a result, the true bottleneck stage is hard-capped at its reserved\n", + "# allocation only.\n", "#\n", - "# Budget (16 CPUs, reservation_ratio=0.5, 2 eligible ActorPool ops):\n", - "# reserved/op = 4 | shared = 8\n", - "# SlowActor steals shared when it exceeds 4 actors (reserved)\n", - "# At 12 actors: shared fully exhausted -> SlowerActor capped at 4\n", + "# Resource Budget Configuration (128 CPUs, reservation_ratio=0.5, 2 ops):\n", + "# - Reserved allocation per operator = 32 CPUs\n", + "# - Global shared pool allocation = 64 CPUs\n", + "# - Maximum cap to drain the shared pool = 32 (reserved) + 64 (shared) = 96 CPUs\n", + "#\n", + "# Feasible Fair Counterfactual (The Global Optimum):\n", + "# Since `SlowerActor` (15s) is the definitive critical path bottleneck, a global-aware\n", + "# scheduler should allocate the 64 shared CPUs to `SlowerActor` to maximize end-to-end\n", + "# pipeline throughput, while keeping `SlowActor` at its 32 reserved slots to prevent\n", + "# memory backlog.\n", + "# - Optimal Fair Profile: SlowActor = 32 CPUs | SlowerActor = 96 CPUs (Total = 128, feasible)\n", + "# - Actual Bug Profile : SlowActor = 96 CPUs | SlowerActor = 32 CPUs (Total = 128, starved)\n", + "#\n", + "# This structural imbalance leads to a permanent 3x capacity loss on the bottleneck stage.\n", + "# ======================================================================================\n", "\n", "import time, threading, collections\n", "import ray, ray.data\n", @@ -56,10 +75,10 @@ "id": "c01", "metadata": { "execution": { - "iopub.execute_input": "2026-07-14T21:51:26.405223Z", - "iopub.status.busy": "2026-07-14T21:51:26.404858Z", - "iopub.status.idle": "2026-07-14T21:51:26.410669Z", - "shell.execute_reply": "2026-07-14T21:51:26.408793Z" + "iopub.execute_input": "2026-07-14T23:21:28.364429Z", + "iopub.status.busy": "2026-07-14T23:21:28.363941Z", + "iopub.status.idle": "2026-07-14T23:21:28.369799Z", + "shell.execute_reply": "2026-07-14T23:21:28.368390Z" } }, "outputs": [ @@ -67,25 +86,34 @@ "name": "stdout", "output_type": "stream", "text": [ - "SlowerActor if NOT starved: 12 actors / 10s = 1.20 files/sec\n", - "SlowerActor when starved : 4 actors / 10s = 0.40 files/sec\n", - "=> 3x throughput loss on the critical path\n" + "Optimal Fair Profile: SlowActor=32 + SlowerActor=96 = 128 CPUs (= budget)\n", + "Actual Bug Profile : SlowActor=96 + SlowerActor=32 = 128 CPUs (= budget)\n", + "\n", + "SlowerActor stage capacity — fair ideal: 96 actors / 15s = 6.40 files/sec\n", + "SlowerActor stage capacity — starved : 32 actors / 15s = 2.13 files/sec\n", + "=> 3x capacity loss on the bottleneck stage\n" ] } ], "source": [ - "NUM_FILES = 32\n", - "SLOW_DELAY = 15.0 # SlowActor: 15s/item; with 32 tasks, util=32/12=2.67>=1.75 all the way to budget cap\n", - "SLOWER_DELAY = 10.0 # SlowerActor: true bottleneck, starved at reserved CPUs only\n", + "NUM_FILES = 512\n", + "SLOW_DELAY = 10.0 # SlowActor: 10s/item (fast upstream, like Download)\n", + " # SlowActor ramps to 96 by t~30s; queue still has >400 items => pool stolen\n", + "SLOWER_DELAY = 15.0 # SlowerActor: 15s/item (slow downstream, like Iterate|Extract); true bottleneck\n", "\n", - "# Budget (16 CPUs, ratio=0.5, 2 ops):\n", - "RESERVED = 4 # CPUs per op\n", - "SHARED = 8 # shared pool\n", - "STARVED_AT = RESERVED + SHARED # slow actors needed to exhaust shared = 12\n", + "# Budget (128 CPUs, ratio=0.5, 2 ops):\n", + "RESERVED = 32 # CPUs per op\n", + "SHARED = 64 # shared pool\n", + "STARVED_AT = RESERVED + SHARED # SlowActor actors needed to exhaust shared pool = 96\n", "\n", - "print(f\"SlowerActor if NOT starved: {STARVED_AT} actors / {SLOWER_DELAY:.0f}s = {STARVED_AT/SLOWER_DELAY:.2f} files/sec\")\n", - "print(f\"SlowerActor when starved : {RESERVED} actors / {SLOWER_DELAY:.0f}s = {RESERVED/SLOWER_DELAY:.2f} files/sec\")\n", - "print(f\"=> {STARVED_AT//RESERVED}x throughput loss on the critical path\")\n" + "# Fair counterfactual: SlowActor stays at RESERVED, SlowerActor gets RESERVED + SHARED\n", + "# Total CPUs = RESERVED + STARVED_AT = 32 + 96 = 128 = budget (physically feasible)\n", + "print(f\"Optimal Fair Profile: SlowActor={RESERVED} + SlowerActor={STARVED_AT} = {RESERVED+STARVED_AT} CPUs (= budget)\")\n", + "print(f\"Actual Bug Profile : SlowActor={STARVED_AT} + SlowerActor={RESERVED} = {STARVED_AT+RESERVED} CPUs (= budget)\")\n", + "print()\n", + "print(f\"SlowerActor stage capacity — fair ideal: {STARVED_AT} actors / {SLOWER_DELAY:.0f}s = {STARVED_AT/SLOWER_DELAY:.2f} files/sec\")\n", + "print(f\"SlowerActor stage capacity — starved : {RESERVED} actors / {SLOWER_DELAY:.0f}s = {RESERVED/SLOWER_DELAY:.2f} files/sec\")\n", + "print(f\"=> {STARVED_AT//RESERVED}x capacity loss on the bottleneck stage\")\n" ] }, { @@ -94,10 +122,10 @@ "id": "c02", "metadata": { "execution": { - "iopub.execute_input": "2026-07-14T21:51:26.414628Z", - "iopub.status.busy": "2026-07-14T21:51:26.414441Z", - "iopub.status.idle": "2026-07-14T21:51:26.423500Z", - "shell.execute_reply": "2026-07-14T21:51:26.421497Z" + "iopub.execute_input": "2026-07-14T23:21:28.373546Z", + "iopub.status.busy": "2026-07-14T23:21:28.373366Z", + "iopub.status.idle": "2026-07-14T23:21:28.381185Z", + "shell.execute_reply": "2026-07-14T23:21:28.379727Z" } }, "outputs": [], @@ -168,10 +196,10 @@ "id": "c03", "metadata": { "execution": { - "iopub.execute_input": "2026-07-14T21:51:26.426647Z", - "iopub.status.busy": "2026-07-14T21:51:26.426506Z", - "iopub.status.idle": "2026-07-14T21:52:58.267915Z", - "shell.execute_reply": "2026-07-14T21:52:58.265146Z" + "iopub.execute_input": "2026-07-14T23:21:28.384794Z", + "iopub.status.busy": "2026-07-14T23:21:28.384644Z", + "iopub.status.idle": "2026-07-14T23:24:11.246759Z", + "shell.execute_reply": "2026-07-14T23:24:11.245618Z" } }, "outputs": [ @@ -179,406 +207,622 @@ "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:40,178\tINFO worker.py:2015 -- Started a local Ray instance. View the dashboard at \u001b[1m\u001b[32mhttp://127.0.0.1:8269 \u001b[39m\u001b[22m\n" + "2026-07-14 23:21:42,982\tINFO worker.py:2015 -- Started a local Ray instance. View the dashboard at \u001b[1m\u001b[32mhttp://127.0.0.1:8269 \u001b[39m\u001b[22m\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:21:45,960\tINFO streaming_executor.py:193 -- Starting execution of Dataset dataset_5_0. Full logs are in /raid/weijiac/ray_tmp/session_2026-07-14_23-21-28_664742_3010502/logs/ray-data\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:21:45,961\tINFO streaming_executor.py:194 -- Execution plan of Dataset dataset_5_0: InputDataBuffer[Input] -> TaskPoolMapOperator[MapBatches(instant_source)->StreamingRepartition[num_rows_per_block=1,strict=False]] -> ActorPoolMapOperator[MapBatches(SlowActor)] -> ActorPoolMapOperator[MapBatches(SlowerActor)] -> TaskPoolMapOperator[MapBatches(fast_sink)]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[2026-07-14 23:21:45,994 E 3010502 3010502] core_worker.cc:2149: Actor with class name: 'MapWorker(MapBatches(SlowActor))' and ID: 'ec39eb6e0d98bd03654fdb2701000000' has constructor arguments in the object store and max_restarts > 0. If the arguments in the object store go out of scope or are lost, the actor restart will fail. See https://github.com/ray-project/ray/issues/53727 for more details.\n", + "2026-07-14 23:21:46,017\tINFO __init__.py:56 -- Progress will be logged because stdout is a non-interactive terminal.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:21:46,051\tWARNING resource_manager.py:766 -- Cluster resources are not enough to run any task from TaskPoolMapOperator[MapBatches(instant_source)->StreamingRepartition[num_rows_per_block=1,strict=False]]. The job may hang forever unless the cluster scales up.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:21:46,172\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:21:46,173\tINFO logging_progress.py:225 -- Total Progress: 0/?\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:21:46,173\tINFO logging_progress.py:227 -- Active & requested resources: 0/0 CPU, 0.0B/0.0B object store (pending: 2 CPU)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:21:46,173\tINFO logging_progress.py:181 -- \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:21:46,174\tINFO logging_progress.py:231 -- MapBatches(instant_source)->StreamingRepartition[num_rows_per_block=1,strict=False]: 0/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:21:46,174\tINFO logging_progress.py:233 -- Tasks: 1 [backpressured:tasks(ResourceBudget)]; Actors: 0; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:21:46,174\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 0/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:21:46,174\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 1 (running=0, restarting=0, pending=1, active=0, idle=0, util=0.000, tasks_in_flight=0); Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:21:46,175\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 0/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:21:46,175\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 1 (running=0, restarting=0, pending=1, active=0, idle=0, util=0.000, tasks_in_flight=0); Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:21:46,175\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 0/1\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:21:46,176\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:21:46,176\tINFO logging_progress.py:192 -- ============================================\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:42,573\tINFO streaming_executor.py:193 -- Starting execution of Dataset dataset_5_0. Full logs are in /tmp/ray/session_2026-07-14_21-51-26_677860_2186124/logs/ray-data\n" + "2026-07-14 23:21:56,181\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:42,575\tINFO streaming_executor.py:194 -- Execution plan of Dataset dataset_5_0: InputDataBuffer[Input] -> TaskPoolMapOperator[MapBatches(instant_source)] -> AllToAllOperator[Repartition] -> ActorPoolMapOperator[MapBatches(SlowActor)] -> ActorPoolMapOperator[MapBatches(SlowerActor)] -> TaskPoolMapOperator[MapBatches(fast_sink)]\n" + "2026-07-14 23:21:56,184\tINFO logging_progress.py:225 -- Total Progress: 0/?\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "[2026-07-14 21:51:42,617 E 2186124 2186124] core_worker.cc:2149: Actor with class name: 'MapWorker(MapBatches(SlowActor))' and ID: 'd714c01c220de29caff2d43501000000' has constructor arguments in the object store and max_restarts > 0. If the arguments in the object store go out of scope or are lost, the actor restart will fail. See https://github.com/ray-project/ray/issues/53727 for more details.\n", - "2026-07-14 21:51:42,643\tINFO __init__.py:56 -- Progress will be logged because stdout is a non-interactive terminal.\n" + "2026-07-14 23:21:56,185\tINFO logging_progress.py:227 -- Active & requested resources: 17/128 CPU, 1.4KiB/93.1GiB object store (pending: 3 CPU)\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:42,682\tWARNING resource_manager.py:766 -- Cluster resources are not enough to run any task from TaskPoolMapOperator[MapBatches(instant_source)]. The job may hang forever unless the cluster scales up.\n" + "2026-07-14 23:21:56,186\tINFO logging_progress.py:181 -- \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:42,807\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + "2026-07-14 23:21:56,187\tINFO logging_progress.py:231 -- MapBatches(instant_source)->StreamingRepartition[num_rows_per_block=1,strict=False]: 171/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:42,809\tINFO logging_progress.py:225 -- Total Progress: 0/?\n" + "2026-07-14 23:21:56,188\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 1.4KiB object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:42,811\tINFO logging_progress.py:227 -- Active & requested resources: 0/0 CPU, 0.0B/0.0B object store (pending: 2 CPU)\n" + "2026-07-14 23:21:56,189\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 0/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:42,812\tINFO logging_progress.py:181 -- \n" + "2026-07-14 23:21:56,189\tINFO logging_progress.py:233 -- Tasks: 30; Actors: 18 (running=15, restarting=0, pending=3, active=15, idle=0, util=1.667, tasks_in_flight=30); Queued blocks: 141 (1.1KiB); Resources: 15.0 CPU, 0.0B object store; [0/30 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:42,813\tINFO logging_progress.py:231 -- MapBatches(instant_source): 0/1\n" + "2026-07-14 23:21:56,190\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 0/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:42,814\tINFO logging_progress.py:233 -- Tasks: 1 [backpressured:tasks(ResourceBudget)]; Actors: 0; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store\n" + "2026-07-14 23:21:56,190\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 1; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store; [all objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:42,815\tINFO logging_progress.py:231 -- Repartition: 0/1\n" + "2026-07-14 23:21:56,191\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 0/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:42,815\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 0 rows output\n" + "2026-07-14 23:21:56,191\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:42,816\tINFO logging_progress.py:231 -- - Split Repartition: 0/1\n" + "2026-07-14 23:21:56,192\tINFO logging_progress.py:192 -- ============================================\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:42,816\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 0/1\n" + "2026-07-14 23:22:06,236\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:42,817\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 1 (running=0, restarting=0, pending=1, active=0, idle=0, util=0.000, tasks_in_flight=0); Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n" + "2026-07-14 23:22:06,240\tINFO logging_progress.py:225 -- Total Progress: 0/?\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:42,818\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 0/1\n" + "2026-07-14 23:22:06,241\tINFO logging_progress.py:227 -- Active & requested resources: 88/128 CPU, 464.0B/1.9TiB memory, 3.3KiB/93.1GiB object store (pending: 7 CPU, 48.0B memory)\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:42,818\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 1 (running=0, restarting=0, pending=1, active=0, idle=0, util=0.000, tasks_in_flight=0); Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; [all objects local]\n" + "2026-07-14 23:22:06,242\tINFO logging_progress.py:181 -- \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:42,819\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 0/1\n" + "2026-07-14 23:22:06,243\tINFO logging_progress.py:231 -- MapBatches(instant_source)->StreamingRepartition[num_rows_per_block=1,strict=False]: 347/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:42,819\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + "2026-07-14 23:22:06,243\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 2.6KiB object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:42,820\tINFO logging_progress.py:192 -- ============================================\n" + "2026-07-14 23:22:06,244\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 15/?\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\u001b[33m(raylet)\u001b[0m [2026-07-14 21:51:45,087 E 2187411 2187442] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_21-51-26_677860_2186124 is over 95% full, available space: 0.0276375 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" + "2026-07-14 23:22:06,244\tINFO logging_progress.py:233 -- Tasks: 158; Actors: 86 (running=79, restarting=0, pending=7, active=79, idle=0, util=1.837, tasks_in_flight=158); Queued blocks: 174 (1.4KiB); Resources: 79.0 CPU, 464.0B memory, 752.0B object store; [0/173 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:52,869\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + "2026-07-14 23:22:06,245\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 0/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:52,872\tINFO logging_progress.py:225 -- Total Progress: 0/?\n" + "2026-07-14 23:22:06,245\tINFO logging_progress.py:233 -- Tasks: 15; Actors: 9 (running=8, restarting=0, pending=1, active=8, idle=0, util=1.667, tasks_in_flight=15); Queued blocks: 0 (0.0B); Resources: 8.0 CPU, 0.0B object store; [0/15 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:52,874\tINFO logging_progress.py:227 -- Active & requested resources: 8/16 CPU, 256.0B/93.1GiB object store (pending: 2 CPU)\n" + "2026-07-14 23:22:06,246\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 0/1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:52,876\tINFO logging_progress.py:181 -- \n" + "2026-07-14 23:22:06,247\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:52,877\tINFO logging_progress.py:231 -- MapBatches(instant_source): 32/32\n" + "2026-07-14 23:22:06,247\tINFO logging_progress.py:192 -- ============================================\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:16,091\tWARNING issue_detector_manager.py:69 -- \n", + "\n", + "Operator 'MapBatches(fast_sink)' uses 107.2MiB of memory per task on\n", + "average, but Ray only requests 0.0B per task at the start of the\n", + "pipeline.\n", + "\n", + "To avoid out-of-memory errors, consider setting `memory=107.2MiB` in\n", + "the appropriate function or method call. (This might be unnecessary if\n", + "the number of concurrent tasks is low.)\n", + "\n", + "To change the frequency of this warning, set\n", + "`DataContext.get_current().issue_detectors_config.high_memory_detector_config.detection_time_interval_s`,\n", + "or disable the warning by setting value to -1. (current value: 30)\n", + "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:52,878\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + "2026-07-14 23:22:16,094\tWARNING issue_detector_manager.py:96 -- Found 1 issues. To disable issue detection, run DataContext.get_current().issue_detectors_config.detectors = [].\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:52,879\tINFO logging_progress.py:231 -- Repartition: 32/32\n" + "2026-07-14 23:22:16,316\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:52,880\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 256.0B object store; 32 rows output\n" + "2026-07-14 23:22:16,318\tINFO logging_progress.py:225 -- Total Progress: 3/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:52,882\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" + "2026-07-14 23:22:16,319\tINFO logging_progress.py:227 -- Active & requested resources: 114/128 CPU, 608.0B/1.9TiB memory, 4.9KiB/93.1GiB object store (pending: 2 CPU, 16.0B memory)\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:52,882\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 0/1\n" + "2026-07-14 23:22:16,320\tINFO logging_progress.py:181 -- \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:52,884\tINFO logging_progress.py:233 -- Tasks: 14; Actors: 9 (running=7, restarting=0, pending=2, active=7, idle=0, util=1.556, tasks_in_flight=14); Queued blocks: 18 (144.0B); Resources: 7.0 CPU, 0.0B object store; [0/14 objects local]\n" + "2026-07-14 23:22:16,320\tINFO logging_progress.py:231 -- MapBatches(instant_source)->StreamingRepartition[num_rows_per_block=1,strict=False]: 512/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:52,885\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 0/1\n" + "2026-07-14 23:22:16,321\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 3.3KiB object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:52,885\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 1; Queued blocks: 0 (0.0B); Resources: 1.0 CPU, 0.0B object store; [all objects local]\n" + "2026-07-14 23:22:16,321\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 94/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:52,886\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 0/1\n" + "2026-07-14 23:22:16,322\tINFO logging_progress.py:233 -- Tasks: 190; Actors: 96; Queued blocks: 228 (1.8KiB); Resources: 96.0 CPU, 600.0B memory, 1.5KiB object store; [0/284 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:52,887\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + "2026-07-14 23:22:16,322\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 3/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:51:52,888\tINFO logging_progress.py:192 -- ============================================\n" + "2026-07-14 23:22:16,322\tINFO logging_progress.py:233 -- Tasks: 35; Actors: 20 (running=18, restarting=0, pending=2, active=18, idle=0, util=1.750, tasks_in_flight=35); Queued blocks: 56 (448.0B); Resources: 18.0 CPU, 8.0B memory, 144.0B object store; [0/38 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\u001b[33m(raylet)\u001b[0m [2026-07-14 21:51:55,109 E 2187411 2187442] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_21-51-26_677860_2186124 is over 95% full, available space: 0.0273285 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" + "2026-07-14 23:22:16,323\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 3/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:02,891\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + "2026-07-14 23:22:16,323\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:02,894\tINFO logging_progress.py:225 -- Total Progress: 0/?\n" + "2026-07-14 23:22:16,323\tINFO logging_progress.py:192 -- ============================================\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:02,896\tINFO logging_progress.py:227 -- Active & requested resources: 14/16 CPU, 352.0B/93.1GiB object store (pending: 1 CPU)\n" + "2026-07-14 23:22:26,414\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:02,898\tINFO logging_progress.py:181 -- \n" + "2026-07-14 23:22:26,415\tINFO logging_progress.py:225 -- Total Progress: 17/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:02,899\tINFO logging_progress.py:231 -- MapBatches(instant_source): 32/32\n" + "2026-07-14 23:22:26,416\tINFO logging_progress.py:227 -- Active & requested resources: 128/128 CPU, 720.0B/1.9TiB memory, 4.9KiB/93.1GiB object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:02,900\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + "2026-07-14 23:22:26,417\tINFO logging_progress.py:181 -- \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:02,901\tINFO logging_progress.py:231 -- Repartition: 32/32\n" + "2026-07-14 23:22:26,417\tINFO logging_progress.py:231 -- MapBatches(instant_source)->StreamingRepartition[num_rows_per_block=1,strict=False]: 512/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:02,901\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 216.0B object store; 32 rows output\n" + "2026-07-14 23:22:26,418\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 2.5KiB object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:02,901\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" + "2026-07-14 23:22:26,418\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 190/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:02,902\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 5/32\n" + "2026-07-14 23:22:26,418\tINFO logging_progress.py:233 -- Tasks: 192; Actors: 96; Queued blocks: 130 (1.0KiB); Resources: 96.0 CPU, 600.0B memory, 2.1KiB object store; [0/382 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:02,902\tINFO logging_progress.py:233 -- Tasks: 24; Actors: 12; Queued blocks: 3 (24.0B); Resources: 12.0 CPU, 136.0B object store; [0/29 objects local]\n" + "2026-07-14 23:22:26,419\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 17/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:02,903\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 0/1\n" + "2026-07-14 23:22:26,419\tINFO logging_progress.py:233 -- Tasks: 64; Actors: 32; Queued blocks: 109 (872.0B); Resources: 32.0 CPU, 120.0B memory, 256.0B object store; [0/81 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:02,904\tINFO logging_progress.py:233 -- Tasks: 4; Actors: 3 (running=2, restarting=0, pending=1, active=2, idle=0, util=1.333, tasks_in_flight=4); Queued blocks: 1 (8.0B); Resources: 2.0 CPU, 0.0B object store; [0/4 objects local]\n" + "2026-07-14 23:22:26,419\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 17/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:02,906\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 0/1\n" + "2026-07-14 23:22:26,419\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:02,908\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + "2026-07-14 23:22:26,419\tINFO logging_progress.py:192 -- ============================================\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:02,909\tINFO logging_progress.py:192 -- ============================================\n" + "2026-07-14 23:22:36,425\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\u001b[33m(raylet)\u001b[0m [2026-07-14 21:52:05,129 E 2187411 2187442] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_21-51-26_677860_2186124 is over 95% full, available space: 0.027092 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" + "2026-07-14 23:22:36,426\tINFO logging_progress.py:225 -- Total Progress: 38/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:12,776\tWARNING issue_detector_manager.py:69 -- \n", + "2026-07-14 23:22:36,428\tINFO logging_progress.py:227 -- Active & requested resources: 128/128 CPU, 720.0B/1.9TiB memory, 4.7KiB/93.1GiB object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:36,429\tINFO logging_progress.py:181 -- \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:36,429\tINFO logging_progress.py:231 -- MapBatches(instant_source)->StreamingRepartition[num_rows_per_block=1,strict=False]: 512/512\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:36,429\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 1.8KiB object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:36,429\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 286/512\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:36,430\tINFO logging_progress.py:233 -- Tasks: 192; Actors: 96; Queued blocks: 34 (272.0B); Resources: 96.0 CPU, 600.0B memory, 2.7KiB object store; [0/478 objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:36,430\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 38/512\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:36,430\tINFO logging_progress.py:233 -- Tasks: 64; Actors: 32; Queued blocks: 184 (1.4KiB); Resources: 32.0 CPU, 120.0B memory, 256.0B object store; [0/102 objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:36,430\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 38/512\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:36,431\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:36,431\tINFO logging_progress.py:192 -- ============================================\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:46,121\tWARNING issue_detector_manager.py:69 -- \n", "\n", - "Operator 'MapBatches(fast_sink)' uses 114.8MiB of memory per task on\n", + "Operator 'MapBatches(fast_sink)' uses 106.8MiB of memory per task on\n", "average, but Ray only requests 0.0B per task at the start of the\n", "pipeline.\n", "\n", - "To avoid out-of-memory errors, consider setting `memory=114.8MiB` in\n", + "To avoid out-of-memory errors, consider setting `memory=106.8MiB` in\n", "the appropriate function or method call. (This might be unnecessary if\n", "the number of concurrent tasks is low.)\n", "\n", @@ -592,377 +836,593 @@ "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:12,778\tWARNING issue_detector_manager.py:96 -- Found 1 issues. To disable issue detection, run DataContext.get_current().issue_detectors_config.detectors = [].\n" + "2026-07-14 23:22:46,123\tWARNING issue_detector_manager.py:96 -- Found 1 issues. To disable issue detection, run DataContext.get_current().issue_detectors_config.detectors = [].\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:46,452\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:46,454\tINFO logging_progress.py:225 -- Total Progress: 51/512\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:46,456\tINFO logging_progress.py:227 -- Active & requested resources: 128/128 CPU, 728.0B/1.9TiB memory, 4.6KiB/93.1GiB object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:46,458\tINFO logging_progress.py:181 -- \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:46,458\tINFO logging_progress.py:231 -- MapBatches(instant_source)->StreamingRepartition[num_rows_per_block=1,strict=False]: 512/512\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:46,459\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 1.0KiB object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:46,460\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 382/512\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:46,460\tINFO logging_progress.py:233 -- Tasks: 130; Actors: 96; Queued blocks: 0 (0.0B); Resources: 96.0 CPU, 600.0B memory, 3.3KiB object store; [0/512 objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:46,460\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 53/512\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:46,461\tINFO logging_progress.py:233 -- Tasks: 63; Actors: 32; Queued blocks: 266 (2.1KiB); Resources: 32.0 CPU, 120.0B memory, 272.0B object store; [0/116 objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:46,461\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 51/512\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:46,461\tINFO logging_progress.py:233 -- Tasks: 2; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 16.0B memory, 24.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:46,461\tINFO logging_progress.py:192 -- ============================================\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:56,546\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:56,547\tINFO logging_progress.py:225 -- Total Progress: 81/512\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:56,548\tINFO logging_progress.py:227 -- Active & requested resources: 92/128 CPU, 520.0B/1.9TiB memory, 4.0KiB/93.1GiB object store (pending: 4 CPU, 32.0B memory)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:56,548\tINFO logging_progress.py:181 -- \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:56,548\tINFO logging_progress.py:231 -- MapBatches(instant_source)->StreamingRepartition[num_rows_per_block=1,strict=False]: 512/512\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:22:56,548\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 256.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:12,995\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + "2026-07-14 23:22:56,549\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 480/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:12,997\tINFO logging_progress.py:225 -- Total Progress: 2/32\n" + "2026-07-14 23:22:56,549\tINFO logging_progress.py:233 -- Tasks: 32; Actors: 41; Queued blocks: 0 (0.0B); Resources: 41.0 CPU, 248.0B memory, 3.4KiB object store; [0/512 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:12,999\tINFO logging_progress.py:227 -- Active & requested resources: 16/16 CPU, 376.0B/93.1GiB object store\n" + "2026-07-14 23:22:56,549\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 81/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:13,000\tINFO logging_progress.py:181 -- \n" + "2026-07-14 23:22:56,550\tINFO logging_progress.py:233 -- Tasks: 97; Actors: 55 (running=51, restarting=0, pending=4, active=49, idle=2, util=1.764, tasks_in_flight=97); Queued blocks: 302 (2.4KiB); Resources: 51.0 CPU, 272.0B memory, 392.0B object store; [0/178 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:13,001\tINFO logging_progress.py:231 -- MapBatches(instant_source): 32/32\n" + "2026-07-14 23:22:56,550\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 81/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:13,002\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + "2026-07-14 23:22:56,550\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:13,003\tINFO logging_progress.py:231 -- Repartition: 32/32\n" + "2026-07-14 23:22:56,550\tINFO logging_progress.py:192 -- ============================================\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:13,003\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 160.0B object store; 32 rows output\n" + "2026-07-14 23:23:06,554\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:13,004\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" + "2026-07-14 23:23:06,557\tINFO logging_progress.py:225 -- Total Progress: 102/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:13,004\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 12/32\n" + "2026-07-14 23:23:06,558\tINFO logging_progress.py:227 -- Active & requested resources: 96/128 CPU, 632.0B/1.9TiB memory, 4.0KiB/93.1GiB object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:13,004\tINFO logging_progress.py:233 -- Tasks: 20; Actors: 12; Queued blocks: 0 (0.0B); Resources: 12.0 CPU, 176.0B object store; [0/32 objects local]\n" + "2026-07-14 23:23:06,560\tINFO logging_progress.py:181 -- \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:13,005\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 2/32\n" + "2026-07-14 23:23:06,561\tINFO logging_progress.py:231 -- MapBatches(instant_source)->StreamingRepartition[num_rows_per_block=1,strict=False]: 512/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:13,005\tINFO logging_progress.py:233 -- Tasks: 8; Actors: 4; Queued blocks: 2 (16.0B); Resources: 4.0 CPU, 32.0B object store; [0/10 objects local]\n" + "2026-07-14 23:23:06,562\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:13,006\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 2/32\n" + "2026-07-14 23:23:06,563\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 512/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:13,006\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B object store\n" + "2026-07-14 23:23:06,563\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 3.2KiB object store; [0/512 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:13,007\tINFO logging_progress.py:192 -- ============================================\n" + "2026-07-14 23:23:06,564\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 102/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\u001b[33m(raylet)\u001b[0m [2026-07-14 21:52:15,152 E 2187411 2187442] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_21-51-26_677860_2186124 is over 95% full, available space: 0.0269051 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" + "2026-07-14 23:23:06,564\tINFO logging_progress.py:233 -- Tasks: 192; Actors: 96; Queued blocks: 218 (1.7KiB); Resources: 96.0 CPU, 632.0B memory, 768.0B object store; [0/294 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:23,091\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + "2026-07-14 23:23:06,564\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 102/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:23,093\tINFO logging_progress.py:225 -- Total Progress: 6/32\n" + "2026-07-14 23:23:06,565\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:23,095\tINFO logging_progress.py:227 -- Active & requested resources: 16/16 CPU, 344.0B/93.1GiB object store\n" + "2026-07-14 23:23:06,565\tINFO logging_progress.py:192 -- ============================================\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:23,097\tINFO logging_progress.py:181 -- \n" + "2026-07-14 23:23:16,161\tWARNING issue_detector_manager.py:69 -- \n", + "\n", + "Operator 'MapBatches(fast_sink)' uses 106.5MiB of memory per task on\n", + "average, but Ray only requests 0.0B per task at the start of the\n", + "pipeline.\n", + "\n", + "To avoid out-of-memory errors, consider setting `memory=106.5MiB` in\n", + "the appropriate function or method call. (This might be unnecessary if\n", + "the number of concurrent tasks is low.)\n", + "\n", + "To change the frequency of this warning, set\n", + "`DataContext.get_current().issue_detectors_config.high_memory_detector_config.detection_time_interval_s`,\n", + "or disable the warning by setting value to -1. (current value: 30)\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:23:16,163\tWARNING issue_detector_manager.py:96 -- Found 1 issues. To disable issue detection, run DataContext.get_current().issue_detectors_config.detectors = [].\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:23,098\tINFO logging_progress.py:231 -- MapBatches(instant_source): 32/32\n" + "2026-07-14 23:23:16,596\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:23,100\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + "2026-07-14 23:23:16,598\tINFO logging_progress.py:225 -- Total Progress: 156/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:23,101\tINFO logging_progress.py:231 -- Repartition: 32/32\n" + "2026-07-14 23:23:16,600\tINFO logging_progress.py:227 -- Active & requested resources: 96/128 CPU, 632.0B/1.9TiB memory, 3.5KiB/93.1GiB object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:23,102\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 104.0B object store; 32 rows output\n" + "2026-07-14 23:23:16,604\tINFO logging_progress.py:181 -- \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:23,102\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" + "2026-07-14 23:23:16,605\tINFO logging_progress.py:231 -- MapBatches(instant_source)->StreamingRepartition[num_rows_per_block=1,strict=False]: 512/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:23,103\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 19/32\n" + "2026-07-14 23:23:16,605\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:23,104\tINFO logging_progress.py:233 -- Tasks: 13; Actors: 12; Queued blocks: 0 (0.0B); Resources: 12.0 CPU, 200.0B object store; [0/32 objects local]\n" + "2026-07-14 23:23:16,606\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 512/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:23,104\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 6/32\n" + "2026-07-14 23:23:16,606\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 2.8KiB object store; [0/512 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:23,105\tINFO logging_progress.py:233 -- Tasks: 8; Actors: 4; Queued blocks: 5 (40.0B); Resources: 4.0 CPU, 32.0B object store; [0/14 objects local]\n" + "2026-07-14 23:23:16,607\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 159/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:23,105\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 6/32\n" + "2026-07-14 23:23:16,607\tINFO logging_progress.py:233 -- Tasks: 189; Actors: 96; Queued blocks: 164 (1.3KiB); Resources: 96.0 CPU, 632.0B memory, 792.0B object store; [0/348 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:23,106\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B object store\n" + "2026-07-14 23:23:16,607\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 156/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:23,106\tINFO logging_progress.py:192 -- ============================================\n" + "2026-07-14 23:23:16,608\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 2 (16.0B); Resources: 0.0 CPU, 8.0B memory, 24.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\u001b[33m(raylet)\u001b[0m [2026-07-14 21:52:25,174 E 2187411 2187442] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_21-51-26_677860_2186124 is over 95% full, available space: 0.0267105 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" + "2026-07-14 23:23:16,608\tINFO logging_progress.py:192 -- ============================================\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:33,170\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + "2026-07-14 23:23:26,674\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:33,173\tINFO logging_progress.py:225 -- Total Progress: 9/32\n" + "2026-07-14 23:23:26,675\tINFO logging_progress.py:225 -- Total Progress: 225/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:33,175\tINFO logging_progress.py:227 -- Active & requested resources: 12/16 CPU, 48.0B/1.9TiB memory, 296.0B/93.1GiB object store (pending: 2 CPU, 16.0B memory)\n" + "2026-07-14 23:23:26,677\tINFO logging_progress.py:227 -- Active & requested resources: 96/128 CPU, 632.0B/1.9TiB memory, 3.0KiB/93.1GiB object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:33,177\tINFO logging_progress.py:181 -- \n" + "2026-07-14 23:23:26,678\tINFO logging_progress.py:181 -- \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:33,178\tINFO logging_progress.py:231 -- MapBatches(instant_source): 32/32\n" + "2026-07-14 23:23:26,679\tINFO logging_progress.py:231 -- MapBatches(instant_source)->StreamingRepartition[num_rows_per_block=1,strict=False]: 512/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:33,179\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + "2026-07-14 23:23:26,680\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:33,180\tINFO logging_progress.py:231 -- Repartition: 32/32\n" + "2026-07-14 23:23:26,681\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 512/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:33,180\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 24.0B object store; 32 rows output\n" + "2026-07-14 23:23:26,682\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 2.2KiB object store; [0/512 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:33,181\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" + "2026-07-14 23:23:26,682\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 228/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:33,181\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 29/32\n" + "2026-07-14 23:23:26,683\tINFO logging_progress.py:233 -- Tasks: 189; Actors: 96; Queued blocks: 95 (760.0B); Resources: 96.0 CPU, 632.0B memory, 792.0B object store; [0/417 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:33,182\tINFO logging_progress.py:233 -- Tasks: 3; Actors: 3; Queued blocks: 0 (0.0B); Resources: 3.0 CPU, 176.0B object store; [0/32 objects local]\n" + "2026-07-14 23:23:26,683\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 225/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:33,183\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 10/32\n" + "2026-07-14 23:23:26,684\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 2 (16.0B); Resources: 0.0 CPU, 8.0B memory, 16.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:33,184\tINFO logging_progress.py:233 -- Tasks: 18; Actors: 11 (running=9, restarting=0, pending=2, active=9, idle=0, util=1.636, tasks_in_flight=18); Queued blocks: 1 (8.0B); Resources: 9.0 CPU, 40.0B memory, 80.0B object store; [0/28 objects local]\n" + "2026-07-14 23:23:26,684\tINFO logging_progress.py:192 -- ============================================\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:33,185\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 9/32\n" + "2026-07-14 23:23:36,758\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:33,185\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B memory, 16.0B object store\n" + "2026-07-14 23:23:36,760\tINFO logging_progress.py:225 -- Total Progress: 294/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:33,186\tINFO logging_progress.py:192 -- ============================================\n" + "2026-07-14 23:23:36,762\tINFO logging_progress.py:227 -- Active & requested resources: 96/128 CPU, 632.0B/1.9TiB memory, 2.5KiB/93.1GiB object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\u001b[33m(raylet)\u001b[0m [2026-07-14 21:52:35,196 E 2187411 2187442] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_21-51-26_677860_2186124 is over 95% full, available space: 0.0263901 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" + "2026-07-14 23:23:36,763\tINFO logging_progress.py:181 -- \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:42,813\tWARNING issue_detector_manager.py:69 -- \n", + "2026-07-14 23:23:36,764\tINFO logging_progress.py:231 -- MapBatches(instant_source)->StreamingRepartition[num_rows_per_block=1,strict=False]: 512/512\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:23:36,765\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:23:36,766\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 512/512\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:23:36,767\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 1.7KiB object store; [0/512 objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:23:36,767\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 295/512\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:23:36,767\tINFO logging_progress.py:233 -- Tasks: 191; Actors: 96; Queued blocks: 26 (208.0B); Resources: 96.0 CPU, 632.0B memory, 776.0B object store; [0/486 objects local]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:23:36,768\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 294/512\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:23:36,768\tINFO logging_progress.py:233 -- Tasks: 1; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B memory, 16.0B object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:23:36,769\tINFO logging_progress.py:192 -- ============================================\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:23:46,228\tWARNING issue_detector_manager.py:69 -- \n", "\n", - "Operator 'MapBatches(fast_sink)' uses 108.4MiB of memory per task on\n", + "Operator 'MapBatches(fast_sink)' uses 110.1MiB of memory per task on\n", "average, but Ray only requests 0.0B per task at the start of the\n", "pipeline.\n", "\n", - "To avoid out-of-memory errors, consider setting `memory=108.4MiB` in\n", + "To avoid out-of-memory errors, consider setting `memory=110.1MiB` in\n", "the appropriate function or method call. (This might be unnecessary if\n", "the number of concurrent tasks is low.)\n", "\n", @@ -976,266 +1436,301 @@ "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:42,815\tWARNING issue_detector_manager.py:96 -- Found 1 issues. To disable issue detection, run DataContext.get_current().issue_detectors_config.detectors = [].\n" + "2026-07-14 23:23:46,231\tWARNING issue_detector_manager.py:96 -- Found 1 issues. To disable issue detection, run DataContext.get_current().issue_detectors_config.detectors = [].\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:23:46,779\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:23:46,780\tINFO logging_progress.py:225 -- Total Progress: 351/512\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:23:46,781\tINFO logging_progress.py:227 -- Active & requested resources: 96/128 CPU, 632.0B/1.9TiB memory, 2.0KiB/93.1GiB object store\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:23:46,782\tINFO logging_progress.py:181 -- \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2026-07-14 23:23:46,783\tINFO logging_progress.py:231 -- MapBatches(instant_source)->StreamingRepartition[num_rows_per_block=1,strict=False]: 512/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:43,249\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + "2026-07-14 23:23:46,784\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:43,252\tINFO logging_progress.py:225 -- Total Progress: 19/32\n" + "2026-07-14 23:23:46,785\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 512/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:43,254\tINFO logging_progress.py:227 -- Active & requested resources: 11/16 CPU, 56.0B/1.9TiB memory, 200.0B/93.1GiB object store\n" + "2026-07-14 23:23:46,786\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 1.3KiB object store; [0/512 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:43,255\tINFO logging_progress.py:181 -- \n" + "2026-07-14 23:23:46,786\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 351/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:43,257\tINFO logging_progress.py:231 -- MapBatches(instant_source): 32/32\n" + "2026-07-14 23:23:46,786\tINFO logging_progress.py:233 -- Tasks: 161; Actors: 96; Queued blocks: 0 (0.0B); Resources: 96.0 CPU, 632.0B memory, 768.0B object store; [0/512 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:43,259\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + "2026-07-14 23:23:46,787\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 351/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:43,261\tINFO logging_progress.py:231 -- Repartition: 32/32\n" + "2026-07-14 23:23:46,787\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:43,262\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 32 rows output\n" + "2026-07-14 23:23:46,788\tINFO logging_progress.py:192 -- ============================================\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:43,263\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" + "2026-07-14 23:23:56,822\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:43,264\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 32/32\n" + "2026-07-14 23:23:56,824\tINFO logging_progress.py:225 -- Total Progress: 417/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:43,265\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 104.0B object store; [0/32 objects local]\n" + "2026-07-14 23:23:56,824\tINFO logging_progress.py:227 -- Active & requested resources: 94/128 CPU, 616.0B/1.9TiB memory, 1.5KiB/93.1GiB object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:43,265\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 19/32\n" + "2026-07-14 23:23:56,827\tINFO logging_progress.py:181 -- \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:43,266\tINFO logging_progress.py:233 -- Tasks: 13; Actors: 11; Queued blocks: 0 (0.0B); Resources: 11.0 CPU, 56.0B memory, 88.0B object store; [0/32 objects local]\n" + "2026-07-14 23:23:56,830\tINFO logging_progress.py:231 -- MapBatches(instant_source)->StreamingRepartition[num_rows_per_block=1,strict=False]: 512/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:43,267\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 19/32\n" + "2026-07-14 23:23:56,832\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:43,267\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B object store\n" + "2026-07-14 23:23:56,832\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 512/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:43,268\tINFO logging_progress.py:192 -- ============================================\n" + "2026-07-14 23:23:56,833\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 736.0B object store; [0/512 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\u001b[33m(raylet)\u001b[0m [2026-07-14 21:52:45,219 E 2187411 2187442] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_21-51-26_677860_2186124 is over 95% full, available space: 0.0261765 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" + "2026-07-14 23:23:56,833\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 420/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:53,348\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" + "2026-07-14 23:23:56,834\tINFO logging_progress.py:233 -- Tasks: 92; Actors: 93; Queued blocks: 0 (0.0B); Resources: 94.0 CPU, 616.0B memory, 736.0B object store; [0/512 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:53,351\tINFO logging_progress.py:225 -- Total Progress: 30/32\n" + "2026-07-14 23:23:56,834\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 420/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:53,353\tINFO logging_progress.py:227 -- Active & requested resources: 2/16 CPU, 8.0B/1.9TiB memory, 40.0B/93.1GiB object store\n" + "2026-07-14 23:23:56,834\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 32.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:53,354\tINFO logging_progress.py:181 -- \n" + "2026-07-14 23:23:56,834\tINFO logging_progress.py:192 -- ============================================\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:53,355\tINFO logging_progress.py:231 -- MapBatches(instant_source): 32/32\n" + "2026-07-14 23:24:06,897\tINFO logging_progress.py:174 -- ======= Running Dataset: dataset_5_0 =======\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:53,356\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" + "2026-07-14 23:24:06,907\tINFO logging_progress.py:225 -- Total Progress: 487/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:53,357\tINFO logging_progress.py:231 -- Repartition: 32/32\n" + "2026-07-14 23:24:06,920\tINFO logging_progress.py:227 -- Active & requested resources: 25/128 CPU, 136.0B/1.9TiB memory, 416.0B/93.1GiB object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:53,357\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store; 32 rows output\n" + "2026-07-14 23:24:06,922\tINFO logging_progress.py:181 -- \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:53,358\tINFO logging_progress.py:231 -- - Split Repartition: 32/1\n" + "2026-07-14 23:24:06,922\tINFO logging_progress.py:231 -- MapBatches(instant_source)->StreamingRepartition[num_rows_per_block=1,strict=False]: 512/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:53,359\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 32/32\n" + "2026-07-14 23:24:06,923\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 0.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:53,360\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 16.0B object store; [0/32 objects local]\n" + "2026-07-14 23:24:06,923\tINFO logging_progress.py:231 -- MapBatches(SlowActor): 512/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:53,360\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 30/32\n" + "2026-07-14 23:24:06,924\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 200.0B object store; [0/512 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:53,361\tINFO logging_progress.py:233 -- Tasks: 2; Actors: 2; Queued blocks: 0 (0.0B); Resources: 2.0 CPU, 8.0B memory, 16.0B object store; [0/32 objects local]\n" + "2026-07-14 23:24:06,924\tINFO logging_progress.py:231 -- MapBatches(SlowerActor): 487/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:53,362\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 30/32\n" + "2026-07-14 23:24:06,924\tINFO logging_progress.py:233 -- Tasks: 25; Actors: 25; Queued blocks: 0 (0.0B); Resources: 25.0 CPU, 136.0B memory, 200.0B object store; [0/512 objects local]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:53,362\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 8.0B object store\n" + "2026-07-14 23:24:06,925\tINFO logging_progress.py:231 -- MapBatches(fast_sink): 487/512\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:53,363\tINFO logging_progress.py:192 -- ============================================\n" + "2026-07-14 23:24:06,925\tINFO logging_progress.py:233 -- Tasks: 0; Actors: 0; Queued blocks: 0 (0.0B); Resources: 0.0 CPU, 16.0B object store\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\u001b[33m(raylet)\u001b[0m [2026-07-14 21:52:55,240 E 2187411 2187442] (raylet) file_system_monitor.cc:116: /tmp/ray/session_2026-07-14_21-51-26_677860_2186124 is over 95% full, available space: 0.0260582 GB; capacity: 8 GB. Object creation will fail if spilling is required.\n" + "2026-07-14 23:24:06,925\tINFO logging_progress.py:192 -- ============================================\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2026-07-14 21:52:58,244\tINFO streaming_executor.py:327 -- ✔️ Dataset dataset_5_0 execution finished in 75.67 seconds\n" + "2026-07-14 23:24:11,214\tINFO streaming_executor.py:327 -- ✔️ Dataset dataset_5_0 execution finished in 145.25 seconds\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Done: 32 items in 76.5s\n", - "Peak actors — slow: 12 slower: 11\n" + "Done: 512 items in 146.1s\n", + "Peak actors — slow: 96 slower: 96\n" ] } ], "source": [ "ray.shutdown()\n", - "ray.init(num_cpus=16)\n", + "ray.init(num_cpus=128, _temp_dir=\"/raid/weijiac/ray_tmp\")\n", "\n", "ctr = _Counter.options(name=\"_ctr\").remote()\n", "snapshots = []\n", @@ -1258,11 +1753,11 @@ "ds = (\n", " ray.data.from_items([{\"seed\": 0}])\n", " .map_batches(instant_source, batch_size=1)\n", - " .repartition(NUM_FILES)\n", + " .repartition(target_num_rows_per_block=1)\n", " .map_batches(SlowActor, batch_size=1, num_cpus=1,\n", - " compute=ActorPoolStrategy(min_size=1, max_size=NUM_FILES))\n", + " compute=ActorPoolStrategy(min_size=1, max_size=STARVED_AT))\n", " .map_batches(SlowerActor, batch_size=1, num_cpus=1,\n", - " compute=ActorPoolStrategy(min_size=1, max_size=NUM_FILES))\n", + " compute=ActorPoolStrategy(min_size=1, max_size=STARVED_AT))\n", " .map_batches(fast_sink, batch_size=1, num_cpus=0)\n", ")\n", "\n", @@ -1283,10 +1778,10 @@ "id": "c04", "metadata": { "execution": { - "iopub.execute_input": "2026-07-14T21:52:58.275549Z", - "iopub.status.busy": "2026-07-14T21:52:58.275151Z", - "iopub.status.idle": "2026-07-14T21:52:58.286702Z", - "shell.execute_reply": "2026-07-14T21:52:58.284536Z" + "iopub.execute_input": "2026-07-14T23:24:11.251067Z", + "iopub.status.busy": "2026-07-14T23:24:11.250762Z", + "iopub.status.idle": "2026-07-14T23:24:11.262451Z", + "shell.execute_reply": "2026-07-14T23:24:11.261105Z" } }, "outputs": [ @@ -1298,84 +1793,156 @@ " t slow_alloc slow_active slower_alloc slower_active cpu note\n", " ------------------------------------------------------------------------------------------\n", " 0.2s 0 0 0 0 2 \n", - " 1.2s 1 0 1 0 0 \n", - " 2.2s 1 1 1 0 3 \n", - " 3.2s 2 2 1 0 4 \n", - " 4.2s 3 3 1 0 5 \n", - " 5.2s 5 4 1 0 6 \n", - " 6.2s 5 5 1 0 7 \n", - " 7.2s 6 6 1 0 8 \n", - " 8.3s 6 6 1 0 8 \n", - " 9.3s 7 7 1 0 9 \n", - " 10.3s 7 7 1 0 10 \n", - " 11.3s 8 8 1 0 10 \n", - " 12.3s 9 9 1 0 12 \n", - " 13.3s 11 9 1 0 12 \n", - " 14.3s 11 11 1 0 13 \n", - " 15.3s 12 12 1 0 13 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 16.3s 12 12 1 0 13 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 17.3s 12 12 1 1 13 <- slower FIRST task slow=12 actors, shared stolen=8, slower budget=4\n", - " 18.3s 12 12 1 1 14 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 19.4s 12 12 1 1 14 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 20.4s 12 12 2 2 15 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 21.4s 12 12 2 2 15 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 22.4s 12 12 3 3 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 23.4s 12 12 3 3 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 24.4s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 25.4s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 26.4s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 27.4s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 28.4s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 29.4s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 30.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 31.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 32.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 33.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 34.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 35.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 36.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 37.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 38.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 39.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 40.5s 12 12 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 41.6s 12 11 4 4 0 <- STARVED: slower capped at reserved=4, util>=1.75 but Gate 3 blocks\n", - " 42.6s 11 11 4 4 0 \n", - " 43.6s 10 9 4 4 15 \n", - " 44.6s 9 9 5 5 15 \n", - " 45.6s 8 8 5 5 14 \n", - " 46.6s 8 8 6 6 15 \n", - " 47.6s 7 7 7 7 0 \n", - " 48.6s 6 6 7 7 15 \n", - " 49.6s 5 4 9 8 15 \n", - " 50.6s 3 3 9 9 14 \n", - " 51.6s 3 3 10 10 14 \n", - " 52.7s 2 2 11 11 13 \n", - " 53.7s 2 2 11 11 13 \n", - " 54.7s 1 1 11 11 12 \n", - " 55.7s 1 1 11 11 12 \n", - " 56.7s 0 0 11 11 11 \n", - " 57.7s 0 0 11 11 11 \n", - " 58.7s 0 0 11 11 11 \n", - " 59.7s 0 0 11 11 11 \n", - " 60.7s 0 0 11 11 11 \n", - " 61.7s 0 0 11 10 11 \n", - " 62.7s 0 0 8 8 8 \n", - " 63.7s 0 0 8 8 8 \n", - " 64.8s 0 0 7 7 7 \n", - " 65.8s 0 0 7 7 7 \n", - " 66.8s 0 0 7 7 7 \n", - " 67.8s 0 0 5 5 5 \n", - " 68.8s 0 0 5 5 5 \n", - " 69.8s 0 0 4 3 5 \n", - " 70.8s 0 0 2 2 2 \n", - " 71.8s 0 0 2 2 2 \n", - " 72.8s 0 0 2 2 2 \n", - " 73.8s 0 0 2 2 2 \n", - " 74.8s 0 0 1 1 1 \n", + " 1.2s 1 1 1 0 3 \n", + " 2.2s 2 2 1 0 4 \n", + " 3.2s 3 3 1 0 6 \n", + " 4.2s 4 4 1 0 7 \n", + " 5.2s 5 5 1 0 8 \n", + " 6.2s 6 6 1 0 9 \n", + " 7.2s 8 8 1 0 12 \n", + " 8.2s 11 11 1 0 15 \n", + " 9.3s 13 13 1 0 17 \n", + " 10.3s 15 15 1 0 20 \n", + " 11.3s 18 18 1 1 23 <- slower FIRST task slow=18 actors, shared stolen=0, slower budget=96\n", + " 12.3s 24 24 1 1 27 \n", + " 13.3s 29 28 2 2 33 \n", + " 14.3s 33 32 2 2 41 \n", + " 15.3s 39 39 3 3 48 \n", + " 16.3s 46 45 4 3 55 \n", + " 17.3s 54 53 5 5 65 \n", + " 18.3s 61 61 6 6 74 \n", + " 19.3s 71 71 7 7 85 \n", + " 20.3s 79 79 8 8 95 \n", + " 21.3s 88 87 10 9 105 \n", + " 22.4s 95 95 13 13 110 \n", + " 23.4s 95 95 15 15 113 \n", + " 24.4s 95 95 17 17 113 \n", + " 25.4s 95 95 17 17 113 \n", + " 26.4s 95 95 17 17 113 \n", + " 27.4s 95 95 17 17 113 \n", + " 28.4s 95 95 17 17 113 \n", + " 29.4s 95 95 17 17 113 \n", + " 30.4s 96 95 18 18 116 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 31.4s 96 96 23 21 120 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 32.4s 96 96 26 25 125 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 33.4s 96 96 26 26 126 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 34.5s 96 95 29 29 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 35.5s 96 96 30 30 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 36.5s 96 95 31 31 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 37.5s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 38.5s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 39.5s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 40.5s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 41.5s 96 95 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 42.5s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 43.5s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 44.5s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 45.5s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 46.5s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 47.5s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 48.6s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 49.6s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 50.6s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 51.6s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 52.6s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 53.6s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 54.6s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 55.6s 96 95 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 56.6s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 57.6s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 58.6s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 59.6s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 60.6s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 61.6s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 62.7s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 63.7s 96 96 32 32 0 <- STARVED: slower capped at reserved=32, shared pool fully stolen by slow upstream\n", + " 64.7s 91 90 32 32 0 \n", + " 65.7s 84 83 32 32 121 \n", + " 66.7s 77 75 37 37 119 \n", + " 67.7s 68 65 37 37 112 \n", + " 68.7s 59 53 43 43 106 \n", + " 69.7s 50 44 45 44 101 \n", + " 70.7s 41 28 51 51 96 \n", + " 71.7s 32 15 53 53 94 \n", + " 72.7s 23 6 59 58 88 \n", + " 73.7s 14 1 62 62 85 \n", + " 74.7s 5 0 69 68 82 \n", + " 75.7s 0 0 72 72 83 \n", + " 76.7s 0 0 80 80 90 \n", + " 77.7s 0 0 86 84 96 \n", + " 78.8s 0 0 94 94 96 \n", + " 79.8s 0 0 96 96 96 \n", + " 80.8s 0 0 96 96 96 \n", + " 81.8s 0 0 96 96 96 \n", + " 82.8s 0 0 96 96 96 \n", + " 83.8s 0 0 96 96 96 \n", + " 84.8s 0 0 96 96 96 \n", + " 85.8s 0 0 96 96 96 \n", + " 86.8s 0 0 96 96 96 \n", + " 87.8s 0 0 96 96 96 \n", + " 88.8s 0 0 96 96 96 \n", + " 89.8s 0 0 96 96 96 \n", + " 90.8s 0 0 96 96 96 \n", + " 91.9s 0 0 96 96 96 \n", + " 92.9s 0 0 96 96 96 \n", + " 93.9s 0 0 96 94 96 \n", + " 94.9s 0 0 96 96 96 \n", + " 95.9s 0 0 96 96 96 \n", + " 96.9s 0 0 96 96 96 \n", + " 97.9s 0 0 96 96 96 \n", + " 98.9s 0 0 96 96 96 \n", + " 99.9s 0 0 96 96 96 \n", + " 100.9s 0 0 96 96 96 \n", + " 101.9s 0 0 96 96 96 \n", + " 102.9s 0 0 96 96 96 \n", + " 104.0s 0 0 96 96 96 \n", + " 105.0s 0 0 96 96 96 \n", + " 106.0s 0 0 96 96 96 \n", + " 107.0s 0 0 96 96 96 \n", + " 108.0s 0 0 96 96 96 \n", + " 109.0s 0 0 96 96 96 \n", + " 110.0s 0 0 96 96 96 \n", + " 111.0s 0 0 96 96 96 \n", + " 112.0s 0 0 96 96 96 \n", + " 113.0s 0 0 96 96 96 \n", + " 114.0s 0 0 96 96 96 \n", + " 115.0s 0 0 96 96 96 \n", + " 116.1s 0 0 96 96 96 \n", + " 117.1s 0 0 96 96 96 \n", + " 118.1s 0 0 96 96 96 \n", + " 119.1s 0 0 96 96 96 \n", + " 120.1s 0 0 96 96 96 \n", + " 121.1s 0 0 96 96 96 \n", + " 122.1s 0 0 96 96 96 \n", + " 123.1s 0 0 96 96 96 \n", + " 124.1s 0 0 96 96 96 \n", + " 125.1s 0 0 96 96 96 \n", + " 126.2s 0 0 96 95 96 \n", + " 127.2s 0 0 96 96 96 \n", + " 128.2s 0 0 96 96 96 \n", + " 129.2s 0 0 96 96 96 \n", + " 130.2s 0 0 96 96 96 \n", + " 131.2s 0 0 92 90 92 \n", + " 132.2s 0 0 88 87 88 \n", + " 133.2s 0 0 82 81 83 \n", + " 134.2s 0 0 77 76 78 \n", + " 135.2s 0 0 71 69 71 \n", + " 136.2s 0 0 63 61 64 \n", + " 137.2s 0 0 54 49 55 \n", + " 138.2s 0 0 45 41 46 \n", + " 139.2s 0 0 35 30 36 \n", + " 140.3s 0 0 26 26 27 \n", + " 141.3s 0 0 24 23 25 \n", + " 142.3s 0 0 16 16 17 \n", + " 143.3s 0 0 12 10 13 \n", + " 144.3s 0 0 4 4 5 \n", + " 145.3s 0 0 1 0 1 \n", "\n", - "SlowActor peak: 12 actors (exhausts shared pool at >= 12)\n", - "SlowerActor during starvation: 4 actors (reserved=4, potential=12)\n", - "Throughput loss on critical path: 1.20 vs 0.40 files/sec => 3x slower\n" + "SlowActor peak: 96 actors (shared pool exhausted at >= 96 actors)\n", + "SlowerActor during shared pool exhaustion: 32 actors\n", + " => capped at reserved=32 instead of optimal fair allocation=96\n", + " => optimal profile: SlowActor=32 + SlowerActor=96 = 128 CPUs (= budget, feasible)\n", + "SlowerActor stage capacity: 6.40 files/sec (optimal fair) vs 2.13 files/sec (starved) => 3x capacity loss on bottleneck stage\n" ] } ], @@ -1403,7 +1970,7 @@ " slower_started = True\n", " note = f\"<- slower FIRST task slow={sl_a} actors, shared stolen={stolen}, slower budget={sr_budget}\"\n", " elif sl_a >= STARVED_AT and sr_a <= RESERVED:\n", - " note = f\"<- STARVED: slower capped at reserved={RESERVED}, util>=1.75 but Gate 3 blocks\"\n", + " note = f\"<- STARVED: slower capped at reserved={RESERVED}, shared pool fully stolen by slow upstream\"\n", "\n", " print(f\" {ts:5.1f}s {sl_a:>10d} {sl_t:>11d} \"\n", " f\"{sr_a:>12d} {sr_t:>13d} {cpu:>3.0f} {note}\")\n", @@ -1415,14 +1982,14 @@ "sr_starved = [s[1].get(\"slower\", 0) for s in snapshots if s[1].get(\"slow\", 0) >= STARVED_AT]\n", "peak_sr_starved = max(sr_starved, default=0)\n", "\n", - "print(f\"SlowActor peak: {peak_slow} actors (exhausts shared pool at >= {STARVED_AT})\")\n", - "print(f\"SlowerActor during starvation: {peak_sr_starved} actors \"\n", - " f\"(reserved={RESERVED}, potential={STARVED_AT})\")\n", - "potential_tput = STARVED_AT / SLOWER_DELAY\n", - "actual_tput = max(1, peak_sr_starved) / SLOWER_DELAY\n", - "print(f\"Throughput loss on critical path: \"\n", - " f\"{potential_tput:.2f} vs {actual_tput:.2f} files/sec\"\n", - " f\" => {int(round(potential_tput / actual_tput))}x slower\")\n" + "print(f\"SlowActor peak: {peak_slow} actors (shared pool exhausted at >= {STARVED_AT} actors)\")\n", + "print(f\"SlowerActor during shared pool exhaustion: {peak_sr_starved} actors\")\n", + "print(f\" => capped at reserved={RESERVED} instead of optimal fair allocation={STARVED_AT}\")\n", + "print(f\" => optimal profile: SlowActor={RESERVED} + SlowerActor={STARVED_AT} = {RESERVED+STARVED_AT} CPUs (= budget, feasible)\")\n", + "fair_tput = STARVED_AT / SLOWER_DELAY\n", + "actual_tput = max(1, peak_sr_starved) / SLOWER_DELAY\n", + "print(f\"SlowerActor stage capacity: {fair_tput:.2f} files/sec (optimal fair) vs {actual_tput:.2f} files/sec (starved)\"\n", + " f\" => {int(round(fair_tput / actual_tput))}x capacity loss on bottleneck stage\")\n" ] } ],