many_tasks.json 1.3 KB

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  1. {
  2. "_peak_memory": 2.95,
  3. "_peak_process_memory": "PID\tMEM\tCOMMAND\n291\t1.11GiB\t/home/ray/anaconda3/lib/python3.7/site-packages/ray/core/src/ray/gcs/gcs_server --log_dir=/tmp/ray/s\n2033\t0.74GiB\tpython distributed/test_many_tasks.py --num-tasks=10000\n415\t0.45GiB\t/home/ray/anaconda3/bin/python /home/ray/anaconda3/lib/python3.7/site-packages/ray/dashboard/dashboa\n47\t0.09GiB\t/home/ray/anaconda3/bin/python /home/ray/anaconda3/bin/anyscale session web_terminal_server --deploy\n2240\t0.07GiB\tray::StateAPIGeneratorActor.start\n717\t0.06GiB\t/home/ray/anaconda3/bin/python -u /home/ray/anaconda3/lib/python3.7/site-packages/ray/dashboard/agen\n2169\t0.06GiB\tray::MemoryMonitorActor.run\n44\t0.06GiB\t/home/ray/anaconda3/bin/python /home/ray/anaconda3/bin/jupyter-notebook --NotebookApp.token=aph0_Ckg\n342\t0.05GiB\t/home/ray/anaconda3/bin/python -m ray.util.client.server --address=172.31.171.196:9031 --host=0.0.0.\n615\t0.05GiB\t/home/ray/anaconda3/bin/python -u /home/ray/anaconda3/lib/python3.7/site-packages/ray/_private/log_m",
  4. "num_tasks": 10000,
  5. "perf_metrics": [
  6. {
  7. "perf_metric_name": "tasks_per_second",
  8. "perf_metric_type": "THROUGHPUT",
  9. "perf_metric_value": 27.08832351001015
  10. }
  11. ],
  12. "success": "1",
  13. "tasks_per_second": 27.08832351001015,
  14. "time": 669.162750005722
  15. }