many_tasks.json

{
    "_dashboard_memory_usage_mb": 687.808512,
    "_dashboard_test_success": true,
    "_peak_memory": 16.12,
    "_peak_process_memory": "PID\tMEM\tCOMMAND\n202\t1.64GiB\t/home/ray/anaconda3/lib/python3.8/site-packages/ray/core/src/ray/gcs/gcs_server --log_dir=/tmp/ray/s\n868\t0.74GiB\tpython distributed/test_many_tasks.py --num-tasks=10000\n303\t0.73GiB\t/home/ray/anaconda3/bin/python /home/ray/anaconda3/lib/python3.8/site-packages/ray/dashboard/dashboa\n1046\t0.08GiB\tray::DashboardTester.run\n388\t0.07GiB\t/home/ray/anaconda3/bin/python -u /home/ray/anaconda3/lib/python3.8/site-packages/ray/_private/runti\n716\t0.07GiB\tray::JobSupervisor\n1082\t0.06GiB\tray::StateAPIGeneratorActor.start\n70\t0.06GiB\t/home/ray/anaconda3/bin/python /home/ray/anaconda3/bin/jupyter-lab --allow-root --ip=127.0.0.1 --no-\n990\t0.06GiB\tray::MemoryMonitorActor.run\n386\t0.06GiB\t/home/ray/anaconda3/bin/python -u /home/ray/anaconda3/lib/python3.8/site-packages/ray/dashboard/agen",
    "num_tasks": 10000,
    "perf_metrics": [
        {
            "perf_metric_name": "tasks_per_second",
            "perf_metric_type": "THROUGHPUT",
            "perf_metric_value": 443.65590223624235
        },
        {
            "perf_metric_name": "used_cpus_by_deadline",
            "perf_metric_type": "THROUGHPUT",
            "perf_metric_value": 2500.0
        },
        {
            "perf_metric_name": "dashboard_p50_latency_ms",
            "perf_metric_type": "LATENCY",
            "perf_metric_value": 7.346
        },
        {
            "perf_metric_name": "dashboard_p95_latency_ms",
            "perf_metric_type": "LATENCY",
            "perf_metric_value": 7335.859
        },
        {
            "perf_metric_name": "dashboard_p99_latency_ms",
            "perf_metric_type": "LATENCY",
            "perf_metric_value": 14570.201
        }
    ],
    "success": "1",
    "tasks_per_second": 443.65590223624235,
    "time": 322.539990901947,
    "used_cpus": 2500.0
}