wehub-resource-sync
33 lines
1.8 KiB
JSON
33 lines
1.8 KiB
JSON
{
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"_dashboard_memory_usage_mb": 458.919936,
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"_dashboard_test_success": true,
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"_peak_memory": 15.4,
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"_peak_process_memory": "PID\tMEM\tCOMMAND\n218\t1.59GiB\t/home/ray/anaconda3/lib/python3.8/site-packages/ray/core/src/ray/gcs/gcs_server --log_dir=/tmp/ray/s\n1189\t0.84GiB\tpython distributed/test_many_actors.py\n325\t0.31GiB\t/home/ray/anaconda3/bin/python /home/ray/anaconda3/lib/python3.8/site-packages/ray/dashboard/dashboa\n415\t0.1GiB\t/home/ray/anaconda3/bin/python -u /home/ray/anaconda3/lib/python3.8/site-packages/ray/dashboard/agen\n61\t0.09GiB\t/home/ray/anaconda3/bin/python /home/ray/anaconda3/bin/anyscale session web_terminal_server --deploy\n909\t0.09GiB\tray::JobSupervisor\n1357\t0.08GiB\tray::DashboardTester.run\n1289\t0.07GiB\tray::MemoryMonitorActor.run\n54\t0.06GiB\t/home/ray/anaconda3/bin/python /home/ray/anaconda3/bin/jupyter-lab --allow-root --ip=127.0.0.1 --no-\n324\t0.05GiB\t/home/ray/anaconda3/bin/python -m ray.util.client.server --address=10.0.20.59:6379 --host=0.0.0.0 --",
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"actors_per_second": 801.4844694307048,
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"num_actors": 10000,
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"perf_metrics": [
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{
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"perf_metric_name": "actors_per_second",
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"perf_metric_type": "THROUGHPUT",
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"perf_metric_value": 801.4844694307048
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},
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{
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"perf_metric_name": "dashboard_p50_latency_ms",
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"perf_metric_type": "LATENCY",
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"perf_metric_value": 26.666
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},
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{
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"perf_metric_name": "dashboard_p95_latency_ms",
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"perf_metric_type": "LATENCY",
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"perf_metric_value": 1234.094
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},
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{
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"perf_metric_name": "dashboard_p99_latency_ms",
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"perf_metric_type": "LATENCY",
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"perf_metric_value": 4854.945
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}
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],
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"success": "1",
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"time": 12.476848125457764
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}
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