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add pytest-benchmarks:ubuntu-22.04,psql_dos benchmark result for 3404c01
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github-action-benchmark committed Jun 4, 2024
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185 changes: 184 additions & 1 deletion dev/bench/ubuntu-22.04/psql_dos/data.js
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window.BENCHMARK_DATA = {
"lastUpdate": 1717494070231,
"lastUpdate": 1717511586121,
"repoUrl": "https://github.com/aiidateam/aiida-core",
"xAxis": "id",
"oneChartGroups": [],
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"extra": "mean: 25.297 msec\nrounds: 100"
}
]
},
{
"cpu": {
"speed": "3.24",
"cores": 4,
"physicalCores": 2,
"processors": 1
},
"extra": {
"pythonVersion": "3.10.14",
"metadata": "postgres:12.14, rabbitmq:3.8.14-management"
},
"commit": {
"id": "3404c01925da941c08f246e231b6587f53ce445b",
"message": "Devops: Fix the Docker builds (#6445)\n\nIn a recent commit, the `aiida-prepare.sh` startup script was updated to\r\nswitch from the deprecated `verdi quicksetup` to `verdi presto`. This\r\nleft the builds broken since there were a few bugs in the implementation\r\nof `verdi presto`, but also because the behavior of the commands is not\r\nidentical:\r\n\r\n* The option `--profile` for `verdi quicksetup` was not correctly\r\n renamed to `--profile-name` for `verdi presto`.\r\n* The `detect_postgres_config` utility returned the database hostname\r\n under the key `database_host` instead of `database_hostname`.\r\n* The `detect_rabbitmq_config` utility returned a dictionary whose keys\r\n were not prefixed with `broker_` as is expected by the implementation\r\n of the `RabbitmqBroker` plugin.\r\n* The `detect_rabbitmq_config` utility now checks an environment\r\n variable for each connection parameter before resorting to the default.\r\n This is necessary to allow the `aiida-core-base` to define the hostname\r\n of RabbitMQ which is `messaging` instead of the default `locahost`.\r\n The `verdi presto` command intentionally does not expose options to\r\n configure RabbitMQ connection parameters.\r\n* The `aiida-core-base` case now defines the hostnames of the PSQL and\r\n RabbitMQ services through environment variables as they are set to\r\n the key in the docker compose file, which are `database` and\r\n `messaging`, respectively, instead of `localhost`.\r\n* The `_docker_service_wait` fixture now prints the log output captured\r\n from `docker compose` if the health check times out or fails.\r\n* The healthcheck for the RabbitMQ service is enabled in the docker\r\n compose of `aiida-core-base` and the healthchecks for both the PSQL\r\n and RabbitMQ services are corrected. These checks are necessary to\r\n ensure the `aiida-prepare.sh` is not called before they are up. If\r\n called before, `verdi presto` is called before the services are up and\r\n the profile creation will fail or will be configured without broker.\r\n* The healthchecks for `aiida-core-base` do not work for the case of\r\n `aiida-core-with-services` as there the services are part of the main\r\n container. Here the `aiida-prepare.sh` is called as soon as the\r\n services startup scripts have started, but they don't have a health\r\n check. Therefore, a `sleep` is added before `verdi presto` is called.\r\n There should be a better solution for this using s6, but this will\r\n have to do for the moment.",
"timestamp": "2024-06-04T16:24:51+02:00",
"url": "https://github.com/aiidateam/aiida-core/commit/3404c01925da941c08f246e231b6587f53ce445b",
"distinct": true,
"tree_id": "310ee9718c748cbeedc80096f1e950feada3a35f"
},
"date": 1717511581344,
"benches": [
{
"name": "tests/benchmark/test_archive.py::test_export[no-objects]",
"value": 2.9630492293977513,
"unit": "iter/sec",
"range": "stddev: 0.066848",
"group": "import-export",
"extra": "mean: 337.49 msec\nrounds: 12"
},
{
"name": "tests/benchmark/test_archive.py::test_export[with-objects]",
"value": 2.9358216973120967,
"unit": "iter/sec",
"range": "stddev: 0.066389",
"group": "import-export",
"extra": "mean: 340.62 msec\nrounds: 12"
},
{
"name": "tests/benchmark/test_archive.py::test_import[no-objects]",
"value": 4.349357375923589,
"unit": "iter/sec",
"range": "stddev: 0.0046121",
"group": "import-export",
"extra": "mean: 229.92 msec\nrounds: 12"
},
{
"name": "tests/benchmark/test_archive.py::test_import[with-objects]",
"value": 3.8309788257718997,
"unit": "iter/sec",
"range": "stddev: 0.0086386",
"group": "import-export",
"extra": "mean: 261.03 msec\nrounds: 12"
},
{
"name": "tests/benchmark/test_engine.py::test_workchain_local[basic-loop]",
"value": 3.5239148124774786,
"unit": "iter/sec",
"range": "stddev: 0.016148",
"group": "engine",
"extra": "mean: 283.78 msec\nrounds: 10"
},
{
"name": "tests/benchmark/test_engine.py::test_workchain_local[serial-wc-loop]",
"value": 0.7326891717801178,
"unit": "iter/sec",
"range": "stddev: 0.076374",
"group": "engine",
"extra": "mean: 1.3648 sec\nrounds: 10"
},
{
"name": "tests/benchmark/test_engine.py::test_workchain_local[threaded-wc-loop]",
"value": 0.7575312624275659,
"unit": "iter/sec",
"range": "stddev: 0.14360",
"group": "engine",
"extra": "mean: 1.3201 sec\nrounds: 10"
},
{
"name": "tests/benchmark/test_engine.py::test_workchain_local[serial-calcjob-loop]",
"value": 0.19807516684082782,
"unit": "iter/sec",
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"group": "engine",
"extra": "mean: 5.0486 sec\nrounds: 10"
},
{
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"value": 0.21441002422506944,
"unit": "iter/sec",
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"group": "engine",
"extra": "mean: 4.6640 sec\nrounds: 10"
},
{
"name": "tests/benchmark/test_engine.py::test_workchain_daemon[basic-loop]",
"value": 2.3568778884627495,
"unit": "iter/sec",
"range": "stddev: 0.0091059",
"group": "engine",
"extra": "mean: 424.29 msec\nrounds: 10"
},
{
"name": "tests/benchmark/test_engine.py::test_workchain_daemon[serial-wc-loop]",
"value": 0.4863401334251351,
"unit": "iter/sec",
"range": "stddev: 0.068362",
"group": "engine",
"extra": "mean: 2.0562 sec\nrounds: 10"
},
{
"name": "tests/benchmark/test_engine.py::test_workchain_daemon[threaded-wc-loop]",
"value": 0.529324602931475,
"unit": "iter/sec",
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"group": "engine",
"extra": "mean: 1.8892 sec\nrounds: 10"
},
{
"name": "tests/benchmark/test_engine.py::test_workchain_daemon[serial-calcjob-loop]",
"value": 0.14858106785022207,
"unit": "iter/sec",
"range": "stddev: 0.11990",
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"extra": "mean: 6.7303 sec\nrounds: 10"
},
{
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"value": 0.15841744849546815,
"unit": "iter/sec",
"range": "stddev: 0.16074",
"group": "engine",
"extra": "mean: 6.3124 sec\nrounds: 10"
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{
"name": "tests/benchmark/test_nodes.py::test_store_backend",
"value": 460.30126409750807,
"unit": "iter/sec",
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"extra": "mean: 2.1725 msec\nrounds: 263"
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"name": "tests/benchmark/test_nodes.py::test_store",
"value": 74.71772873057685,
"unit": "iter/sec",
"range": "stddev: 0.00072526",
"group": "node",
"extra": "mean: 13.384 msec\nrounds: 100"
},
{
"name": "tests/benchmark/test_nodes.py::test_store_with_object",
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"unit": "iter/sec",
"range": "stddev: 0.00093729",
"group": "node",
"extra": "mean: 18.808 msec\nrounds: 100"
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{
"name": "tests/benchmark/test_nodes.py::test_delete_backend",
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"unit": "iter/sec",
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"group": "node",
"extra": "mean: 3.4631 msec\nrounds: 100"
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{
"name": "tests/benchmark/test_nodes.py::test_delete",
"value": 43.787422441654996,
"unit": "iter/sec",
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"group": "node",
"extra": "mean: 22.838 msec\nrounds: 100"
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"name": "tests/benchmark/test_nodes.py::test_delete_with_object",
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"unit": "iter/sec",
"range": "stddev: 0.033010",
"group": "node",
"extra": "mean: 28.131 msec\nrounds: 100"
}
]
}
]
}
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