@@ -11,7 +11,7 @@ kinds of benchmarks relevant to pandas:
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pandas benchmarks are implemented in the [ asv_bench] ( https://github.com/pandas-dev/pandas/tree/main/asv_bench )
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directory of our repository. The benchmarks are implemented for the
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- [ airspeed velocity] ( https://asv.readthedocs.io/en/v0.6.1 / ) (asv for short) framework.
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+ [ airspeed velocity] ( https://asv.readthedocs.io/en/latest / ) (asv for short) framework.
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The benchmarks can be run locally by any pandas developer. This can be done
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with the ` asv run ` command, and it can be useful to detect if local changes have
@@ -22,53 +22,15 @@ More information on running the performance test suite is found
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Note that benchmarks are not deterministic, and running in different hardware or
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running in the same hardware with different levels of stress have a big impact in
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the result. Even running the benchmarks with identical hardware and almost identical
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- conditions produces significant differences when running the same exact code.
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+ conditions can produce significant differences when running the same exact code.
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- ## pandas benchmarks servers
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+ ## Automated benchmark runner
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- We currently have two physical servers running the benchmarks of pandas for every
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- (or almost every) commit to the ` main ` branch. The servers run independently from
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- each other. The original server has been running for a long time, and it is physically
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- located with one of the pandas maintainers. The newer server is in a datacenter
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- kindly sponsored by [ OVHCloud] ( https://www.ovhcloud.com/ ) . More information about
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- pandas sponsors, and how your company can support the development of pandas is
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- available at the [ pandas sponsors] ({{ base_url }}about/sponsors.html) page.
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+ The [ asv-runner] ( https://github.com/pandas-dev/asv-runner/ ) repository automatically runs the pandas asv benchmark suite
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+ for every (or almost every) commit to the ` main ` branch. It is run on GitHub actions.
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+ See the linked repository for more details. The results are available at:
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- Results of the benchmarks are available at:
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-
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- - GitHub Actions results: [ asv] ( https://pandas-dev.github.io/asv-runner/ )
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- - OVH server: [ asv] ( https://pandas.pydata.org/benchmarks/asv/ )
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-
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- ### Original server configuration
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-
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- The machine can be configured with the Ansible playbook in
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- [ tomaugspurger/asv-runner] ( https://github.com/tomaugspurger/asv-runner ) .
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- The results are published to another GitHub repository,
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- [ tomaugspurger/asv-collection] ( https://github.com/tomaugspurger/asv-collection ) .
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-
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- The benchmarks are scheduled by [ Airflow] ( https://airflow.apache.org/ ) .
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- It has a dashboard for viewing and debugging the results.
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- You’ll need to setup an SSH tunnel to view them:
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-
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- ```
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- ssh -L 8080:localhost:8080 [email protected]
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- ```
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-
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- ### OVH server configuration
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-
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- The server used to run the benchmarks has been configured to reduce system
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- noise and maximize the stability of the benchmarks times.
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-
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- The details on how the server is configured can be found in the
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- [ pandas-benchmarks repository] ( https://github.com/pandas-dev/pandas-benchmarks ) .
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- There is a quick summary here:
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-
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- - CPU isolation: Avoid user space tasks to execute in the same CPU as benchmarks, possibly interrupting them during the execution (include all virtual CPUs using a physical core)
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- - NoHZ: Stop the kernel tick that enables context switching in the isolated CPU
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- - IRQ affinity: Ban benchmarks CPU to avoid many (but not all) kernel interruption in the isolated CPU
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- - TurboBoost: Disable CPU scaling based on high CPU demand
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- - P-States: Use "performance" governor to disable P-States and CPU frequency changes based on them
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- - C-States: Set C-State to 0 and disable changes to avoid slower CPU after system inactivity
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+ https://pandas-dev.github.io/asv-runner/
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## Community benchmarks
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