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Posted to commits@cassandra.apache.org by "Blake Eggleston (Jira)" <ji...@apache.org> on 2019/12/10 23:31:00 UTC

[jira] [Updated] (CASSANDRA-15388) Add compaction allocation measurement test to support compaction gc optimization.

     [ https://issues.apache.org/jira/browse/CASSANDRA-15388?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Blake Eggleston updated CASSANDRA-15388:
----------------------------------------
    Reviewers: Benedict Elliott Smith

> Add compaction allocation measurement test to support compaction gc optimization. 
> ----------------------------------------------------------------------------------
>
>                 Key: CASSANDRA-15388
>                 URL: https://issues.apache.org/jira/browse/CASSANDRA-15388
>             Project: Cassandra
>          Issue Type: Sub-task
>          Components: Local/Compaction
>            Reporter: Blake Eggleston
>            Assignee: Blake Eggleston
>            Priority: Normal
>             Fix For: 4.0
>
>
> This adds a test that is able to quickly and accurately measure the effect of potential gc optimizations against a wide range of (synthetic) compaction workloads. This test accurately measures allocation rates from 16 workloads in less that 2 minutes.
> This test uses google’s {{java-allocation-instrumenter}} agent to measure the workloads. Measurements using this agent are very accurate and pretty repeatable from run to run, with most variance being negligible (1-2 bytes per partition), although workloads with larger but fewer partitions vary a bit more (still less that 0.03%).
> The thinking behind this patch is that with compaction, we’re generally interested in the memory allocated per partition, since garbage scales more or less linearly with the number of partitions compacted. So measuring allocation from a small number of partitions that otherwise represent real world use cases is a good enough approximation.
> In addition to helping with compaction optimizations, this test could be used as a template for future optimization work. This pattern could also be used to set allocation limits on workloads/operations and fail CI if the allocation behavior changes past some threshold. 



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