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https://issues.apache.org/jira/browse/SPARK-22784?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16290745#comment-16290745
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Apache Spark commented on SPARK-22784:
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User 'MikhailErofeev' has created a pull request for this issue:
https://github.com/apache/spark/pull/19978
> Configure reading buffer size in Spark History Server
> -----------------------------------------------------
>
> Key: SPARK-22784
> URL: https://issues.apache.org/jira/browse/SPARK-22784
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Affects Versions: 2.2.1
> Reporter: Mikhail Erofeev
> Priority: Minor
> Attachments: replay-baseline.svg
>
>
> Motivation:
> Our Spark History Server spends most of the backfill time inside
> BufferedReader and StringBuffer. It happens because average line size of our
> events is ~1.500.000 chars (due to a lot of partitions and iterations),
> whereas the default buffer size is 2048 bytes. See the attached flame graph.
> Implementation:
> I've added logging of spent time and line size for each job.
> Parametrised ReplayListenerBus with a new buffer size parameter.
> Measured the best buffer size. x20 of the average line size (30mb) gives 32%
> speedup in a local test.
> Result:
> Backfill of Spark History and reading to the cache will be up to 30% faster
> after tuning.
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