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https://issues.apache.org/jira/browse/SPARK-36252?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17554351#comment-17554351
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Apache Spark commented on SPARK-36252:
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User 'jhu-chang' has created a pull request for this issue:
https://github.com/apache/spark/pull/36872
> Add log files rolling policy for driver running in cluster mode with spark
> standalone cluster
> ---------------------------------------------------------------------------------------------
>
> Key: SPARK-36252
> URL: https://issues.apache.org/jira/browse/SPARK-36252
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Affects Versions: 3.1.2
> Reporter: Jack Hu
> Priority: Major
>
> For a long running driver in cluster mode, there is no rolling policy, the
> log (stdout/stderr) may accupy lots of space, user needs an external tool to
> clean the old logs, it's not user friendly.
> For executor, following 5 configurations is used to control the log file
> rolling policy:
> {code:java}
> spark.executor.logs.rolling.maxRetainedFiles
> spark.executor.logs.rolling.enableCompression
> spark.executor.logs.rolling.maxSize
> spark.executor.logs.rolling.strategy
> spark.executor.logs.rolling.time.interval
> {code}
> For driver running in cluster mode:
> 1. reuse the executor settings
> 2. similar to executor: add following configurations (only works for
> stderr/stdout for driver in cluster mode)
> {code:java}
> spark.driver.logs.rolling.maxRetainedFiles
> spark.driver.logs.rolling.enableCompression
> spark.driver.logs.rolling.maxSize
> spark.driver.logs.rolling.strategy
> spark.driver.logs.rolling.time.interval
> {code}
> #2 seems better, do you agree?
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