[jira] [Updated] (SPARK-50421) Executor memory config is incorrect when multiple stage level resource profiles works

["ASF GitHub Bot (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-50421?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

ASF GitHub Bot updated SPARK-50421:
-----------------------------------
    Labels: pull-request-available  (was: )

> Executor memory config is incorrect when multiple stage level resource profiles works
> -------------------------------------------------------------------------------------
>
>                 Key: SPARK-50421
>                 URL: https://issues.apache.org/jira/browse/SPARK-50421
>             Project: Spark
>          Issue Type: Bug
>          Components: Scheduler, YARN
>    Affects Versions: 3.1.3, 3.2.4, 3.3.4, 3.4.4, 3.5.3
>            Reporter: Terry Wang
>            Priority: Major
>              Labels: pull-request-available
>
> https://issues.apache.org/jira/browse/SPARK-27495 has imported a great feature to help adjust stage's level resource profile(abbv rp), we are observing some config is not as expected when multiple resource profile works. 
> When one stage assigned rp2 different with default rp, the `UnifiedMemoryManager` will still get old conf as the default rp, which will cause  maxOffHeapMemory is still the old value!
> {code:scala}
> protected[this] val maxOffHeapMemory = conf.get(MEMORY_OFFHEAP_SIZE)
> {code}



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