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https://issues.apache.org/jira/browse/SPARK-47208?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Thomas Graves reassigned SPARK-47208:
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Assignee: Joao Correia
> Allow overriding base overhead memory
> -------------------------------------
>
> Key: SPARK-47208
> URL: https://issues.apache.org/jira/browse/SPARK-47208
> Project: Spark
> Issue Type: New Feature
> Components: Kubernetes, Spark Core, YARN
> Affects Versions: 3.5.1
> Reporter: Joao Correia
> Assignee: Joao Correia
> Priority: Major
> Labels: pull-request-available
> Fix For: 4.0.0
>
>
> We can already select the desired overhead memory directly via the
> _'spark.driver/executor.memoryOverhead'_ flags, however, if that flag is not
> present the overhead memory calculation goes as follows:
> {code:java}
> overhead_memory = Max(384, 'spark.driver/executor.memory' *
> 'spark.driver/executor.memoryOverheadFactor')
> where the 'memoryOverheadFactor' flag defaults to 0.1{code}
> There are certain times where being able to override the 384Mb minimum
> directly can be beneficial. We may have a scenario where a lot of off-heap
> operations are performed (ex: using package managers/native
> compression/decompression) where we don't have a need for a large JVM heap
> but we may still need a signficant amount of memory in the spark node.
> Using the '{_}memoryOverheadFactor{_}' flag may not prove appropriate. Since
> we may not want the overhead allocation to directly scale with JVM memory, as
> a cost saving/resource limitation problem.
> As such, I propose the addition of a
> 'spark.driver/executor.minMemoryOverhead' flag, which can be used to override
> the 384Mib value used in the overhead calculation.
> The memory overhead calculation will now be :
> {code:java}
> min_memory =
> sparkConf.get('spark.driver/executor.minMemoryOverhead').getOrElse(384)
> overhead_memory = Max(min_memory, 'spark.driver/executor.memory' *
> 'spark.driver/executor.memoryOverheadFactor'){code}
> PR: https://github.com/apache/spark/pull/45240
>
>
>
>
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