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https://issues.apache.org/jira/browse/SPARK-48628?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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ASF GitHub Bot updated SPARK-48628:
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Labels: pull-request-available (was: )
> Add task peak on/off heap execution memory metrics
> --------------------------------------------------
>
> Key: SPARK-48628
> URL: https://issues.apache.org/jira/browse/SPARK-48628
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Affects Versions: 4.0.0
> Reporter: Ziqi Liu
> Priority: Major
> Labels: pull-request-available
>
> Currently there is no task on/off heap execution memory metrics. There is a
> [peakExecutionMemory|https://github.com/apache/spark/blob/3cd35f8cb6462051c621cf49de54b9c5692aae1d/core/src/main/scala/org/apache/spark/executor/TaskMetrics.scala#L114]
> metrics, however, the semantic is a confusing: it only cover the execution
> memory used by shuffle/join/aggregate/sort, which is accumulated in specific
> operators.
>
> We can easily maintain the whole task-level peak memory in TaskMemoryManager,
> assuming *acquireExecutionMemory* is the only one narrow waist for acquiring
> execution memory.
>
> Also it's nice to cleanup/deprecate that poorly-named `peakExecutionMemory`.
>
> Creating two followup sub tickets:
> * https://issues.apache.org/jira/browse/SPARK-48788 :accumulate task metrics
> in stage, and display in Spark UI
> * https://issues.apache.org/jira/browse/SPARK-48789 : deprecate
> `peakExecutionMemory` once we have replacement for it.
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