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https://issues.apache.org/jira/browse/SPARK-34898?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17310515#comment-17310515
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Apache Spark commented on SPARK-34898:
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User 'AngersZhuuuu' has created a pull request for this issue:
https://github.com/apache/spark/pull/31992
> Send ExecutorMetricsUpdate EventLog appropriately
> -------------------------------------------------
>
> Key: SPARK-34898
> URL: https://issues.apache.org/jira/browse/SPARK-34898
> Project: Spark
> Issue Type: Sub-task
> Components: Spark Core
> Affects Versions: 3.2.0
> Reporter: angerszhu
> Priority: Major
>
> In current EventLoggingListener, we won't write
> SparkListenerExecutorMetricsUpdate message at all
> {code:java}
> override def onExecutorMetricsUpdate(event:
> SparkListenerExecutorMetricsUpdate): Unit = {
> if (shouldLogStageExecutorMetrics) {
> event.executorUpdates.foreach { case (stageKey1, newPeaks) =>
> liveStageExecutorMetrics.foreach { case (stageKey2, metricsPerExecutor)
> =>
> // If the update came from the driver, stageKey1 will be the dummy
> key (-1, -1),
> // so record those peaks for all active stages.
> // Otherwise, record the peaks for the matching stage.
> if (stageKey1 == DRIVER_STAGE_KEY || stageKey1 == stageKey2) {
> val metrics = metricsPerExecutor.getOrElseUpdate(
> event.execId, new ExecutorMetrics())
> metrics.compareAndUpdatePeakValues(newPeaks)
> }
> }
> }
> }
> }
> {code}
> It cause we can't get driver executor peakMemoryMetrics in SHS. We can got
> executor's since it will update with TaskEnd events.
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