[jira] [Assigned] (SPARK-34898) Send ExecutorMetricsUpdate EventLog appropriately

["Apache Spark (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-34898?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Apache Spark reassigned SPARK-34898:
------------------------------------

    Assignee:     (was: Apache Spark)

> 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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