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https://issues.apache.org/jira/browse/SPARK-12009?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15028370#comment-15028370
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Saisai Shao commented on SPARK-12009:
-------------------------------------
If I understood correctly, this log should come from application master, I
don't think it related to executor termination.
{code}
override def onDisconnected(remoteAddress: RpcAddress): Unit = {
// In cluster mode, do not rely on the disassociated event to exit
// This avoids potentially reporting incorrect exit codes if the driver
fails
if (!isClusterMode) {
logInfo(s"Driver terminated or disconnected! Shutting down.
$remoteAddress")
finish(FinalApplicationStatus.SUCCEEDED, ApplicationMaster.EXIT_SUCCESS)
}
}
{code}
> Avoid re-allocate yarn container while driver want to stop all Executors
> ------------------------------------------------------------------------
>
> Key: SPARK-12009
> URL: https://issues.apache.org/jira/browse/SPARK-12009
> Project: Spark
> Issue Type: Bug
> Components: YARN
> Affects Versions: 1.5.2
> Reporter: SuYan
> Priority: Minor
>
> 2015-11-26,03:05:16,176 WARN
> org.spark-project.jetty.util.thread.QueuedThreadPool: 8 threads could not be
> stopped
> 2015-11-26,03:05:16,177 INFO org.apache.spark.ui.SparkUI: Stopped Spark web
> UI at http://
> 2015-11-26,03:05:16,401 INFO org.apache.spark.scheduler.DAGScheduler:
> Stopping DAGScheduler
> 2015-11-26,03:05:16,450 INFO
> org.apache.spark.scheduler.cluster.YarnClusterSchedulerBackend: Shutting down
> all executors
> 2015-11-26,03:05:16,525 INFO
> org.apache.spark.scheduler.cluster.YarnClusterSchedulerBackend: Asking each
> executor to shut down
> 2015-11-26,03:05:16,791 INFO
> org.apache.spark.deploy.yarn.ApplicationMaster$AMEndpoint: Driver terminated
> or disconnected! Shutting down. XX.XX.XX.XX:38734
> 2015-11-26,03:05:16,847 ERROR org.apache.spark.scheduler.LiveListenerBus:
> SparkListenerBus has already stopped! Dropping event
> SparkListenerExecutorMetricsUpdate(164,WrappedArray())
> 2015-11-26,03:05:27,242 INFO org.apache.spark.deploy.yarn.YarnAllocator: Will
> request 13 executor containers, each with 1 cores and 4608 MB memory
> including 1024 MB overhead
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