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https://issues.apache.org/jira/browse/SPARK-15652?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15306762#comment-15306762
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Subroto Sanyal commented on SPARK-15652:
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the jar contains the source code as well.
> Missing org.apache.spark.launcher.SparkAppHandle.Listener notification if
> SparkSubmit JVM shutsdown
> ---------------------------------------------------------------------------------------------------
>
> Key: SPARK-15652
> URL: https://issues.apache.org/jira/browse/SPARK-15652
> Project: Spark
> Issue Type: Bug
> Affects Versions: 1.6.0
> Reporter: Subroto Sanyal
> Priority: Critical
> Attachments: spark-launcher-client-hang.jar
>
>
> h6. Problem
> In case SparkSubmit JVM goes down even before sending the job complete
> notification; the _org.apache.spark.launcher.SparkAppHandle.Listener_ will
> not receive any notification which may lead to the client using SparkLauncher
> hang indefinitely.
> h6. Root Cause
> No proper exception handling at
> org.apache.spark.launcher.LauncherConnection#run when an EOFException is
> encountered while reading over Socket Stream. Mostly EOFException will be
> thrown at the suggested
> point(_org.apache.spark.launcher.LauncherConnection.run(LauncherConnection.java:58)_)
> if the SparkSubmit JVM is shutdown.
> Probably, it was assumed that SparkSubmit JVM can shut down only with normal
> healthy completion but, there could be scenarios where this is not the case:
> # OS kill the SparkSubmit process using OOM Killer.
> # Exception while SparkSubmit submits the job, even before it starts
> monitoring the application. This can happen if SparkLauncher is not
> configured properly. There might be no exception handling in
> org.apache.spark.deploy.yarn.Client#submitApplication(), which may lead to
> any exception/throwable at this point lead to shutting down of JVM without
> proper finalisation
> h6. Possible Solutions
> # In case of EOFException or any other exception notify the listeners that
> job has failed
> # Better exception handling on the SparkSubmit JVM side (though this may not
> resolve the problem completely)
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