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https://issues.apache.org/jira/browse/HIVE-8956?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14226504#comment-14226504
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Marcelo Vanzin commented on HIVE-8956:
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I haven't looked at akka in that much detail to see if there is some API to
catch those. You can enable akka logging (set {{spark.akka.logLifecycleEvents}}
to true) and that will print these errors to the logs. Spark tries to serialize
data before sending it to akka, to try to catch serialization issues, but that
adds overhead, and it also doesn't help in the deserialization path...
> Hive hangs while some error/exception happens beyond job execution [Spark
> Branch]
> ---------------------------------------------------------------------------------
>
> Key: HIVE-8956
> URL: https://issues.apache.org/jira/browse/HIVE-8956
> Project: Hive
> Issue Type: Sub-task
> Components: Spark
> Reporter: Chengxiang Li
> Assignee: Rui Li
> Labels: Spark-M3
> Fix For: spark-branch
>
> Attachments: HIVE-8956.1-spark.patch
>
>
> Remote spark client communicate with remote spark context asynchronously, if
> error/exception is throw out during job execution in remote spark context, it
> would be wrapped and send back to remote spark client, but if error/exception
> is throw out beyond job execution, such as job serialized failed, remote
> spark client would never know what's going on in remote spark context, and it
> would hangs there.
> Set a timeout in remote spark client side may not a great idea, as we are not
> sure how long the query executed in spark cluster. we need find a way to
> check whether job has failed(whole life cycle) in remote spark context.
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