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https://issues.apache.org/jira/browse/SPARK-20658?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16001638#comment-16001638
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Marcelo Vanzin commented on SPARK-20658:
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That's different... what version of Hadoop libraries is part of the Spark build?
Generally there will be Hadoop jars in {{$SPARK_HOME/jars}}. Those are the ones
that matter.
(Alternatively, if you found - or did not find - the log message I mentioned in
your logs, that would have answered these questions already.)
> spark.yarn.am.attemptFailuresValidityInterval doesn't seem to have an effect
> ----------------------------------------------------------------------------
>
> Key: SPARK-20658
> URL: https://issues.apache.org/jira/browse/SPARK-20658
> Project: Spark
> Issue Type: Bug
> Components: YARN
> Affects Versions: 2.1.0
> Reporter: Paul Jones
> Priority: Minor
>
> I'm running a job in YARN cluster mode using
> `spark.yarn.am.attemptFailuresValidityInterval=1h` specified in both
> spark-default.conf and in my spark-submit command. (This flag shows up in the
> environment tab of spark history server, so it seems that it's specified
> correctly).
> However, I just had a job die with with four AM failures (three of the four
> failures were over an hour apart). So, I'm confused as to what could be going
> on. I haven't figured out the cause of the individual failures, so is it
> possible that we always count certain types of failures? E.g. jobs that are
> killed due to memory issues always count?
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