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https://issues.apache.org/jira/browse/SPARK-2282?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14062916#comment-14062916
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Ken Carlile commented on SPARK-2282:
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We may be running into this issue on our cluster. Any input on whether this
property needs to be set on all nodes or on only the master? I ask because we
dynamically spin up spark clusters on a larger general purpose compute cluster,
so I'm hesitant to start changing sysctls willy nilly unless I absolutely have
to.
Thanks,
Ken
> PySpark crashes if too many tasks complete quickly
> --------------------------------------------------
>
> Key: SPARK-2282
> URL: https://issues.apache.org/jira/browse/SPARK-2282
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 0.9.1, 1.0.0, 1.0.1
> Reporter: Aaron Davidson
> Assignee: Aaron Davidson
> Fix For: 0.9.2, 1.0.0, 1.0.1
>
>
> Upon every task completion, PythonAccumulatorParam constructs a new socket to
> the Accumulator server running inside the pyspark daemon. This can cause a
> buildup of used ephemeral ports from sockets in the TIME_WAIT termination
> stage, which will cause the SparkContext to crash if too many tasks complete
> too quickly. We ran into this bug with 17k tasks completing in 15 seconds.
> This bug can be fixed outside of Spark by ensuring these properties are set
> (on a linux server);
> echo "1" > /proc/sys/net/ipv4/tcp_tw_reuse
> echo "1" > /proc/sys/net/ipv4/tcp_tw_recycle
> or by adding the SO_REUSEADDR option to the Socket creation within Spark.
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