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https://issues.apache.org/jira/browse/SPARK-4737?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Matt Cheah updated SPARK-4737:
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Comment: was deleted
(was: I will be out of the office with limited access to e-mail from January 05
to January 06. If there are specifically urgent matters requiring my assistance
and you have other means of contacting me, please use those other channels.
Sorry for the inconvenience. Thanks,
-Matt Cheah
)
> Prevent serialization errors from ever crashing the DAG scheduler
> -----------------------------------------------------------------
>
> Key: SPARK-4737
> URL: https://issues.apache.org/jira/browse/SPARK-4737
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.0.2, 1.1.1, 1.2.0
> Reporter: Patrick Wendell
> Assignee: Matthew Cheah
> Priority: Blocker
>
> Currently in Spark we assume that when tasks are serialized in the
> TaskSetManager that the serialization cannot fail. We assume this because
> upstream in the DAGScheduler we attempt to catch any serialization errors by
> serializing a single partition. However, in some cases this upstream test is
> not accurate - i.e. an RDD can have one partition that can serialize cleanly
> but not others.
> Do do this in the proper way we need to catch and propagate the exception at
> the time of serialization. The tricky bit is making sure it gets propagated
> in the right way.
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