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https://issues.apache.org/jira/browse/SPARK-7718?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14549846#comment-14549846
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Apache Spark commented on SPARK-7718:
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User 'andrewor14' has created a pull request for this issue:
https://github.com/apache/spark/pull/6256
> Speed up data source partitioning by avoiding cleaning closures
> ---------------------------------------------------------------
>
> Key: SPARK-7718
> URL: https://issues.apache.org/jira/browse/SPARK-7718
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.4.0
> Reporter: Andrew Or
> Assignee: Andrew Or
> Priority: Critical
>
> The new partitioning support strategy creates a bunch of RDDs (1 per
> partition, could be up to several thousands), then calls `mapPartitions` on
> every single one of these RDDs. This causes us to clean the same closure many
> times. Since we provide the closure in Spark we know for sure it is
> serializable, so we can bypass the cleaning for performance.
> According to [~yhuai] cleaning 5000 closures take up to 6-7 seconds in a 12
> seconds job that involves data source partitioning.
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