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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2016/06/01 15:55:59 UTC
[jira] [Assigned] (SPARK-15671) performance regression CoalesceRDD
large # partitions
[ https://issues.apache.org/jira/browse/SPARK-15671?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-15671:
------------------------------------
Assignee: (was: Apache Spark)
> performance regression CoalesceRDD large # partitions
> -----------------------------------------------------
>
> Key: SPARK-15671
> URL: https://issues.apache.org/jira/browse/SPARK-15671
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.0.0
> Reporter: Thomas Graves
> Priority: Critical
>
> I was running a 15TB join job with 202000 partitions. It looks like the changes I made to CoalesceRDD in pickBin() are really slow with that large of partitions. The array filter with that many elements just takes to long.
> It took about an hour for it to pickBins for all the partitions.
> original change:
> https://github.com/apache/spark/commit/83ee92f60345f016a390d61a82f1d924f64ddf90
> Just reverting the pickBin code back to get currpreflocs fixes the issue
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