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Posted to issues@spark.apache.org by "Andrew Or (JIRA)" <ji...@apache.org> on 2014/05/14 03:04:48 UTC

[jira] [Updated] (SPARK-1823) ExternalAppendOnlyMap can still OOM if one key is very large

     [ https://issues.apache.org/jira/browse/SPARK-1823?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Andrew Or updated SPARK-1823:
-----------------------------

    Description: 
If the values for one key do not collectively fit into memory, then the map will still OOM when you merge the spilled contents back in.

This is a problem especially for PySpark, since we hash the keys (Python objects) before a shuffle, and there are only so many integers out there in the world, so there could potentially be many collisions.

  was:If the values for one key do not collectively fit into memory, then the map will still OOM when you merge the spilled contents back in.


> ExternalAppendOnlyMap can still OOM if one key is very large
> ------------------------------------------------------------
>
>                 Key: SPARK-1823
>                 URL: https://issues.apache.org/jira/browse/SPARK-1823
>             Project: Spark
>          Issue Type: Bug
>            Reporter: Andrew Or
>
> If the values for one key do not collectively fit into memory, then the map will still OOM when you merge the spilled contents back in.
> This is a problem especially for PySpark, since we hash the keys (Python objects) before a shuffle, and there are only so many integers out there in the world, so there could potentially be many collisions.



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