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