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Posted to issues@spark.apache.org by "Andrew Ash (JIRA)" <ji...@apache.org> on 2014/09/05 19:38:29 UTC
[jira] [Commented] (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:comment-tabpanel&focusedCommentId=14123213#comment-14123213 ]
Andrew Ash commented on SPARK-1823:
-----------------------------------
// This was not fixed in Spark 1.1 and should be bumped to Spark 1.2
[~pwendell] about this issue on dev@ Aug 25th:
{quote}
We might create a new JIRA for it, but it doesn't exist yet. We'll create JIRA's for the major 1.2 issues at the beginning of September.
{quote}
> 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
> Affects Versions: 1.0.0
> Reporter: Andrew Or
> Fix For: 1.1.0
>
>
> 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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