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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2019/05/21 04:25:13 UTC
[jira] [Updated] (SPARK-9599) Dynamic partitioning based on
key-distribution
[ https://issues.apache.org/jira/browse/SPARK-9599?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon updated SPARK-9599:
--------------------------------
Labels: bulk-closed (was: )
> Dynamic partitioning based on key-distribution
> ----------------------------------------------
>
> Key: SPARK-9599
> URL: https://issues.apache.org/jira/browse/SPARK-9599
> Project: Spark
> Issue Type: Improvement
> Components: Shuffle, Spark Core
> Affects Versions: 1.4.1
> Reporter: Zoltán Zvara
> Priority: Major
> Labels: bulk-closed
>
> When - for example - using {{groupByKey}} operator with default {{HashPartitioner}}, there might be a case when heavy keys get partitioned into the same bucket, later raising an OOM error at the result partition. A domain-based partitioner might not be able to help, when the outstanding key-distribution changes from time to time (for example while dealing with data streams).
> Spark should identify these situations and change the partitioning accordingly when a partitioning would raise an OOM later.
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