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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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