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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2015/04/27 20:21:38 UTC

[jira] [Assigned] (SPARK-5763) Sort-based Groupby and Join to resolve skewed data

     [ https://issues.apache.org/jira/browse/SPARK-5763?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Apache Spark reassigned SPARK-5763:
-----------------------------------

    Assignee: Apache Spark

> Sort-based Groupby and Join to resolve skewed data
> --------------------------------------------------
>
>                 Key: SPARK-5763
>                 URL: https://issues.apache.org/jira/browse/SPARK-5763
>             Project: Spark
>          Issue Type: Improvement
>          Components: Shuffle, Spark Core
>            Reporter: Lianhui Wang
>            Assignee: Apache Spark
>
> In SPARK-4644, it provide a way to resolve skewed data. But when we has more keys that are skewed, I think that the way in SPARK-4644 is inappropriate. So we can use sort-merge to resolve skewed-groupby and skewed-join.because SPARK-2926 implement merge-sort, we can implement sort-merge for skewed based on SPARK-2926. And i have implemented sort-merge-groupby and it is very well for skewed data in my test.Later i will implement sort-merge-join to resolve skewed-join.
> [~rxin] [~sandyr] [~andrewor14] how about your opinions about this?



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