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From "Chao (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HIVE-7503) Support Hive's multi-table insert query with Spark [Spark Branch]
Date Thu, 18 Sep 2014 18:37:34 GMT

    [ https://issues.apache.org/jira/browse/HIVE-7503?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14139308#comment-14139308
] 

Chao commented on HIVE-7503:
----------------------------

All failed spark tests (4 of them) have multi-insertion queries. The difference is in the
plans generated, but not the results.
The other 3 failed tests are not related to this patch, I think.

> Support Hive's multi-table insert query with Spark [Spark Branch]
> -----------------------------------------------------------------
>
>                 Key: HIVE-7503
>                 URL: https://issues.apache.org/jira/browse/HIVE-7503
>             Project: Hive
>          Issue Type: Sub-task
>          Components: Spark
>            Reporter: Xuefu Zhang
>            Assignee: Chao
>              Labels: spark-m1
>         Attachments: HIVE-7503.1-spark.patch, HIVE-7503.2-spark.patch, HIVE-7503.3-spark.patch,
HIVE-7503.4-spark.patch, HIVE-7503.5-spark.patch, HIVE-7503.6-spark.patch
>
>
> For Hive's multi insert query (https://cwiki.apache.org/confluence/display/Hive/LanguageManual+DML),
there may be an MR job for each insert.  When we achieve this with Spark, it would be nice
if all the inserts can happen concurrently.
> It seems that this functionality isn't available in Spark. To make things worse, the
source of the insert may be re-computed unless it's staged. Even with this, the inserts will
happen sequentially, making the performance suffer.
> This task is to find out what takes in Spark to enable this without requiring staging
the source and sequential insertion. If this has to be solved in Hive, find out an optimum
way to do this.



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