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From "Xuefu Zhang (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (HIVE-8920) IOContext problem with multiple MapWorks cloned for multi-insert [Spark Branch]
Date Tue, 30 Dec 2014 16:17:14 GMT

     [ https://issues.apache.org/jira/browse/HIVE-8920?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Xuefu Zhang updated HIVE-8920:
------------------------------
    Attachment: HIVE-8920.4-spark.patch

> IOContext problem with multiple MapWorks cloned for multi-insert [Spark Branch]
> -------------------------------------------------------------------------------
>
>                 Key: HIVE-8920
>                 URL: https://issues.apache.org/jira/browse/HIVE-8920
>             Project: Hive
>          Issue Type: Sub-task
>          Components: Spark
>    Affects Versions: spark-branch
>            Reporter: Chao
>            Assignee: Xuefu Zhang
>         Attachments: HIVE-8920.1-spark.patch, HIVE-8920.2-spark.patch, HIVE-8920.3-spark.patch,
HIVE-8920.4-spark.patch
>
>
> The following query will not work:
> {code}
> from (select * from table0 union all select * from table1) s
> insert overwrite table table3 select s.x, count(1) group by s.x
> insert overwrite table table4 select s.y, count(1) group by s.y;
> {code}
> Currently, the plan for this query, before SplitSparkWorkResolver, looks like below:
> {noformat}
>    M1    M2
>      \  / \
>       U3   R5
>       |
>       R4
> {noformat}
> In {{SplitSparkWorkResolver#splitBaseWork}}, it assumes that the {{childWork}} is a ReduceWork,
but for this case, you can see that for M2 the childWork could be UnionWork U3. Thus, the
code will fail.
> HIVE-9041 addressed partially addressed the problem by removing union task. However,
it's still necessary to cloning M1 and M2 to support multi-insert. Because M1 and M2 can run
in a single JVM, the original solution of storing a global IOContext will not work because
M1 and M2 have different io contexts, both needing to be stored.



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