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https://issues.apache.org/jira/browse/HIVE-17486?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16283241#comment-16283241
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liyunzhang commented on HIVE-17486:
-----------------------------------
[~xuefuz] and [~lirui]: the second problem I found is the modification of
MapOperator after changing from M->R to M->M->R.
MapOperator is reponsible for deserializing and [initObjectInspector|
https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/exec/MapOperator.java#L170].
For the second M in M->M->R, deserializing is not necessary and
initObjectInspector is necessary. Currently I am investigating how to make this
work. If there is some wrong in my understanding, please tell me!
> Enable SharedWorkOptimizer in tez on HOS
> ----------------------------------------
>
> Key: HIVE-17486
> URL: https://issues.apache.org/jira/browse/HIVE-17486
> Project: Hive
> Issue Type: Bug
> Reporter: liyunzhang
> Assignee: liyunzhang
> Attachments: HIVE-17486.1.patch, explain.28.share.false,
> explain.28.share.true, scanshare.after.svg, scanshare.before.svg
>
>
> in HIVE-16602, Implement shared scans with Tez.
> Given a query plan, the goal is to identify scans on input tables that can be
> merged so the data is read only once. Optimization will be carried out at the
> physical level. In Hive on Spark, it caches the result of spark work if the
> spark work is used by more than 1 child spark work. After sharedWorkOptimizer
> is enabled in physical plan in HoS, the identical table scans are merged to 1
> table scan. This result of table scan will be used by more 1 child spark
> work. Thus we need not do the same computation because of cache mechanism.
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