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https://issues.apache.org/jira/browse/HIVE-17486?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16235137#comment-16235137
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Xuefu Zhang commented on HIVE-17486:
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[~kellyzly] I think M->M->R is possible. It's just that the current planner
doesn't do this, but in theory it can be done. Currently the assumption is that
a Map task is always followed by a Reduce task.
> 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
> Priority: Major
> Attachments: 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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