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https://issues.apache.org/jira/browse/HIVE-17486?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16308547#comment-16308547
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Sahil Takiar commented on HIVE-17486:
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[~kellyzly] {quote} what i want to ask is there any possiblity to change
current structure in the SparkTask in HoS {quote}
What exactly is the advantage of introducing a M -> M edge? I know Tez does it,
but I think they mainly use it to broadcast data from one set of map tasks to
another (which is useful for map-joins).
> 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, HIVE-17486.2.patch,
> HIVE-17486.3.patch, HIVE-17486.4.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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