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https://issues.apache.org/jira/browse/HIVE-17486?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16285558#comment-16285558
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liyunzhang edited comment on HIVE-17486 at 12/11/17 6:41 AM:
-------------------------------------------------------------

[~xuefuz]
{quote}  It seems that we can do so whenever an TS is connected to multiple 
RSs. The split point should happen at the fork. {quote}  not very understand 
about this. Currently the split is on the TS
for example
{code}
TS[0]-FIL[52]-SEL[2]-GBY[3]-RS[4]-GBY[5]-RS[42]-JOIN[48]-SEL[49]-LIM[50]-FS[51]
        -FIL[53]-SEL[9]-GBY[10]-RS[11]-GBY[12]-RS[43]-JOIN[48]
{code}

->
{code}          
Map1: TS[0]
Map2:FIL[52]-SEL[2]-GBY[3]-RS[4]
Map3:FIL[53]-SEL[9]-GBY[10]-RS[11]
Reducer1:GBY[5]-RS[42]-JOIN[48]-SEL[49]-LIM[50]-FS[51]
Reducer2:GBY[12]-RS[43]
{code}


was (Author: kellyzly):
[~xuefuz]
{quote}  It seems that we can do so whenever an TS is connected to multiple 
RSs. The split point should happen at the fork. {quote}  not very understand 
about this. Please explain more, thanks!

> 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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