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https://issues.apache.org/jira/browse/HIVE-12165?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Aihua Xu updated HIVE-12165:
----------------------------
Resolution: Fixed
Fix Version/s: 2.1.0
Status: Resolved (was: Patch Available)
> wrong result when hive.optimize.sampling.orderby=true with some aggregate
> functions
> -----------------------------------------------------------------------------------
>
> Key: HIVE-12165
> URL: https://issues.apache.org/jira/browse/HIVE-12165
> Project: Hive
> Issue Type: Bug
> Affects Versions: 2.1.0
> Environment: hortonworks 2.3
> Reporter: ErwanMAS
> Assignee: Aihua Xu
> Priority: Critical
> Fix For: 2.1.0
>
> Attachments: HIVE-12165.patch
>
>
> This simple query give wrong result , when , i use the parallel order .
> {noformat}
> select count(*) , count(distinct dummyint ) , min(dummyint),max(dummyint)
> from foobar_1M ;
> {noformat}
> Current wrong result :
> {noformat}
> c0 c1 c2 c3
> 32740 32740 0 163695
> 113172 113172 163700 729555
> 54088 54088 729560 999995
> {noformat}
> Right result :
> {noformat}
> c0 c1 c2 c3
> 1000000 1000000 0 999999
> {noformat}
> The sql script for my test
> {noformat}
> drop table foobar_1 ;
> create table foobar_1 ( dummyint int , dummystr string ) ;
> insert into table foobar_1 select count(*),'dummy 0' from foobar_1 ;
> drop table foobar_1M ;
> create table foobar_1M ( dummyint bigint , dummystr string ) ;
> insert overwrite table foobar_1M
> select val_int , concat('dummy ',val_int) from
> ( select ((((((d_1*10)+d_2)*10+d_3)*10+d_4)*10+d_5)*10+d_6) as
> val_int from foobar_1
> lateral view outer explode(split("0,1,2,3,4,5,6,7,8,9",","))
> tbl_1 as d_1
> lateral view outer explode(split("0,1,2,3,4,5,6,7,8,9",","))
> tbl_2 as d_2
> lateral view outer explode(split("0,1,2,3,4,5,6,7,8,9",","))
> tbl_3 as d_3
> lateral view outer explode(split("0,1,2,3,4,5,6,7,8,9",","))
> tbl_4 as d_4
> lateral view outer explode(split("0,1,2,3,4,5,6,7,8,9",","))
> tbl_5 as d_5
> lateral view outer explode(split("0,1,2,3,4,5,6,7,8,9",","))
> tbl_6 as d_6 ) as f ;
> set hive.optimize.sampling.orderby.number=10000;
> set hive.optimize.sampling.orderby.percent=0.1f;
> set mapreduce.job.reduces=3 ;
> set hive.optimize.sampling.orderby=false;
> select count(*) , count(distinct dummyint ) , min(dummyint),max(dummyint)
> from foobar_1M ;
> set hive.optimize.sampling.orderby=true;
> select count(*) , count(distinct dummyint ) , min(dummyint),max(dummyint)
> from foobar_1M ;
> {noformat}
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