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From "Gopal V (JIRA)" <j...@apache.org>
Subject [jira] [Resolved] (TEZ-3971) Incorrect query result in hive when hive.convert.join.bucket.mapjoin.tez=true
Date Mon, 16 Jul 2018 19:47:00 GMT

     [ https://issues.apache.org/jira/browse/TEZ-3971?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Gopal V resolved TEZ-3971.
--------------------------
    Resolution: Won't Do

> Incorrect query result in hive when hive.convert.join.bucket.mapjoin.tez=true
> -----------------------------------------------------------------------------
>
>                 Key: TEZ-3971
>                 URL: https://issues.apache.org/jira/browse/TEZ-3971
>             Project: Apache Tez
>          Issue Type: Bug
>         Environment: We are using Hive 3, Hadoop 3.1 and Tez 0.91
>            Reporter: Karthik
>            Priority: Major
>         Attachments: extended_explain.txt
>
>
> When hive.convert.join.bucket.mapjoin.tez=true and bucketed column is in select clause
but not in where clause, hive is performing a bucket map join and returning incorrect results.
When the bucketed column is removed from select clause or  hive.convert.join.bucket.mapjoin.tez=false, returned query
results are correct.
>  
> create table my_fact(AMT decimal(20,3),bucket_col string ,join_col string )
> PARTITIONED BY (FISCAL_YEAR string ,ACCOUNTING_PERIOD string )
>  CLUSTERED BY (bucket_col) INTO 10 
> BUCKETS 
> stored as ORC
>  ;
> create table my_dim(join_col string,filter_col string) stored as orc;
> After populating and analyzing above tables, explain  plan looks as below when  hive.convert.join.bucket.mapjoin.tez=TRUE:
>  
> explain  select T4.join_col as account1,my_fact.accounting_period
> FROM my_fact JOIN my_dim T4 ON my_fact.join_col = T4.join_col
> WHERE my_fact.fiscal_year = '2015'
>  AND T4.filter_col IN ( 'VAL1', 'VAL2' ) 
> and my_fact.accounting_period in (10);
> Vertex dependency in root stage
> Map 1 <- Map 2 (CUSTOM_EDGE)
> Stage-0
>  Fetch Operator
>  limit:-1
>  Stage-1
>  Map 1 vectorized, llap
>  File Output Operator [FS_24]
>  Select Operator [SEL_23] (rows=15282589 width=291)
>  Output:["_col0","_col1","_col2"]
>  Map Join Operator [MAPJOIN_22] (rows=15282589 width=291)
>  *BucketMapJoin*:true,Conds:SEL_21._col1=RS_19._col0(Inner),Output:["_col0","_col3","_col4"]
>  <-Map 2 [CUSTOM_EDGE] vectorized, llap
>  MULTICAST [RS_19]
>  PartitionCols:_col0
>  Select Operator [SEL_18] (rows=818 width=186)
>  Output:["_col0"]
>  Filter Operator [FIL_17] (rows=818 width=186)
>  predicate:((filter_col) IN ('VAL1', 'VAL2') and join_col is not null)
>  TableScan [TS_3] (rows=1635 width=186)
>  default@my_dim,t4,Tbl:COMPLETE,Col:NONE,Output:["join_col","filter_col"]
>  <-Select Operator [SEL_21] (rows=13893263 width=291)
>  Output:["_col0","_col1","_col3"]
>  Filter Operator [FIL_20] (rows=13893263 width=291)
>  predicate:join_col is not null
>  TableScan [TS_0] (rows=13893263 width=291)
>  default@my_fact,my_fact,Tbl:COMPLETE,Col:NONE,Output:["bucket_col","join_col"]
> [^extended_explain.txt] has more detailed plan.
> When  hive.convert.join.bucket.mapjoin.tez=false,  plan no longer has bucketjoin
and query results are correct.
> Vertex dependency in root stage
> Map 1 <- Map 2 (BROADCAST_EDGE)
> Stage-0
>  Fetch Operator
>  limit:-1
>  Stage-1
>  Map 1 vectorized, llap
>  File Output Operator [FS_24]
>  Select Operator [SEL_23] (rows=15282589 width=291)
>  Output:["_col0","_col1","_col2"]
>  Map Join Operator [MAPJOIN_22] (rows=15282589 width=291)
>  Conds:SEL_21._col1=RS_19._col0(Inner),Output:["_col0","_col3","_col4"]
>  <-Map 2 [BROADCAST_EDGE] vectorized, llap
>  BROADCAST [RS_19]
>  PartitionCols:_col0
>  Select Operator [SEL_18] (rows=818 width=186)
>  Output:["_col0"]
>  Filter Operator [FIL_17] (rows=818 width=186)
>  predicate:((filter_col) IN ('VAL1', 'VAL2') and join_col is not null)
>  TableScan [TS_3] (rows=1635 width=186)
>  default@my_dim,t4,Tbl:COMPLETE,Col:NONE,Output:["join_col","filter_col"]
>  <-Select Operator [SEL_21] (rows=13893263 width=291)
>  Output:["_col0","_col1","_col3"]
>  Filter Operator [FIL_20] (rows=13893263 width=291)
>  predicate:join_col is not null
>  TableScan [TS_0] (rows=13893263 width=291)
>  default@my_fact,my_fact,Tbl:COMPLETE,Col:NONE,Output:["bucket_col","join_col"]
>  
>  



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