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Posted to issues@tez.apache.org by "Gopal V (JIRA)" <ji...@apache.org> on 2018/07/16 19:47:00 UTC
[jira] [Resolved] (TEZ-3971) Incorrect query result in hive when
hive.convert.join.bucket.mapjoin.tez=true
[ 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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