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From "Karthik (JIRA)" <j...@apache.org>
Subject [jira] [Created] (TEZ-3971) Incorrect query result in hive when hive.convert.join.bucket.mapjoin.tez=true
Date Sun, 15 Jul 2018 20:34:00 GMT
Karthik created TEZ-3971:
----------------------------

             Summary: 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
         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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