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From "Gopal V (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (HIVE-7232) VectorReduceSink is emitting incorrect JOIN keys
Date Thu, 26 Jun 2014 03:45:25 GMT

     [ https://issues.apache.org/jira/browse/HIVE-7232?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Gopal V updated HIVE-7232:
--------------------------

    Status: Open  (was: Patch Available)

Need to rebase patch to match recent qtest changes made HIVE-7258

> VectorReduceSink is emitting incorrect JOIN keys
> ------------------------------------------------
>
>                 Key: HIVE-7232
>                 URL: https://issues.apache.org/jira/browse/HIVE-7232
>             Project: Hive
>          Issue Type: Bug
>          Components: Query Processor
>    Affects Versions: 0.14.0
>            Reporter: Gopal V
>            Assignee: Gopal V
>         Attachments: HIVE-7232-extra-logging.patch, HIVE-7232.1.patch.txt, q5.explain.txt,
q5.sql
>
>
> After HIVE-7121, tpc-h query5 has resulted in incorrect results.
> Thanks to [~navis], it has been tracked down to the auto-parallel settings which were
initialized for ReduceSinkOperator, but not for VectorReduceSinkOperator. The vector version
inherits, but doesn't call super.initializeOp() or set up the variable correctly from ReduceSinkDesc.
> The query is tpc-h query5, with extra NULL checks just to be sure.
> {code}
> ELECT n_name,
>        sum(l_extendedprice * (1 - l_discount)) AS revenue
> FROM customer,
>      orders,
>      lineitem,
>      supplier,
>      nation,
>      region
> WHERE c_custkey = o_custkey
>   AND l_orderkey = o_orderkey
>   AND l_suppkey = s_suppkey
>   AND c_nationkey = s_nationkey
>   AND s_nationkey = n_nationkey
>   AND n_regionkey = r_regionkey
>   AND r_name = 'ASIA'
>   AND o_orderdate >= '1994-01-01'
>   AND o_orderdate < '1995-01-01'
>   and l_orderkey is not null
>   and c_custkey is not null
>   and l_suppkey is not null
>   and c_nationkey is not null
>   and s_nationkey is not null
>   and n_regionkey is not null
> GROUP BY n_name
> ORDER BY revenue DESC;
> {code}
> The reducer which has the issue has the following plan
> {code}
> Reducer 3
>             Reduce Operator Tree:
>               Join Operator
>                 condition map:
>                      Inner Join 0 to 1
>                 condition expressions:
>                   0 {KEY.reducesinkkey0} {VALUE._col2}
>                   1 {VALUE._col0} {KEY.reducesinkkey0} {VALUE._col3}
>                 outputColumnNames: _col0, _col3, _col10, _col11, _col14
>                 Statistics: Num rows: 183333344 Data size: 95229140992 Basic stats: COMPLETE
Column stats: NONE
>                 Reduce Output Operator
>                   key expressions: _col10 (type: int)
>                   sort order: +
>                   Map-reduce partition columns: _col10 (type: int)
>                   Statistics: Num rows: 183333344 Data size: 95229140992 Basic stats:
COMPLETE Column stats: NONE
>                   value expressions: _col0 (type: int), _col3 (type: int), _col11 (type:
int), _col14 (type: string)
> {code}



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