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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Work logged] (HIVE-21338) Remove order by and limit for aggregates
Date Wed, 06 Mar 2019 05:56:00 GMT

     [ https://issues.apache.org/jira/browse/HIVE-21338?focusedWorklogId=208434&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-208434
]

ASF GitHub Bot logged work on HIVE-21338:
-----------------------------------------

                Author: ASF GitHub Bot
            Created on: 06/Mar/19 05:55
            Start Date: 06/Mar/19 05:55
    Worklog Time Spent: 10m 
      Work Description: jcamachor commented on pull request #557: HIVE-21338 Remove order
by and limit for aggregates
URL: https://github.com/apache/hive/pull/557#discussion_r262800104
 
 

 ##########
 File path: ql/src/java/org/apache/hadoop/hive/ql/parse/CalcitePlanner.java
 ##########
 @@ -1925,6 +1926,11 @@ public RelNode apply(RelOptCluster cluster, RelOptSchema relOptSchema,
SchemaPlu
         perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER, "Calcite:
Window fixing rule");
       }
 
+      perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
 
 Review comment:
   Yes, that is what I meant.
 
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Issue Time Tracking
-------------------

    Worklog Id:     (was: 208434)
    Time Spent: 1h  (was: 50m)

> Remove order by and limit for aggregates
> ----------------------------------------
>
>                 Key: HIVE-21338
>                 URL: https://issues.apache.org/jira/browse/HIVE-21338
>             Project: Hive
>          Issue Type: Improvement
>          Components: Query Planning
>            Reporter: Vineet Garg
>            Assignee: Vineet Garg
>            Priority: Major
>              Labels: pull-request-available
>         Attachments: HIVE-21338.1.patch, HIVE-21338.2.patch, HIVE-21338.3.patch, HIVE-21338.4.patch
>
>          Time Spent: 1h
>  Remaining Estimate: 0h
>
> If a query is guaranteed to produce at most one row LIMIT and ORDER BY could be removed.
This saves unnecessary vertex for LIMIT/ORDER BY.
> {code:sql}
> explain select count(*) cs from store_sales where ss_ext_sales_price > 100.00 order
by cs limit 100
> {code}
> {code}
> STAGE PLANS:
>   Stage: Stage-1
>     Tez
>       DagId: vgarg_20190227131959_2914830f-eab6-425d-b9f0-b8cb56f8a1e9:4
>       Edges:
>         Reducer 2 <- Map 1 (CUSTOM_SIMPLE_EDGE)
>         Reducer 3 <- Reducer 2 (SIMPLE_EDGE)
>       DagName: vgarg_20190227131959_2914830f-eab6-425d-b9f0-b8cb56f8a1e9:4
>       Vertices:
>         Map 1
>             Map Operator Tree:
>                 TableScan
>                   alias: store_sales
>                   filterExpr: (ss_ext_sales_price > 100) (type: boolean)
>                   Statistics: Num rows: 1 Data size: 112 Basic stats: COMPLETE Column
stats: NONE
>                   Filter Operator
>                     predicate: (ss_ext_sales_price > 100) (type: boolean)
>                     Statistics: Num rows: 1 Data size: 112 Basic stats: COMPLETE Column
stats: NONE
>                     Select Operator
>                       Statistics: Num rows: 1 Data size: 112 Basic stats: COMPLETE Column
stats: NONE
>                       Group By Operator
>                         aggregations: count()
>                         mode: hash
>                         outputColumnNames: _col0
>                         Statistics: Num rows: 1 Data size: 120 Basic stats: COMPLETE
Column stats: NONE
>                         Reduce Output Operator
>                           sort order:
>                           Statistics: Num rows: 1 Data size: 120 Basic stats: COMPLETE
Column stats: NONE
>                           value expressions: _col0 (type: bigint)
>             Execution mode: vectorized
>         Reducer 2
>             Execution mode: vectorized
>             Reduce Operator Tree:
>               Group By Operator
>                 aggregations: count(VALUE._col0)
>                 mode: mergepartial
>                 outputColumnNames: _col0
>                 Statistics: Num rows: 1 Data size: 120 Basic stats: COMPLETE Column stats:
NONE
>                 Reduce Output Operator
>                   key expressions: _col0 (type: bigint)
>                   sort order: +
>                   Statistics: Num rows: 1 Data size: 120 Basic stats: COMPLETE Column
stats: NONE
>                   TopN Hash Memory Usage: 0.1
>         Reducer 3
>             Execution mode: vectorized
>             Reduce Operator Tree:
>               Select Operator
>                 expressions: KEY.reducesinkkey0 (type: bigint)
>                 outputColumnNames: _col0
>                 Statistics: Num rows: 1 Data size: 120 Basic stats: COMPLETE Column stats:
NONE
>                 Limit
>                   Number of rows: 100
>                   Statistics: Num rows: 1 Data size: 120 Basic stats: COMPLETE Column
stats: NONE
>                   File Output Operator
>                     compressed: false
>                     Statistics: Num rows: 1 Data size: 120 Basic stats: COMPLETE Column
stats: NONE
>                     table:
>                         input format: org.apache.hadoop.mapred.SequenceFileInputFormat
>                         output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat
>                         serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
>   Stage: Stage-0
>     Fetch Operator
>       limit: 100
>       Processor Tree:
>         ListSink
> {code}



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