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https://issues.apache.org/jira/browse/HIVE-21338?focusedWorklogId=209305&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-209305
]
ASF GitHub Bot logged work on HIVE-21338:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 07/Mar/19 01:52
Start Date: 07/Mar/19 01:52
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_r263210480
##########
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:
I believe now that the rule relies on the logic from the metadata provider
that is more powerful, we could move this before step 6. in
```applyPreJoinOrderingTransforms```. This means that ```RelFieldTrimmer```
will be executed after this rule and thus may eliminate any column(s) that were
used by SortLimit but are not needed anymore (for instance, the example above).
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Issue Time Tracking
-------------------
Worklog Id: (was: 209305)
Time Spent: 1.5h (was: 1h 20m)
> 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, HIVE-21338.5.patch
>
> Time Spent: 1.5h
> 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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