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https://issues.apache.org/jira/browse/HIVE-25204?focusedWorklogId=611282&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-611282
]
ASF GitHub Bot logged work on HIVE-25204:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 15/Jun/21 12:17
Start Date: 15/Jun/21 12:17
Worklog Time Spent: 10m
Work Description: aasha commented on a change in pull request #2365:
URL: https://github.com/apache/hive/pull/2365#discussion_r651731735
##########
File path:
hcatalog/server-extensions/src/main/java/org/apache/hive/hcatalog/listener/DbNotificationListener.java
##########
@@ -905,25 +909,32 @@ public void
onUpdatePartitionColumnStat(UpdatePartitionColumnStatEvent updatePar
}
@Override
- public void
onUpdatePartitionColumnStatDirectSql(UpdatePartitionColumnStatEvent
updatePartColStatEvent,
- Connection dbConn,
SQLGenerator sqlGenerator)
+ public void
onUpdatePartitionColumnStatInBatch(UpdatePartitionColumnStatEventBatch
updatePartColStatEventBatch,
Review comment:
updatePartitionColStatsForOneBatch calls the direct sql method but also
does the following MetaStoreListenerNotifier.notifyEvent(listeners,
EventMessage.EventType.UPDATE_PARTITION_COLUMN_STAT,
new UpdatePartitionColumnStatEvent(colStats, partVals,
parameters,
tbl, writeId, this));
for each event.
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Issue Time Tracking
-------------------
Worklog Id: (was: 611282)
Time Spent: 50m (was: 40m)
> Reduce overhead of adding notification log for update partition column
> statistics
> ---------------------------------------------------------------------------------
>
> Key: HIVE-25204
> URL: https://issues.apache.org/jira/browse/HIVE-25204
> Project: Hive
> Issue Type: Sub-task
> Components: Hive, HiveServer2
> Reporter: mahesh kumar behera
> Assignee: mahesh kumar behera
> Priority: Major
> Labels: perfomance, pull-request-available
> Time Spent: 50m
> Remaining Estimate: 0h
>
> The notification logs for partition column statistics can be optimised by
> adding them in batch. In the current implementation its done one by one
> causing multiple sql execution in the backend RDBMS. These SQL executions can
> be batched to reduce the execution time.
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