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https://issues.apache.org/jira/browse/HIVE-25867?focusedWorklogId=745134&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-745134
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ASF GitHub Bot logged work on HIVE-25867:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 21/Mar/22 14:29
Start Date: 21/Mar/22 14:29
Worklog Time Spent: 10m
Work Description: pvary commented on pull request #2947:
URL: https://github.com/apache/hive/pull/2947#issuecomment-1073969722
600k partitions are always a pain.
We are working on integrating Iceberg that would help there.
I would guess that the solution is this case should be a configuration to
turn off DB level filtering on query level. Maybe we already have a config for
that.
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Issue Time Tracking
-------------------
Worklog Id: (was: 745134)
Time Spent: 1.5h (was: 1h 20m)
> Partition filter condition should pushed down to metastore query if it is
> equivalence Predicate
> -----------------------------------------------------------------------------------------------
>
> Key: HIVE-25867
> URL: https://issues.apache.org/jira/browse/HIVE-25867
> Project: Hive
> Issue Type: Improvement
> Components: Standalone Metastore
> Reporter: shezm
> Assignee: shezm
> Priority: Major
> Labels: pull-request-available
> Fix For: 4.0.0
>
> Time Spent: 1.5h
> Remaining Estimate: 0h
>
> The colnum type of the partition is different from the column type of the hql
> query, the metastore will not push down the query to the RDBMS, but will
> instead get all PARTITIONS.PART_NAME of the hive table then filter it
> according to the hql Expression.
> https://github.com/apache/hive/blob/5b112aa6dcc4e374c0a7c2b24042f24ae6815da1/standalone-metastore/metastore-server/src/main/java/org/apache/hadoop/hive/metastore/MetaStoreDirectSql.java#L1316
> If the hive table has too many partitions and there are multiple hql queries
> at the same time,RDBMS will increasing CPU IO_WAIT and affect performance.
> If the partition filter condition in hql is an equivalent predicate, the
> metastore should be pushed down to RDBMS, which can optimize the query
> performance of hive large tables.
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