You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Apache Spark (Jira)" <ji...@apache.org> on 2022/07/27 08:46:00 UTC
[jira] [Commented] (SPARK-39893) Remove redundant aggregate if it is group only and all grouping and aggregate expressions are foldable
[ https://issues.apache.org/jira/browse/SPARK-39893?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17571803#comment-17571803 ]
Apache Spark commented on SPARK-39893:
--------------------------------------
User 'wankunde' has created a pull request for this issue:
https://github.com/apache/spark/pull/37316
> Remove redundant aggregate if it is group only and all grouping and aggregate expressions are foldable
> ------------------------------------------------------------------------------------------------------
>
> Key: SPARK-39893
> URL: https://issues.apache.org/jira/browse/SPARK-39893
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 3.4.0
> Reporter: Wan Kun
> Priority: Major
>
> If all groupingExpressions and aggregateExpressions in a aggregate are foldable, we can remove this aggregate.
> For example, query :
> {code:java}
> SELECT distinct 1001 as id , cast('2022-06-03' as date) AS DT FROM testData
> {code}
> the grouping expressions are : *[1001, 2022-06-03]*
> the aggregate expressions are : *[1001 AS id#274, 2022-06-03 AS DT#275]*
> so we can skip scan table testData and remote the aggregate operation.
> Before this PR:
> {code:java}
> Aggregate [1001, 2022-06-03], [1001 AS id#274, 2022-06-03 AS DT#275], Statistics(sizeInBytes=16.0 EiB)
> +- SerializeFromObject, Statistics(sizeInBytes=8.0 EiB)
> +- ExternalRDD [obj#12], Statistics(sizeInBytes=8.0 EiB)
> {code}
> After this PR:
> {code:java}
> Project [1001 AS id#218, 2022-06-03 AS DT#219], Statistics(sizeInBytes=2.0 B)
> +- OneRowRelation, Statistics(sizeInBytes=1.0 B)
> {code}
--
This message was sent by Atlassian Jira
(v8.20.10#820010)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org