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Posted to issues@spark.apache.org by "Mike K (Jira)" <ji...@apache.org> on 2025/01/02 21:31:00 UTC
[jira] [Commented] (SPARK-49881) SPIP : Improving analyzer performance by skipping DeduplicateRelations rule conditionally
[ https://issues.apache.org/jira/browse/SPARK-49881?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17909424#comment-17909424 ]
Mike K commented on SPARK-49881:
--------------------------------
User 'ahshahid' has created a pull request for this issue:
https://github.com/apache/spark/pull/48354
> SPIP : Improving analyzer performance by skipping DeduplicateRelations rule conditionally
> -----------------------------------------------------------------------------------------
>
> Key: SPARK-49881
> URL: https://issues.apache.org/jira/browse/SPARK-49881
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 4.0.0, 3.5.3
> Reporter: Asif
> Priority: Major
>
> In many cases, it has been observed that DeduplicateRelations rule, though essential, but by its nature has impacted query analysis time to big extent especially when dealing with large query plans.
> It appears that in many situations we can guarantee that there would be no duplicate relations present and thus avoid applying the rule.
> Those situations are :
> 1) When dataframe api's like select/filter which operate on existing dataframe, are used.
>
> Also if we store the MultiInstanceRelations in the QueryExecution ,for a given plan, then we can make use of that information , while creating new dataframes where there is a possibility of duplicate relations ( like join, union, intersection etc).
> If two datasets being unioned/intersected/joined ..etc have no common MultiInstanceRelation , then it should be safe to assume that there is no possibility of duplicate relations , there by allowing skipping the Dedup rule
>
> Atleast that is the idea.
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