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https://issues.apache.org/jira/browse/SPARK-47094?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Chao Sun resolved SPARK-47094.
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Fix Version/s: 4.0.0
Resolution: Fixed
Issue resolved by pull request 45267
[https://github.com/apache/spark/pull/45267]
> SPJ : Dynamically rebalance number of buckets when they are not equal
> ---------------------------------------------------------------------
>
> Key: SPARK-47094
> URL: https://issues.apache.org/jira/browse/SPARK-47094
> Project: Spark
> Issue Type: Sub-task
> Components: Spark Core
> Affects Versions: 3.3.0, 3.4.0
> Reporter: Himadri Pal
> Priority: Major
> Labels: pull-request-available
> Fix For: 4.0.0
>
>
> SPJ: Storage Partition Join works with Iceberg tables when both the tables
> have same number of buckets. As part of this feature request, we would like
> spark to gather the number of buckets information from both the tables and
> dynamically rebalance the number of buckets by coalesce or repartition so
> that SPJ will work fine. In this case, we would still have to shuffle but
> would be better than no SPJ.
> Use Case :
> Many times we do not have control of the input tables, hence it's not
> possible to change partitioning scheme on those tables. As a consumer, we
> would still like them to be used with SPJ when used with other tables and
> output tables which has different number of buckets.
> In these scenario, we would need to read those tables rewrite them with
> matching number of buckets for the SPJ to work, this extra step could
> outweigh the benefits of less shuffle via SPJ. Also when there are multiple
> different tables being joined, each tables need to be rewritten with matching
> number of buckets.
> If this feature is implemented, SPJ functionality will be more powerful.
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