[SPARK-45882][SQL][3.5] BroadcastHashJoinExec propagate partitioning should respect CoalescedHashPartitioning #43792
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…d respect CoalescedHashPartitioning Add HashPartitioningLike trait and make HashPartitioning and CoalescedHashPartitioning extend it. When we propagate output partiitoning, we should handle HashPartitioningLike instead of HashPartitioning. This pr also changes the BroadcastHashJoinExec to use HashPartitioningLike to avoid regression. Avoid unnecessary shuffle exchange. yes, avoid regression add test no Closes apache#43753 from ulysses-you/partitioning. Authored-by: ulysses-you <ulyssesyou18@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
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thanks for review, merging to branch-3.5 |
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…should respect CoalescedHashPartitioning This pr backport #43753 to branch-3.5 ### What changes were proposed in this pull request? Add HashPartitioningLike trait and make HashPartitioning and CoalescedHashPartitioning extend it. When we propagate output partiitoning, we should handle HashPartitioningLike instead of HashPartitioning. This pr also changes the BroadcastHashJoinExec to use HashPartitioningLike to avoid regression. ### Why are the changes needed? Avoid unnecessary shuffle exchange. ### Does this PR introduce _any_ user-facing change? yes, avoid regression ### How was this patch tested? add test ### Was this patch authored or co-authored using generative AI tooling? no Closes #43792 from ulysses-you/partitioning-3.5. Authored-by: ulysses-you <ulyssesyou18@gmail.com> Signed-off-by: youxiduo <youxiduo@corp.netease.com>
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Hi, @ulysses-you and @cloud-fan . If you don't mind, please adjust the JIRA type properly before backporting.
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This pr backport #43753 to branch-3.5
What changes were proposed in this pull request?
Add HashPartitioningLike trait and make HashPartitioning and CoalescedHashPartitioning extend it. When we propagate output partiitoning, we should handle HashPartitioningLike instead of HashPartitioning. This pr also changes the BroadcastHashJoinExec to use HashPartitioningLike to avoid regression.
Why are the changes needed?
Avoid unnecessary shuffle exchange.
Does this PR introduce any user-facing change?
yes, avoid regression
How was this patch tested?
add test
Was this patch authored or co-authored using generative AI tooling?
no