peter-toth commented on PR #59599:
URL: https://github.com/apache/spark/pull/59599#issuecomment-6339569304

   @szehon-ho @uros-b IMO this is a real correctness problem, but it isn't a 
regression since the last 4.1 and 4.0 releases. So it isn't necessarily a 
release blocker.
   
   These SPJ bugs are open on 4.1 and 4.0 too, and fixed on `branch-4.2` and 
later:
   - SPARK-59121: wrong results when a storage-partitioned join reduces the 
partition keys of both sides.
   - SPARK-59887: wrong results when a storage-partitioned join pairs a 
transform of a join-key expression with one of a column.
   - SPARK-59901: an `INTERNAL_ERROR` when a one-side shuffle's join key 
references two columns.
   - SPARK-59688: wrong results when a storage-partitioned join skips the 
reduce on coinciding partition keys.
   - SPARK-58996: a partially clustered storage-partitioned join duplicates 
rows when `EnsureRequirements` re-runs. On 4.1 and 4.0 this needs 
`spark.sql.adaptive.forceOptimizeSkewedJoin`.
   
   Two smaller ones are open on every branch, master included:
   - SPARK-60027: a partition transform skips its input casts, so the query 
fails with a `ClassCastException`.
   - SPARK-60260: wrong results when `spark.sql.sources.v2.bucketing.enabled` 
is changed after a storage-partitioned join is planned.
   
   One more is open on 4.1 and 4.0 only:
   - SPARK-60460: a storage-partitioned join over a nested join that shuffles 
one side fails with `Can't zip RDDs`.
   


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