sunchao commented on PR #58522:
URL: https://github.com/apache/spark/pull/58522#issuecomment-5547679944

   **Request changes: one P1 correctness issue.** Reviewed all six changed 
files at `78e2e312f272`.
   
   ### [P1] Preserve full partition keys for scan preparation
   
   At 
[DataSourceV2ScanExecBase.scala:108](https://github.com/apache/spark/blob/78e2e312f2729c8b1cae1598a9121177267b0c67/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/DataSourceV2ScanExecBase.scala#L108),
 the projection shortens partition-key rows and their types. However, 
`BatchScanExec.filteredPartitions` passes that projected partitioning into 
`PushDownUtils.replanWithRuntimeFilters`, which still reads **full source 
keys**.
   
   This has three consequences:
   
   - **Wrong results:** pruning a leading or middle key can make the actual 
partition order disagree with its advertised keys, causing joins to lose rows.
   - **Type errors:** pruning a leading string key while retaining an integer 
key makes the sorter read a string as an integer.
   - **Runtime-filtering failures, even with trailing pruning:** hashing 
iterates over the full key’s fields but indexes the shorter projected type 
array, causing `ArrayIndexOutOfBoundsException` when partitions survive 
filtering.
   
   Keep the full source-key layout for input sorting and runtime filtering; 
expose the projected partitioning downstream. Add tests for leading/middle 
pruning and runtime filtering with surviving partitions.
   
   This confirms the [existing review’s 
diagnosis](https://github.com/apache/spark/pull/58522#discussion_r3933688559) 
and extends its runtime-filtering impact. I found no additional actionable 
canonicalization/equality issues.
   
   **Validation:** source tracing and an executable model reproduced the 
ordering mismatch and schema-index failure. Full Spark tests were not run; the 
checkout lacks the required build dependencies.
   


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