dwsmith1983 opened a new pull request, #7624:
URL: https://github.com/apache/datafusion-comet/pull/7624

   ## Which issue does this PR close?
   
   Backport of #6268 to `branch-1.1`. Part of #6133.
   
   #7623 must merge first: one of the tests here needs it. This PR and #7338 
(the `branch-1.1` backport of #6270, the other half of #6133) don't depend on 
each other; whichever merges second should take `branch-1.1` and rerun its 
suites. `branch-1.2` already has #6268. `branch-1.0` has the same code; no 
backport is planned there.
   
   ## Rationale for this change
   
   AQE reads `outputPartitioning` when `CoalesceShufflePartitions` changes a 
stage, before the DPP placeholders are converted. On `branch-1.1`, a 
non-bucketed `CometNativeScanExec` answers with its split count, which runs the 
placeholder and fails with `SubqueryAdaptiveBroadcastExec does not support the 
execute() code path`. `CometIcebergNativeScanExec` fails the same way.
   
   ## What changes are included in this PR?
   
   Cherry-pick of 695ca3ab7e6edefffffd6e073069561e66086c50 with `-x`.
   
   - A non-bucketed native scan and the Iceberg scan report 
`UnknownPartitioning(0)`. A bucketed scan keeps its bucket layout.
   - `CometNativeExec` sizes their native RDD from the plan data at execution.
   
   Adaptations: the `CometTaskMetricsSuite` change is dropped, because the test 
it edits is not on this branch, and two suites import what the new tests use, 
which `main` already had.
   
   ## How are these changes tested?
   
   The source PR's three tests. In a Linux container on Spark 4.1, 
`CometExecSuite` and `CometIcebergNativeSuite` pass apart from the bucketed 
test, plus the scan, join and DPP suites. On Spark 3.5 the AQE DPP tests in 
both suites pass apart from the same test. With `spark/src/main` reverted, both 
shuffle coalescing tests fail with the errors above.
   
   The bucketed test fails on `branch-1.1` with or without this change, on an 
empty bucket's scan schema, which #7623 fixes. With both applied, all three 
tests pass on Spark 4.1 and 3.5.
   


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