Cached AQE queries fail after transition reversion on Spark 4.0+

[sam-1112]

Describe the bug

RevertNativeForTransitionHeavyStages assumes result stages always produce rows, passing outputColumnar = false at both result-stage call sites.

On Spark 4.0+, cached queries can require columnar output. When the cache serializer accepts columnar input, as Comet’s ArrowCachedBatchSerializer does, Spark marks the cached AdaptiveSparkPlanExec columnar and AQE plans the final stage with outputsColumnar = true.

Forced transition reversion does not preserve this output format and the cached query fails with:

FilterExec has column support mismatch

Steps to reproduce

Andy reported the following reproduction during his review of #5957:

1. Enable Comet and configure ArrowCachedBatchSerializer as the cache serializer.

2. Set:

   spark.sql.adaptive.enabled=true
   spark.comet.exec.transitionRevert.enabled=true
   spark.comet.exec.transitionRevert.maxTransitions=0
   spark.comet.exec.filter.enabled=false
   

3. Run the following query over tbl, cache the resulting DataFrame, and collect it:

   SELECT _2, s
   FROM (
     SELECT _2, sum(_1) AS s
     FROM tbl
     GROUP BY _2
   )
   WHERE s > 10
   

4. Observe FilterExec has column support mismatch.

Expected behavior

The cached query should execute successfully and match Spark’s results. Stage reversion should preserve the columnar output required by the cache consumer.

Additional context

This is a follow-up to Andy’s review comment on #5957. Andy confirmed that main fails the same way, so this is not a regression introduced by that PR.

The proposed fix is to replace outputColumnar = false at both result-stage call sites with:

outputColumnar = plan.supportsColumnar && !plan.supportsRowBased

Andy tested this change locally: the reproduction and all tests in RevertNativeForTransitionHeavyStagesSuite passed.

Regression coverage should exercise Spark 4.0+ with AQE, caching, and forced transition reversion. The test should install the cache serializer as CometInMemoryCacheSuite does, including clearing Spark’s memoized serializer before and after the suite.