ulysses-you opened a new pull request, #58106:
URL: https://github.com/apache/spark/pull/58106

   ### What changes were proposed in this pull request?
   
   Extend runtime adaptive partial aggregation 
(`spark.sql.execution.aggregate.adaptivePartialAggregation.enabled`) to support 
the DISTINCT intermediate phase, whose aggregate modes are `PartialMerge ++ 
Partial` (non-distinct aggregates in `PartialMerge`, distinct aggregates in 
`Partial`). Previously the feature only bypassed partial aggregates whose 
functions were all in `Partial` mode, so this phase was excluded.
   
   ### Why are the changes needed?
   
   Bypassing a `PartialMerge` member is safe because the pass-through merges 
the incoming buffer into an empty buffer, which leaves it unchanged (the 
existing first-insertion of a key already relies on `merge(initial, x) == x`), 
and the downstream `Final` re-merges it. This lets high-cardinality DISTINCT 
queries benefit from the bypass. A pure `PartialMerge` de-duplication phase 
must still not bypass (it would over-count DISTINCT); it is kept out by its 
required distribution plus a defensive `exists(_.mode == Partial)` guard.
   
   ### Does this PR introduce _any_ user-facing change?
   
   No.
   
   ### How was this patch tested?
   
   Added tests to `AdaptivePartialAggregationSuite` covering DISTINCT with 
plain and filtered non-distinct aggregates, and an imperative aggregate in the 
DISTINCT intermediate phase.
   
   ### Was this patch authored or co-authored using generative AI tooling?
   
   Yes. Generated-by: Claude Code (Anthropic).
   


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