andygrove opened a new issue, #1989:
URL: https://github.com/apache/datafusion-ballista/issues/1989

   **Is your feature request related to a problem or challenge?**
   
   The adaptive execution path does not switch from streaming aggregation to 
hash aggregation (or vice versa) based on runtime statistics. Streaming 
aggregation depends on sorted input and assumptions about group cardinality; 
when runtime statistics contradict the plan-time estimate, the chosen 
aggregation strategy can be suboptimal.
   
   **Describe the solution you'd like**
   
   Add an adaptive physical optimizer rule that reconsiders the aggregation 
strategy for not-yet-resolved aggregate stages using exact runtime statistics 
(input ordering, group cardinality), switching between streaming and hash 
aggregation as appropriate.
   
   ## Context
   
   This is one of the documented limitations of the experimental Adaptive Query 
Execution (AQE) path, listed in 
[`docs/source/user-guide/tuning-guide.md`](https://github.com/apache/datafusion-ballista/blob/main/docs/source/user-guide/tuning-guide.md)
 under "Current limitations" and in the doc comment on `AdaptiveExecutionGraph` 
(`ballista/scheduler/src/state/aqe/mod.rs`). Filing a discrete tracking issue 
so the gap is visible outside the doc.
   
   Parent epic: #1359


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