sunchao commented on PR #5420:
URL: 
https://github.com/apache/datafusion-comet/pull/5420#issuecomment-5806302530

   Thanks, Andy. Addressed the three points in 
[7e9026df4](https://github.com/apache/datafusion-comet/commit/7e9026df4968111be023dbe72610bc4e3df9ba0e):
   
   - The aggregation guide now explicitly says the wide-decimal AVG/TRY_AVG 
fallback moves the whole operator to Spark, including sibling MIN/MAX/COUNT/SUM 
expressions, in both partial and final stages.
   - The global fixture now uses explicit expected results while retaining the 
native-aggregate count assertions. It pins `0.6` at scale 38 for AVG/TRY_AVG, 
including the `repartition(2, col("ord"))` case. The existing `collect_list` 
case explicitly expects NULL: Spark's object aggregate materializes an 
overflowing partial buffer before division.
   - The grouped overflow regression now loops over `jvm` and `native`, 
preserving the legacy AVG, ANSI TRY_AVG, ANSI error, valid-group, and 
all-null-group checks. It asserts the shuffle writer directly above the partial 
aggregate, so the input repartition cannot satisfy the assertion accidentally.
   
   #5421 has merged, and the rebase removed it from this PR's diff. This 
follow-up changes two files. Both affected tests pass on Spark 4.1.3 / JDK 17 
with the current-source native library; full-reactor compilation, Spotless, 
Scalastyle, and whitespace checks pass. [Current-head 
CI](https://github.com/apache/datafusion-comet/actions/runs/35946785166) is 
running with all Spark profiles and Spark 4.1 SQL tests enabled.
   


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