sunchao commented on code in PR #5403:
URL: https://github.com/apache/datafusion-comet/pull/5403#discussion_r3837146731


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spark/src/test/resources/sql-tests/expressions/array/array_min.sql:
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@@ -49,16 +49,16 @@ INSERT INTO test_array_min_double VALUES
 query
 SELECT array_min(arr) FROM test_array_min_double
 
--- Spark treats +0.0 and -0.0 as equal and returns +0.0; Comet returns -0.0.
--- Surfaced by https://github.com/apache/datafusion-comet/issues/5271
+-- Spark preserves the first equal zero (+0.0 here); the native minimum 
returns -0.0.
+-- Native parity is tracked by 
https://github.com/apache/datafusion-comet/issues/5401.
 statement
 CREATE TABLE test_array_min_dbl_negzero(arr array<double>) USING parquet
 
 statement
 INSERT INTO test_array_min_dbl_negzero VALUES
   (array(0.0, double('-0.0'), 1.0))
 
-query ignore(array_min signed-zero: Spark +0.0, Comet -0.0)
+query ignore(https://github.com/apache/datafusion-comet/issues/5401)

Review Comment:
   For cases where fallback is expected, I agree that `query 
expect_fallback(...)` is a better regression check than `ignore`.
   
   I've reworked `array_min` and `array_max` locally to follow Spark's ordering 
natively. In that revision, these signed-zero cases use plain `query` 
assertions, so they must execute natively and match Spark in both strict and 
non-strict modes. The separate non-default-collation tests use `query 
expect_fallback(...)`, since those cases still require Spark by default.
   
   The rework is ready locally but hasn't been pushed yet, so the current PR 
diff still contains the old `ignore`. I'll update the branch once I can publish 
it.



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