HyukjinKwon commented on PR #58790:
URL: https://github.com/apache/spark/pull/58790#issuecomment-5672891793

   <!-- ai-code-review -->
   **Review — [PYTHON] Handle nonfinite values in assertDataFrameEqual**
   
   LGTM. The fix in `compare_vals` is correct. Previously the float branch only 
did `abs(val1 - val2) > (atol + rtol * abs(val2))`; since `abs(nan - x)` is 
`nan` and `nan > y` is `False`, a `NaN` silently compared **equal** to any 
finite value. The new guards make `NaN` equal only to `NaN`, and `inf`/`-inf` 
compare by exact equality. The early `return`s don't skip any tail logic — the 
finite path's only other exit is `return False`, otherwise it falls through to 
the same trailing `return True`. Because both list and DataFrame inputs flow 
through `compare_vals`, the fix covers both.
   
   I exercised the behavior directly (list inputs need no JVM): `NaN` vs 
finite/`inf` → unequal; `NaN`/`inf`/`-inf` vs themselves → equal; `rtol` 
tolerance and nested `Row`/list/map cases all behave as asserted.
   
   The tests are well chosen — both argument orders, `checkRowOrder`, tolerance 
settings, and nested structures — and 
`NonFiniteComparisonTests(unittest.TestCase)` is the right minimal base since 
the list inputs require no `SparkSession`.
   
   Optional nit: the title has no `[SPARK-xxxxx]` id. For a behavior bug fix 
Spark usually wants a JIRA ticket unless it is intentionally kept trivial/minor.
   


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