HyukjinKwon commented on PR #57899:
URL: https://github.com/apache/spark/pull/57899#issuecomment-5248672428

   Thanks for the review, @dongjoon-hyun! Addressed all the nits in 
d8444567c4a9:
   
   1. **Arrow return-type guard** — the non-iterator element-wise Arrow branch 
now calls `verify_scalar_result`, so a non-array-like result raises the 
friendly `UDF_RETURN_TYPE` error (matching the base `SQL_SCALAR_ARROW_UDF` 
path) instead of a bare `TypeError` from `len()`.
   2. **Overstated test comment** — corrected in 
`test_scalar_pandas_udf_in_lambda`; the second assertion only exercises 
arithmetic composition, so the comment no longer claims `filter`/`array_sort` 
coverage.
   3. **ArrowEvalPythonExec Scaladoc** — extended the supported-eval-types list 
to include the element-wise types (102 and the new 103-106). Also 
fully-qualified the dangling `[[PythonEvalType.SQL_ARROW_ELEMENTWISE_UDF]]` 
link in `ExtractPythonUDFFromLambda`.
   4. **Added coverage** — `test_chained_vectorized_udfs_in_lambda` (`f(g(x))` 
for both non-iterator and iterator flavors, asserted against the native 
equivalent) and `test_scalar_iter_udf_struct_element_return_type` (iterator 
struct/DataFrame return).
   
   I left the duplicated re-nest logic (`renest_spec` in the 102 path vs 
`_elementwise_renest`) as a follow-up, as suggested.
   


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