[SPARK-59091][SQL] Emit the NaN guard in transpiled equality only for floating-point columns - #58901
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September 17, 2026 23:11
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@holdenk PTAL when you get a chance! Thanks in advance! |
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Great work, some questions :)
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What changes were proposed in this pull request?
Split the transpiler's
"numeric"category into"integer"(IntegralType) and"float"(FractionalType, excluding DecimalType). The NaN guard in
_lower_eqis now only emittedwhen at least one operand has category
"float".transpile.py:_categoryreturns"integer"/"float"instead of"numeric"forliterals and parameters;
_param_category_combostries["integer", "float", "string"]per parameter;
_lower_eqgates the guard onlc == "float" or rc == "float";_convert_chunkBinOp dispatch uses_is_numeric_cat()for all three sub-categories.ResolveTranspiledPythonUDFOptions.scala: adds"integer"→ IntegralType and"float"→ FractionalType (excluding Decimal) cases to
optionMatchesTypes.Why are the changes needed?
For integer columns (e.g.
BIGINT), the old plan forx == yincludedisnan(cast(x AS DOUBLE)), which is always false—integers can't be NaN. The NaN guard only makes sense for floating-point types.Does this PR introduce any user-facing change?
No. The generated Catalyst plan for integer-column equality no longer contains dead
isnanguards, but the query results are identical.How was this patch tested?
New Python tests in
test_udf_transpile_unit:test_udf_transpile_integer_eq_no_nan_guard— noisnanin plan forBIGINT ==test_udf_transpile_float_eq_nan_semantics—isnanpresent forDOUBLE ==; NaN and null semantics verified end-to-endtest_udf_transpile_int_float_annotation_categories— unit tests for new category namesNew Scala tests in
ResolveTranspiledPythonUDFOptionsSuite:"integer"/"float"matching, cross-type rejection, DecimalType exclusion, FloatType matching.Was this patch authored or co-authored using generative AI tooling?
Co-authored by: Claude Sonnet 4.6