[SPARK-59091][SQL] Emit the NaN guard in transpiled equality only for floating-point columns

[jzhan-2026]

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_eq is now only emitted
when at least one operand has category "float".

• transpile.py: _category returns "integer" / "float" instead of "numeric" for
  literals and parameters; _param_category_combos tries ["integer", "float", "string"]
  per parameter; _lower_eq gates the guard on lc == "float" or rc == "float";
  _convert_chunk BinOp 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 for x == y included isnan(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 isnan guards, 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 — no isnan in plan for BIGINT ==
• test_udf_transpile_float_eq_nan_semantics — isnan present for DOUBLE ==; NaN and null semantics verified end-to-end
• test_udf_transpile_int_float_annotation_categories — unit tests for new category names

New 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

[jzhan-2026]

@holdenk PTAL when you get a chance! Thanks in advance!