[SPARK-58465][PS] Use native expressions for NumPy reciprocal of floating-point columns - #57668
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[SPARK-58465][PS] Use native expressions for NumPy reciprocal of floating-point columns#57668zhengruifeng wants to merge 1 commit into
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What changes were proposed in this pull request?
Use native Spark SQL expressions for NumPy reciprocal on pandas-on-Spark columns with Spark
floatordoubletypes. The expressions preserve nulls, NaN, infinity, and signed zero. Inputs with other types continue to use the existing pandas UDF.Why are the changes needed?
Native expressions avoid the Python worker boundary for floating-point reciprocal while retaining the established behavior for input types with NumPy-specific semantics.
Does this PR introduce any user-facing change?
No. The behavior and result type remain unchanged.
How was this patch tested?
NumPyCompatTests.test_np_math_functions.NumPyCompatTests.test_np_math_functionsandNumPyCompatTests.test_np_spark_compat_series.python/pyspark/pandas/numpy_compat.py.Was this patch authored or co-authored using generative AI tooling?
Generated-by: Codex (GPT-5)