[SPARK-58630][PS] Use native Spark expressions for NumPy copysign - #57836
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Yicong-Huang wants to merge 2 commits into
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[SPARK-58630][PS] Use native Spark expressions for NumPy copysign#57836Yicong-Huang wants to merge 2 commits into
Yicong-Huang wants to merge 2 commits into
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uros-b
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Aug 7, 2026
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What changes were proposed in this pull request?
Replace the
numpy.copysignpandas UDF mapping inpython/pyspark/pandas/numpy_compat.pywith a native Spark SQL expression (umbrella: SPARK-58532).copysign(x, y)returns|x|with the sign ofy. The sign is taken fromy's IEEE-754 sign bit:-0.0counts as negative (detected via a string cast, as the existingreciprocalmapping does) rather than viay < 0, which misses-0.0. NaN falls through to a positive sign. Null handling is type-aware: a floatycolumn carries missing values as NaN (surfaced as NULL), wherecopysign(x, NaN)is|x|; an integerycolumn's NULL is genuine and propagates.Why are the changes needed?
Native expressions avoid pandas UDF serialization/worker overhead and work uniformly on classic and Spark Connect.
Does this PR introduce any user-facing change?
No.
How was this patch tested?
Added
test_np_copysignandtest_np_copysign_signed_zero(also run via the Spark Connect parity suite), covering integer/float/nullable-integer inputs and assertingnp.signbitfor the signed-zero, NaN, null, and+-infedge cases.Was this patch authored or co-authored using generative AI tooling?
No.