[SPARK-58553][PS][FOLLOWUP] Preserve signed zero in NumPy fmax and fmin - #57819
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zhengruifeng wants to merge 3 commits into
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[SPARK-58553][PS][FOLLOWUP] Preserve signed zero in NumPy fmax and fmin#57819zhengruifeng wants to merge 3 commits into
zhengruifeng wants to merge 3 commits into
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uros-b
approved these changes
Aug 6, 2026
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What changes were proposed in this pull request?
This follow-up fixes the native
np.fmaxandnp.fminmappings to preserve the first operand when the operands compare equal. This preserves NumPy signed-zero behavior while retaining the existing NaN handling and native Spark expressions.Why are the changes needed?
Spark
greatestandleastorder-0.0and+0.0, whereas NumPy retains the first operand for an equal-value tie. Consequently, the prior mapping returned the wrong signed zero forfmax(-0.0, 0.0)andfmin(0.0, -0.0).Does this PR introduce any user-facing change?
Yes. It corrects the sign of zero for the affected
np.fmaxandnp.fmininputs.How was this patch tested?
Added signbit-based regression coverage for both signed-zero operand orders.
python/run-tests --testnames pyspark.pandas.tests.test_numpy_compat.NumPyCompatTests.test_np_fmax_fminpython/run-tests --testnames pyspark.pandas.tests.connect.test_parity_numpy_compat.NumPyCompatParityTests.test_np_fmax_fminWas this patch authored or co-authored using generative AI tooling?
Generated-by: Codex GPT-5