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[SPARK-52519][PS] Enable divide-by-zero for numeric floordiv with ANSI enabled #51209

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@xinrong-meng xinrong-meng commented Jun 17, 2025

What changes were proposed in this pull request?

Enable divide-by-zero for numeric floordiv with ANSI enabled

Why are the changes needed?

Ensure pandas on Spark works well with ANSI mode on.
Part of https://issues.apache.org/jira/browse/SPARK-52169.

Does this PR introduce any user-facing change?

Yes.

>>> spark.conf.get("spark.sql.ansi.enabled")
'true'
>>> ps.set_option("compute.fail_on_ansi_mode", False)
>>> ps.set_option("compute.ansi_mode_support", True)
>>> ps.Series([1, 2]) // 0
0    inf
1    inf
dtype: float64
>>> ps.Series([1, 2]) // ps.Series([0, 0])
0    inf
1    inf
dtype: float64

How was this patch tested?

Unit tests.

(dev3.10) spark (num_floordiv) % SPARK_ANSI_SQL_MODE=true  ./python/run-tests --python-executables=python3.10 --testnames "pyspark.pandas.tests.computation.test_binary_ops FrameBinaryOpsTests.test_binary_operator_floordiv"
...
Tests passed in 6 seconds

(dev3.10) spark (num_floordiv) % SPARK_ANSI_SQL_MODE=false  ./python/run-tests --python-executables=python3.10 --testnames "pyspark.pandas.tests.computation.test_binary_ops FrameBinaryOpsTests.test_binary_operator_floordiv"
...
Tests passed in 4 seconds

Was this patch authored or co-authored using generative AI tooling?

No.


def floordiv(left: PySparkColumn, right: Any) -> PySparkColumn:
return F.when(F.lit(right is np.nan), np.nan).otherwise(
F.when(
F.lit(right != 0) | F.lit(right).isNull(),
F.floor(left.__div__(right)),
).otherwise(F.lit(np.inf).__div__(left))
).otherwise(F.try_divide(F.lit(np.inf), left))
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Don't we need to check the config here?

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Forgot we need to keep the current error, updated thanks!

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@ueshin ueshin left a comment

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LGTM, pending tests.

@@ -369,6 +376,9 @@ def floordiv(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
_sanitize_list_like(right)
if not is_valid_operand_for_numeric_arithmetic(right):
raise TypeError("Floor division can not be applied to given types.")
spark_session = left._internal.spark_frame.sparkSession
use_try_divide = is_ansi_mode_enabled(spark_session)
safe_div = F.try_divide if use_try_divide else lambda x, y: x.__div__(y) # type: ignore
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ditto.

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2 participants