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[WIP][SPARK-52288][PS] Avoid INVALID_ARRAY_INDEX in split when ANSI mode is on #51006

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[WIP][SPARK-52288][PS] Avoid INVALID_ARRAY_INDEX in split when ANSI mode is on #51006

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8 changes: 7 additions & 1 deletion python/pyspark/pandas/strings.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2031,7 +2031,13 @@ def pudf(s: pd.Series) -> pd.Series:
if expand:
psdf = psser.to_frame()
scol = psdf._internal.data_spark_columns[0]
spark_columns = [scol[i].alias(str(i)) for i in range(n + 1)]

if ps.get_option("compute.ansi_mode_support"):
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It seems we can always use the new branch, and remove the configuration read here (which needs one Config RPC)

spark_columns = [
F.try_element_at(scol, F.lit(i + 1)).alias(str(i)) for i in range(n + 1)
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@abhiips07 abhiips07 May 26, 2025 •
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can we try to calculate f.lit(i+1) outside loop? since this might avoid function calls and object creation during loop execution

literals = [F.lit(i + 1) for i in range(n + 1)]

spark_columns = [F.try_element_at(scol, lit).alias(str(i)) for i, lit in enumerate(literals)]

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Thanks for suggestion!
There might not be a significant perf difference between creating F.lit inside the loop or beforehand, it's just wrapping a Python literal into a Spark expression, which aren’t executed immediately(just nodes in the DAG), and will be deduplicated by Catalyst. With that being said I’d like to keep the original for simplicity, but feel free to share if you have other opinions!

]
else:
spark_columns = [scol[i].alias(str(i)) for i in range(n + 1)]
column_labels = [(i,) for i in range(n + 1)]
internal = psdf._internal.with_new_columns(
spark_columns,
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2 changes: 2 additions & 0 deletions python/pyspark/pandas/tests/series/test_string_ops_adv.py
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Expand Up @@ -185,6 +185,8 @@ def test_string_split(self):
with self.assertRaises(NotImplementedError):
self.check_func(lambda x: x.str.split(expand=True))

self.check_func_on_series(lambda x: repr(x.str.split("-", n=1, expand=True)), pser)

@unittest.skipIf(is_ansi_mode_test, ansi_mode_not_supported_message)
def test_string_rsplit(self):
self.check_func_on_series(lambda x: repr(x.str.rsplit()), self.pser[:-1])
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