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[SPARK-44876][PYTHON][FOLLOWUP][3.5] Fix Arrow-optimized Python UDF to delay wrapping the function with fail_on_stopiteration #42785

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[SPARK-44876][PYTHON][FOLLOWUP][3.5] Fix Arrow-optimized Python UDF to delay wrapping the function with fail_on_stopiteration #42785

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21 changes: 18 additions & 3 deletions python/pyspark/sql/tests/test_udf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,7 +24,7 @@

from pyspark import SparkContext, SQLContext
from pyspark.sql import SparkSession, Column, Row
from pyspark.sql.functions import udf, assert_true, lit, rand
from pyspark.sql.functions import col, udf, assert_true, lit, rand
from pyspark.sql.udf import UserDefinedFunction
from pyspark.sql.types import (
StringType,
Expand All @@ -38,9 +38,9 @@
TimestampNTZType,
DayTimeIntervalType,
)
from pyspark.errors import AnalysisException, PySparkTypeError
from pyspark.errors import AnalysisException, PythonException, PySparkTypeError
from pyspark.testing.sqlutils import ReusedSQLTestCase, test_compiled, test_not_compiled_message
from pyspark.testing.utils import QuietTest
from pyspark.testing.utils import QuietTest, assertDataFrameEqual


class BaseUDFTestsMixin(object):
Expand Down Expand Up @@ -898,6 +898,21 @@ def test_complex_return_types(self):
self.assertEquals(row[1], {"a": "b"})
self.assertEquals(row[2], Row(col1=1, col2=2))

def test_raise_stop_iteration(self):
@udf("int")
def test_udf(a):
if a < 5:
return a
else:
raise StopIteration()

assertDataFrameEqual(
self.spark.range(5).select(test_udf(col("id"))), [Row(i) for i in range(5)]
)

with self.assertRaisesRegex(PythonException, "StopIteration"):
self.spark.range(10).select(test_udf(col("id"))).show()


class UDFTests(BaseUDFTestsMixin, ReusedSQLTestCase):
@classmethod
Expand Down
22 changes: 7 additions & 15 deletions python/pyspark/worker.py
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Original file line number Diff line number Diff line change
Expand Up @@ -154,20 +154,9 @@ def wrap_arrow_batch_udf(f, return_type):
elif type(return_type) == BinaryType:
result_func = lambda r: bytes(r) if r is not None else r # noqa: E731

@fail_on_stopiteration
def evaluate(*args: pd.Series) -> pd.Series:
return pd.Series(result_func(f(*a)) for a in zip(*args))

def verify_result_type(result):
if not hasattr(result, "__len__"):
pd_type = "pandas.DataFrame" if type(return_type) == StructType else "pandas.Series"
raise PySparkTypeError(
error_class="UDF_RETURN_TYPE",
message_parameters={
"expected": pd_type,
"actual": type(result).__name__,
},
)
return result
return pd.Series([result_func(f(*a)) for a in zip(*args)])

def verify_result_length(result, length):
if len(result) != length:
Expand All @@ -181,7 +170,7 @@ def verify_result_length(result, length):
return result

return lambda *a: (
verify_result_length(verify_result_type(evaluate(*a)), len(a[0])),
verify_result_length(evaluate(*a), len(a[0])),
arrow_return_type,
)

Expand Down Expand Up @@ -543,7 +532,10 @@ def read_single_udf(pickleSer, infile, eval_type, runner_conf, udf_index):
else:
chained_func = chain(chained_func, f)

if eval_type == PythonEvalType.SQL_SCALAR_PANDAS_ITER_UDF:
if eval_type in (
PythonEvalType.SQL_SCALAR_PANDAS_ITER_UDF,
PythonEvalType.SQL_ARROW_BATCHED_UDF,
):
func = chained_func
else:
# make sure StopIteration's raised in the user code are not ignored
Expand Down