mengxr commented on a change in pull request #24643:
[SPARK-26412][PySpark][SQL][WIP] Allow Pandas UDF to take an iterator of
pd.Series or an iterator of tuple of pd.Series
URL: https://github.com/apache/spark/pull/24643#discussion_r291395710
##########
File path: python/pyspark/worker.py
##########
@@ -255,13 +269,54 @@ def read_udfs(pickleSer, infile, eval_type):
# Scalar Pandas UDF handles struct type arguments as pandas DataFrames
instead of
# pandas Series. See SPARK-27240.
- df_for_struct = eval_type == PythonEvalType.SQL_SCALAR_PANDAS_UDF
+ df_for_struct = (eval_type == PythonEvalType.SQL_SCALAR_PANDAS_UDF or
+ eval_type ==
PythonEvalType.SQL_SCALAR_PANDAS_ITER_UDF)
ser = ArrowStreamPandasUDFSerializer(timezone, safecheck,
assign_cols_by_name,
df_for_struct)
else:
ser = BatchedSerializer(PickleSerializer(), 100)
num_udfs = read_int(infile)
+
+ if eval_type == PythonEvalType.SQL_SCALAR_PANDAS_ITER_UDF:
+ assert num_udfs == 1, "One SQL_SCALAR_PANDAS_ITER_UDF expected here."
+
+ arg_offsets, udf = read_single_udf(
+ pickleSer, infile, eval_type, runner_conf, udf_index=i)
+
+ def func(_, iterator):
+ num_input_rows = [0]
Review comment:
define `num_input_rows` outside func and then you shouldn't need to wrap the
value inside array
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