mengxr commented on a change in pull request #24643:
[SPARK-26412][PySpark][SQL] 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_r293602500
##########
File path: python/pyspark/sql/tests/test_pandas_udf_scalar.py
##########
@@ -294,16 +349,23 @@ def test_vectorized_udf_struct_complex(self):
StructField('arr', ArrayType(LongType()))])
@pandas_udf(returnType=return_type)
- def f(id):
+ def scalar_f(id):
return pd.DataFrame({'ts': id.apply(lambda i: pd.Timestamp(i)),
'arr': id.apply(lambda i: [i, i + 1])})
- actual = df.withColumn('f', f(col('id'))).collect()
- for i, row in enumerate(actual):
- id, f = row
- self.assertEqual(i, id)
- self.assertEqual(pd.Timestamp(i).to_pydatetime(), f[0])
- self.assertListEqual([i, i + 1], f[1])
+ @pandas_udf(returnType=return_type,
functionType=PandasUDFType.SCALAR_ITER)
+ def iter_f(it):
+ for id in it:
+ yield pd.DataFrame({'ts': id.apply(lambda i: pd.Timestamp(i)),
Review comment:
minor: Can reuse the code if we don't wrap`@pandas_udf` for the scalar UDF.
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