Lei (Eddy) Xu created SPARK-34600:
-------------------------------------
Summary: Support user defined types in Pandas UDF
Key: SPARK-34600
URL: https://issues.apache.org/jira/browse/SPARK-34600
Project: Spark
Issue Type: New Feature
Components: PySpark, SQL
Affects Versions: 3.1.1, 3.0.2
Reporter: Lei (Eddy) Xu
Because Pandas UDF uses pyarrow to passing data, it does not currently support
UserDefinedTypes, as what normal python udf does.
For example:
{code:python}
class BoxType(UserDefinedType):
@classmethod
def sqlType(cls) -> StructType:
return StructType(
fields=[
StructField("xmin", DoubleType(), False),
StructField("ymin", DoubleType(), False),
StructField("xmax", DoubleType(), False),
StructField("ymax", DoubleType(), False),
]
)
@pandas_udf(
returnType=StructType([StructField("boxes", ArrayType(Box()))]
)
def pandas_pf(s: pd.DataFrame) -> pd.DataFrame:
yield s
{code}
The logs indicate t
{quote}
try:
to_arrow_type(self._returnType_placeholder)
except TypeError:
> raise NotImplementedError(
"Invalid return type with scalar Pandas UDFs: %s is "
E NotImplementedError: Invalid return type with scalar Pandas
UDFs: StructType(List(StructField(boxes,ArrayType(Box,true),true))) is not
supported
{quote}
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