allisonwang-db commented on code in PR #50099:
URL: https://github.com/apache/spark/pull/50099#discussion_r1978456503
##########
python/pyspark/sql/tests/test_udtf.py:
##########
@@ -2948,21 +2948,21 @@ def eval(self):
err = "UDTF_ARROW_TYPE_CAST_ERROR"
for ret_type, expected in [
- ("x: boolean", [Row(x=True)]),
- ("x: tinyint", [Row(x=1)]),
- ("x: smallint", [Row(x=1)]),
- ("x: int", [Row(x=1)]),
- ("x: bigint", [Row(x=1)]),
+ ("x: boolean", err),
+ ("x: tinyint", err),
+ ("x: smallint", err),
+ ("x: int", err),
+ ("x: bigint", err),
Review Comment:
Is this a behavior change? I wonder if we should have a separate flag for
enabling this optimization.
##########
python/pyspark/sql/pandas/serializers.py:
##########
@@ -161,9 +161,12 @@ def wrap_and_init_stream():
assert isinstance(batch, pa.RecordBatch)
# Wrap the root struct
- struct = pa.StructArray.from_arrays(
- batch.columns, fields=pa.struct(list(batch.schema))
- )
+ if len(batch.columns) == 0:
+ struct = pa.array([{}] * batch.num_rows)
Review Comment:
Nit: can we add a comment on why we need this special handling?
##########
python/pyspark/sql/tests/test_udtf.py:
##########
@@ -350,10 +351,7 @@ def terminate(self, a: int):
TestUDTF(lit(1)).show()
def test_udtf_with_wrong_num_output(self):
- err_msg = (
- r"\[UDTF_RETURN_SCHEMA_MISMATCH\] The number of columns in the "
- "result does not match the specified schema."
- )
+ err_msg = "(UDTF_ARROW_TYPE_CAST_ERROR|UDTF_RETURN_SCHEMA_MISMATCH)"
Review Comment:
Why do we need to check both error classes?
##########
python/pyspark/sql/pandas/serializers.py:
##########
@@ -175,6 +178,16 @@ def wrap_and_init_stream():
return super(ArrowStreamUDFSerializer,
self).dump_stream(wrap_and_init_stream(), stream)
+class ArrowStreamUDTFSerializer(ArrowStreamUDFSerializer):
+ """
+ Same as :class:`ArrowStreamSerializer` but it flattens the struct to Arrow
record batch
+ for applying each function with the raw record arrow batch. See also
`DataFrame.mapInArrow`.
+ """
+
+ def load_stream(self, stream):
+ return ArrowStreamSerializer.load_stream(self, stream)
Review Comment:
Shall we update the this doc? It looks like we don't flatten the struct now
##########
python/pyspark/worker.py:
##########
@@ -976,6 +977,8 @@ def use_large_var_types(runner_conf):
# ensure the UDTF is valid. This function also prepares a mapper function for
applying
# the UDTF logic to input rows.
def read_udtf(pickleSer, infile, eval_type):
+ prefers_large_var_types = False
Review Comment:
What is this larger_var_types?
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