zhengruifeng commented on code in PR #40260:
URL: https://github.com/apache/spark/pull/40260#discussion_r1123992438
##########
python/pyspark/sql/connect/_typing.py:
##########
@@ -57,7 +57,7 @@ class UserDefinedFunctionLike(Protocol):
deterministic: bool
@property
- def returnType(self) -> DataType:
+ def returnType(self) -> DataTypeOrString:
Review Comment:
Yeah, but I am still confused about it:
that the old implementation
`PySparkSession.builder.getOrCreate().createDataFrame(data=[],
schema=data_type).schema` works.
I also tried
```
session = PySparkSession.builder.getOrCreate()
parsed = session.client._analyze( # type: ignore[attr-defined]
method="ddl_parse", ddl_string=data_type
).parsed
```
and at least the tests passed.
But if I try
```
parsed = PySparkSession.builder.getOrCreate().client._analyze( # type:
ignore[attr-defined]
method="ddl_parse", ddl_string=data_type
).parsed
```
the tests always fail with `ValueError: Cannot invoke RPC on closed channel!`
Maybe we will have to add a pure python ddl parser, i don't know
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