amaliujia commented on code in PR #38409:
URL: https://github.com/apache/spark/pull/38409#discussion_r1009013217
##########
python/pyspark/sql/connect/dataframe.py:
##########
@@ -305,8 +308,12 @@ def _print_plan(self) -> str:
return self._plan.print()
return ""
- def collect(self) -> None:
- raise NotImplementedError("Please use toPandas().")
+ def collect(self) -> List[Row]:
+ pdf = self.toPandas()
Review Comment:
It is because the returned data batch might not contain a `schema`, and the
python client implementation uses create Pandas from the data batch (e.g. JSON
batch).
If we always include a schema in the data batch, we could drop this
`optional`. I am not familiar enough on Pandas for how to append dtypes to the
DataFrame from PySpark sql StructType though.
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