WeichenXu123 commented on code in PR #50199:
URL: https://github.com/apache/spark/pull/50199#discussion_r1990366864
##########
python/pyspark/ml/util.py:
##########
@@ -185,29 +185,40 @@ def wrapped(self: "JavaWrapper", dataset:
"ConnectDataFrame") -> Any:
assert isinstance(self._java_obj, str)
params = serialize_ml_params(self, session.client)
- return ConnectDataFrame(
- TransformerRelation(
- child=dataset._plan, name=self._java_obj,
ml_params=params, is_model=True
- ),
- session,
+ plan = TransformerRelation(
+ child=dataset._plan,
+ name=self._java_obj,
+ ml_params=params,
+ is_model=True,
)
elif isinstance(self, Transformer):
from pyspark.ml.connect.proto import TransformerRelation
assert isinstance(self._java_obj, str)
params = serialize_ml_params(self, session.client)
- return ConnectDataFrame(
- TransformerRelation(
- child=dataset._plan,
- name=self._java_obj,
- ml_params=params,
- uid=self.uid,
- is_model=False,
- ),
- session,
+ plan = TransformerRelation(
+ child=dataset._plan,
+ name=self._java_obj,
+ ml_params=params,
+ uid=self.uid,
+ is_model=False,
)
+
else:
raise RuntimeError(f"Unsupported {self}")
+
+ # To delay the GC of the model, keep a reference to the source
transformer
+ # in the transformed dataframe and all its descendants.
+ # For this case:
+ #
+ # def fit_transform(df):
+ # model = estimator.fit(df)
+ # return model.transform(df)
+ #
+ # output = fit_transform(df)
+ #
+ plan.__source_transformer__ = self # type: ignore[attr-defined]
Review Comment:
For model summary, it might also return Dataframe, shall we make similar
change ?
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