HyukjinKwon commented on code in PR #46694:
URL: https://github.com/apache/spark/pull/46694#discussion_r1609622792
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python/pyspark/sql/connect/plan.py:
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@@ -547,14 +550,49 @@ class CachedRemoteRelation(LogicalPlan):
"""Logical plan object for a DataFrame reference which represents a
DataFrame that's been
cached on the server with a given id."""
- def __init__(self, relationId: str):
+ def __init__(self, relation_id: str, spark_session: "SparkSession"):
super().__init__(None)
- self._relationId = relationId
-
- def plan(self, session: "SparkConnectClient") -> proto.Relation:
- plan = self._create_proto_relation()
- plan.cached_remote_relation.relation_id = self._relationId
- return plan
+ self._relation_id = relation_id
+ # Needs to hold the session to make a request itself.
+ self._spark_session = spark_session
+
+ def plan(self, session: "SparkConnectClient") -> proto.Relation:
+ plan = self._create_proto_relation()
+ plan.cached_remote_relation.relation_id = self._relation_id
+ return plan
+
+ def __del__(self) -> None:
+ session = self._spark_session
+ # If session is already closed, all cached DataFrame should be
released.
Review Comment:
I don't think so.. we can only tell when to release at the client side
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