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https://issues.apache.org/jira/browse/SPARK-61120?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon reassigned SPARK-61120:
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Assignee: Hyukjin Kwon
> Add DataFrame._session, SparkSession._client, and the methods and results of
> the client that vendored modules use, in the Python client as PySpark does
> -------------------------------------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-61120
> URL: https://issues.apache.org/jira/browse/SPARK-61120
> Project: Spark
> Issue Type: Bug
> Components: Connect
> Affects Versions: connect-rust-4.3.0
> Reporter: Hyukjin Kwon
> Assignee: Hyukjin Kwon
> Priority: Major
> Labels: pull-request-available
> Fix For: connect-rust-4.3.0
>
>
> Modules vendored from Apache Spark v4.3.0 read private attributes of PySpark
> Connect's DataFrame, session and client that the Python client lacks:
> * {{DataFrame._session}}, the session of a DataFrame, which these read:
> ** {{pyspark.ml.util._cache_spark_dataset}}, which {{CrossValidator}} and
> {{TrainValidationSplit}} use with {{SPARKML_TEMP_DFS_PATH}}
> ** {{pyspark.sql.plot}}, for the maximum rows of a plot
> ** {{select_dtypes}} of {{pyspark.pandas}}
> On the client, {{df._session}} is a Column of that name, so with
> {{SPARKML_TEMP_DFS_PATH}} set, {{CrossValidator(...).fit(df)}} raises
> {{TypeError: 'Column' object is not callable}}.
> * {{SparkSession._client}} and {{SparkConnectClient._resources()}}, of which
> {{TorchDistributor}} reads the resources of the cluster on Spark Connect. The
> client has neither.
> * PySpark's {{SparkConnectClient.execute_command}} returns the result of a
> {{get_resources_command}} as a dict of {{ResourceInformation}}, of a
> {{create_resource_profile_command}} as its profile ID, and of a
> {{checkpoint_command}} as a DataFrame of its cached relation, and it also
> returns the {{pipeline_event_result}} of a response. The client returns the
> first as its message, and none of the others.
> The fix is to add them, as PySpark has them.
> The client also lacks {{SparkConnectClient.release_session()}}, which
> releases the session on the server, and {{close()}}, which closes the client.
> Apache Spark's {{test_newSession_returns_distinct_instance}} calls them.
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