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https://issues.apache.org/jira/browse/SPARK-51537?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Hyukjin Kwon resolved SPARK-51537.
----------------------------------
Fix Version/s: 4.1.0
Resolution: Fixed
Issue resolved by pull request 50334
[https://github.com/apache/spark/pull/50334]
> Failed to run third-party Spark ML library on Spark Connect
> ------------------------------------------------------------
>
> Key: SPARK-51537
> URL: https://issues.apache.org/jira/browse/SPARK-51537
> Project: Spark
> Issue Type: Bug
> Components: Connect, ML
> Affects Versions: 4.0.0
> Reporter: Bobby Wang
> Assignee: Bobby Wang
> Priority: Major
> Labels: pull-request-available
> Fix For: 4.1.0
>
>
> I've encountered an issue where the third-party Spark ML library may not run
> on Spark Connect. This problem occurs when specifying the
> third-party ML jar using the *--jars* configuration while creating a connect
> server
> based on a Spark standalone cluster.
>
> The exception thrown is a ClassCastException:
>
> _Caused by: java.lang.ClassCastException: cannot assign instance of
> java.lang.invoke.SerializedLambda to field
> org.apache.spark.rdd.MapPartitionsRDD.f of type scala.Function3 in instance
> of org.apache.spark.rdd.MapPartitionsRDD_
> _at
> java.io.ObjectStreamClass$FieldReflector.setObjFieldValues(ObjectStreamClass.java:2096)_
>
> However, if I place the ML jar into the *$SPARK_HOME/jars* directory and
> restart both the Spark standalone cluster and the Spark Connect server, it
> runs without any exceptions.
>
> Alternatively, adding
> *spark.addArtifacts("target/com.example.ml-1.0-SNAPSHOT.jar")* directly in
> the python code also resolves the issue.
>
> I have made a minimum project which can repro this issue, more details could
> be found at [https://github.com/wbo4958/ConnectMLIssue]
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