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https://issues.apache.org/jira/browse/SPARK-61048?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon updated SPARK-61048:
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Fix Version/s: connect-rust-4.3.0
> Expose the sparkSession of spark.udf, and send the return type of
> registerJavaFunction, in the Python client as PySpark does
> ----------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-61048
> URL: https://issues.apache.org/jira/browse/SPARK-61048
> Project: Spark
> Issue Type: Bug
> Components: Connect
> Affects Versions: connect-rust-4.3.0
> Reporter: Hyukjin Kwon
> Priority: Major
> Fix For: connect-rust-4.3.0
>
>
> In PySpark Connect, {{spark.udf}} is a {{UDFRegistration}} whose
> {{sparkSession}} is the session, and {{spark.udf.registerJavaFunction(name,
> javaClassName, returnType)}} sends its return type in the {{JavaUDF}} of the
> {{RegisterFunction}} command: a DDL string as an unparsed data type, which
> the server parses, and a DataType as itself. It raises
> {{UNSUPPORTED_OPERATION}} of "data type ..." for a return type that is
> neither, and sends the function as not deterministic.
> The Rust-backed Python client names the session {{spark_session}}, and parses
> the {{simpleString}} of the return type in the client: an invalid DDL string
> raises {{INVALID_DATATYPE_FORMAT}} rather than the {{PARSE_SYNTAX_ERROR}} of
> the server, and a return type that is not a DataType raises an
> {{AttributeError}}. Take them as PySpark does.
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