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https://issues.apache.org/jira/browse/SPARK-61035?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-61035.
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Resolution: Fixed
Issue resolved by pull request 231
[https://github.com/apache/spark-connect-rust/pull/231]
> Send the resource profile of mapInPandas and mapInArrow in the Python client
> as PySpark does
> --------------------------------------------------------------------------------------------
>
> Key: SPARK-61035
> URL: https://issues.apache.org/jira/browse/SPARK-61035
> 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
>
>
> In PySpark Connect, {{df.mapInPandas(func, schema, barrier, profile)}} and
> {{df.mapInArrow(func, schema, barrier, profile)}} send the id of the
> {{ResourceProfile}} {{profile}}, which they create on the server, as the
> {{profile_id}} of their {{MapPartitions}}, so that the stage runs with the
> resources of the profile (stage-level scheduling). Against a server that does
> not support the profile, as one in local mode, an action of the DataFrame
> fails with {{SparkException: TaskResourceProfiles are only supported for
> Standalone, Yarn and Kubernetes cluster for now when dynamic allocation is
> disabled.}}
> The Rust-backed Python client takes {{profile}} and ignores it: the stage
> runs without the resources of the profile, and the action succeeds against a
> server that does not support it. Send the profile as PySpark does.
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