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https://issues.apache.org/jira/browse/FLINK-40471?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=18126259#comment-18126259
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Dian Fu commented on FLINK-40471:
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[~chenzhuo] Thanks for working on this issue.
> could you clarify whether concurrency is intended only for async scalar UDFs?
It applies for any kind of Python UDFs.
> whether batch_size applies to pandas/Arrow UDFs?
Yes, you are right.
> What should happen if either option is supplied for an unsupported UDF kind?
Exception could be raised~
> Add per-UDF concurrency and batch size support to DataFrame API
> ---------------------------------------------------------------
>
> Key: FLINK-40471
> URL: https://issues.apache.org/jira/browse/FLINK-40471
> Project: Flink
> Issue Type: Sub-task
> Reporter: Liu Liu
> Priority: Major
>
> Support specifying per-UDF concurrency and batch size in UDF creation:
> {code:java}
> def udf(
> func=None,
> *,
> return_dtype: DataType = None,
> deterministic: bool = True,
> name: str = None,
> concurrency: Optional[int] = None, // per-UDF concurrency
> batch_size: Optional[int] = None, // per-UDF batch size
> ) -> DataFrameUDFWrapper {code}
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