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https://issues.apache.org/jira/browse/ARROW-15635?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17585501#comment-17585501
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Todd Farmer edited comment on ARROW-15635 at 8/26/22 4:16 PM:
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This issue was last updated over 90 days ago, which may be an indication it is
no longer being actively worked. To better reflect the current state, the issue
is being unassigned per [project
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Please feel free to re-take assignment of the issue if it is being actively
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was (Author: JIRAUSER288796):
This issue was last updated over 90 days ago, which may be an indication it is
no longer being actively worked. To better reflect the current state, the issue
is being unassigned per [project
policy|https://arrow.apache.org/docs/dev/developers/bug_reports.html#issue-assignment.
Please feel free to re-take assignment of the issue if it is being actively
worked, or if you plan to start that work soon.
> [C++][Python] UDF Integration
> ------------------------------
>
> Key: ARROW-15635
> URL: https://issues.apache.org/jira/browse/ARROW-15635
> Project: Apache Arrow
> Issue Type: Task
> Components: C++, Python
> Reporter: Vibhatha Lakmal Abeykoon
> Priority: Major
> Labels: pull-request-available
> Time Spent: 2h 20m
> Remaining Estimate: 0h
>
> The objective is to list down a set of tasks required to provide UDF support
> for Apache Arrow streaming execution engine. In the first iteration we will
> be focusing on providing support for Python-based UDFs which can support
> Python functions.
> The UDF Integration is going to pan out with a series of sub-tasks associated
> with the development and PoCs. Note that this is going to be the first
> iteration of UDF integrations with a limited scope. This ticket will cover
> the following topics;
> # POC for UDF integration: The objective is to evaluate the existing
> components in the source and evaluate the required modifications and new
> building blocks required to integrate UDFs.
> # The language will be limited to C+{+}/{+}Python users can register Python
> function as a UDF and use it with an `apply` method on Arrow Tables or
> provide a computation API endpoint via arrow::compute API. Note that the C+
> API already provides a way to register custom functions via the function
> registry API. At the moment this is not exposed to Python.
> # Planned features for this ticket are;
> ## Scalar UDFs : UDFs executed per value (per row)
> ## Vector UDFs : UDFs executed per batch (a full array or partial array)
> ## Aggregate UDFs : UDFs associated with an aggregation operation
> # Integration limitations
> ## Doesn't support custom data types which doesn't support Numpy or Pandas
> ## Complex processing with parallelism within UDFs are not supported
> ## Parallel UDFs are not supported in the initial version of UDFs. Allthough
> we are documenting what is required and a rough sketch for the next phase.
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