I'm curious about how this lines up with
https://github.com/apache/spark/pull/53435/changes , I'd love to see more
zero copy solutions and this seems more IPC oriented. Perhaps both?

On Thu, Feb 19, 2026 at 11:42 AM Lisa N. Cao <[email protected]>
wrote:

> Seems like a good way upfront to avoid lang-specific headaches in the
> future.
>
> --
> LNC
>
>
> On Thu, Feb 19, 2026 at 11:03 AM Ángel Álvarez Pascua <
> [email protected]> wrote:
>
>> Hmmm.... sounds like a great idea to me!
>>
>> El jue, 19 feb 2026, 19:47, Haiyang Sun via dev <[email protected]>
>> escribió:
>>
>>> Hi all,
>>>
>>> I’d like to start a discussion on a draft SPIP: Language-agnostic UDF
>>> Protocol for Spark
>>>
>>> JIRA: https://issues.apache.org/jira/browse/SPARK-55278
>>>
>>> Doc:
>>> https://docs.google.com/document/d/19Whzq127QxVt2Luk0EClgaDtcpBsFUp67NcVdKKyPF8/edit?tab=t.0
>>>
>>> tl;dr
>>>
>>> The SPIP proposes a structured, language-agnostic execution protocol for
>>> running user-defined functions (UDFs) in Spark across multiple programming
>>> languages.
>>>
>>> Today, Spark Connect allows users to write queries from multiple
>>> languages, but support for user-defined functions remains incomplete. In
>>> practice, only Scala / Java / Python / R have working support, and it
>>> relies on language-specific mechanisms that do not generalize well to other
>>> languages such as Go (Apache Spark Connect Go
>>> <https://github.com/apache/spark-connect-go>), Rust (Apache Spark
>>> Connect Rust <https://github.com/apache/spark-connect-rust>), Swift (Apache
>>> Spark Connect Swift <https://github.com/apache/spark-connect-swift>),
>>> or .NET (Spark Connect DotNet
>>> <https://github.com/GoEddie/spark-connect-dotnet>), where UDF support
>>> is currently unavailable. There are also legacy limitations around the
>>> existing PySpark worker.py implementation that can be improved with the
>>> proposal.
>>>
>>> This proposal aims to define a unified API and execution protocol for
>>> UDFs that run outside the Spark executor process and communicate with Spark
>>> via inter-process communication (IPC). The goal is to enable Spark to
>>> interact with external workers in a consistent and extensible way,
>>> regardless of the implementation language.
>>>
>>> I’m happy to help drive the discussion and development of this proposal,
>>> and I would greatly appreciate feedback from the community.
>>>
>>> Thanks,
>>>
>>> Haiyang Sun
>>>
>>

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