Thanks everyone for the feedback! Since there are no objections, I will
work with a PMC member to create the repo.

On Sun, Aug 23, 2026 at 8:31 AM Uroš Bojanić <[email protected]> wrote:

> +1 for this idea, it seems worth doing.
>
> Regarding Nick's comment, the precedent here probably isn't spark-packages
> (never ASF governed) but probably Apache Bahir (extensions to multiple
> distributed analytic platforms) which was the ASF's home for out-of-core
> Spark/Flink connectors, and eventually went to Attic in 2024. Two things
> sank it: scope sprawl across too many backends, and no real removal path
> which led to dead connectors piling up enlessly.
>
> In any case, if we keep it Python DS only (+1 with Allison's proposal here
> as well) and it should be sustainable. Also, AI does lower the cost of
> writing connectors, but not owning them (especially over time). Review,
> security, and testing against live backends only grow with contribution
> volume. It would probably be useful to point the tooling at CI and
> verification, not maintenance.
>
> All in all, great proposal and thank you Allison for brining this up!
>
> On 2026/08/18 23:45:47 Allison Wang wrote:
> > Hi all,
> >
> > I would like to discuss whether Apache Spark should provide an
> experimental,
> > community-maintained home for the ecosystem around the PySpark Data
> Source
> > API
> > <
> https://spark.apache.org/docs/latest/api/python/tutorial/sql/python_data_source.html
> >
> > :
> >
> >
> > Proposed repository: apache/spark-python-datasources
> >
> > Existing implementation: allisonwang-db/pyspark-data-sources
> > <https://github.com/allisonwang-db/pyspark-data-sources>
> >
> > The intent would not be to make these data sources part of Spark core.
> > Instead, the repository would provide an Apache-governed place where the
> > community can collaborate on reusable implementations of the public
> Python
> > Data Source API, share practical examples, and grow the ecosystem around
> > the API without expanding Spark core itself.
> >
> > The existing project can serve as the initial contribution. It contains
> > batch and streaming readers and writers built with the public PySpark
> Data
> > Source API, covering a range of external systems and use cases.
> >
> > I propose starting with a deliberately lightweight model:
> >
> >    -
> >
> >    The repository would be experimental and community-supported.
> >    -
> >
> >    It would focus specifically on implementations built on the public
> PySpark
> >    Data Source API.
> >    <
> https://spark.apache.org/docs/latest/api/python/tutorial/sql/python_data_source.html
> >
> >    -
> >
> >    Code in this repository would remain separate from Spark core and
> would
> >    not carry the same compatibility or support guarantees as Spark
> itself.
> >    -
> >
> >    New contributions would go through community review, with
> >    maintainability, dependencies, licensing, testing, and security taken
> into
> >    consideration.
> >    -
> >
> >    Implementations that become unmaintained or no longer meet the
> >    repository's requirements could be deprecated or removed through the
> normal
> >    community process.
> >    -
> >
> >    The repository would be governed by the Apache Spark community and
> >    follow ASF policies.
> >
> > The existing project is currently published on PyPI as
> pyspark-data-sources
> > using the pyspark_datasources import namespace. For continuity, I would
> > prefer to retain those names if they are compatible with ASF release and
> > branding requirements, but the package naming is not essential to this
> > proposal. I am willing to help maintain the repository, review
> > contributions, and support the release process.
> >
> > The main question I would like feedback on is whether the Spark community
> > thinks it is useful to provide this kind of lightweight, experimental
> home
> > for extensions built on a public Spark API, while keeping those
> > integrations explicitly outside Spark core.
> >
> > If the community supports this proposal, I will work with the Spark PMC
> on
> > the required JIRA and ASF IP-clearance steps, move the approved code to
> the
> > Apache repository, update the package metadata, and transfer PyPI
> > publishing to an ASF-controlled release process. Existing PyPI releases
> and
> > installation commands would remain unchanged.
> >
> > I would appreciate any feedback on this proposal.
> >
> > Thanks,
> >
> > Allison
> >
>
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