Re: Szehon's question: Currently there is no plan to include Java/Scala
connectors. There are already established DSv2 integrations maintained by
other communities, such as the MongoDB Spark Connector
<https://github.com/mongodb/mongo-spark>.

I would prefer to keep Java/Scala separate from Python since their
ecosystems and tooling are very different. We could consider a separate
repository for them later.

On Wed, Aug 19, 2026 at 12:10 PM Allison Wang <[email protected]>
wrote:

> Hi Nicholas, the main lesson for me is that sustainability must be a core
> part of the design. Community-contributed integrations require ongoing
> ownership, reviews, updates, testing, and releases. One difference is
> that Spark Packages is a broad index of independently maintained
> projects. The scope can quickly become too large to maintain, and it is
> hard to know the quality or maintenance status of each package. This
> proposal has a much narrower focus PySpark data sources and place the
> implementations in one Apache github repository similar to
> spark-connect-go <https://github.com/apache/spark-connect-go>.
>
> I also think today’s automation and AI-assisted development tools create
> an opportunity to reduce the maintenance load. We could design the
> repository to be AI-friendly from the beginning. These tools would not
> replace maintainers or human review, but they could make contributions and
> routine updates much easier.
>
> Love to hear others' thoughts on this.
>
> On Tue, Aug 18, 2026 at 8:02 PM Nicholas Chammas <
> [email protected]> wrote:
>
>> Just to be clear, I mean "broadly similar” as in they are both
>> community-maintained libraries for Spark. Allison’s proposal is, of course,
>> much more focused! I would just like to raise the point of comparison since
>> I think it’s relevant.
>>
>>
>> On Aug 18, 2026, at 10:51 PM, Nicholas Chammas <
>> [email protected]> wrote:
>>
>> We had something broadly similar from ~10 years ago, but not limited to
>> data sources: https://spark-packages.org/
>>
>> My impression of Spark Packages is that it is inactive and unmaintained.
>> If so, it might be useful to have a brief post mortem as a community to
>> understand why it didn’t stand the test of time, and how to avoid that fate
>> for this new proposal.
>>
>>
>> On Aug 18, 2026, at 7:45 PM, Allison Wang <[email protected]> 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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