I don’t think is a good idea *yet*

My core hesitation stems from the fact that it is taking on a bunch of
connectors that the existing committers don’t necessarily have context
around. Historically connectors maintained by the data sources or sink
communities / companies themselves have done better than those inside of an
amalgamation or inside the project.

I’m not convinced that AI meaningfully changes the problems we’ve seen with
in tree attempts.

There’s not a very clear “this is our release plan” yet or what the quality
bar would be just that it’s “different.”

Also looking at the connector package it offers datasources which have
their own existing out of tree Spark version. How would those developer
feel / how is our version better / will this cause user confusion?

Additionally I’m a little cautious about the “based on” given the direct
databricks reference for comparability in the readme we’d definitely need
to clean that up.

For those reasons I’m -1 on this iteration of the proposal.


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On Thu, Aug 27, 2026 at 5:42 PM Hyukjin Kwon <[email protected]> wrote:

> +1
>
> On Fri, 28 Aug 2026 at 03:27, Uroš Bojanić <[email protected]> wrote:
>
>> +1 (non-binding)
>>
>> On 2026/08/27 03:36:05 Allison Wang wrote:
>> > Hi all,
>> >
>> > I'd like to open the vote on the proposal to introduce a new Apache
>> Spark
>> > repository for community-contributed Python data sources:
>> > *apache/spark-python-data-sources* based on the existing project
>> > https://github.com/allisonwang-db/pyspark-data-sources
>> >
>> > DISCUSS thread:
>> > https://lists.apache.org/thread/0yqzbr8pzfnfomqq1zdgzcqltnrc6s1o
>> >
>> > The vote is open for at least the next 72 hours.
>> >
>> > [ ] +1: Accept the proposal
>> > [ ] +0
>> > [ ] -1: I don't think this is a good idea because...
>> >
>> > Thanks,
>> > Allison
>> >
>>
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