Sure
I’d love to give it a go. How?
Sent from my iPhone

> On Sep 30, 2026, at 3:27 PM, Uroš Bojanić <[email protected]> wrote:
> 
> Thank you Liang-Chi for catching and reporting the SPARK-59407 regression!
> 
> The fix (#59074) has now landed on branch-4.1, so I'm cancelling Spark 4.1.4 
> RC1 and will cut RC2 shortly.
> 
> Best,
> Uroš
> 
>> On 2026-09-29 00:50 UTC Uroš Bojanić wrote:
>> Please vote on releasing the following candidate as Apache Spark version 
>> 4.1.4.
>> 
>> The vote is open until Thu, 01 Oct 2026 18:44:12 PDT and passes if a 
>> majority +1 PMC votes are cast, with
>> a minimum of 3 +1 votes.
>> 
>> [ ] +1 Release this package as Apache Spark 4.1.4
>> [ ] -1 Do not release this package because ...
>> 
>> To learn more about Apache Spark, please see https://spark.apache.org/
>> 
>> The tag to be voted on is v4.1.4-rc1 (commit ce5c307f607):
>> https://github.com/apache/spark/tree/v4.1.4-rc1
>> 
>> The release files, including signatures, digests, etc. can be found at:
>> https://dist.apache.org/repos/dist/dev/spark/v4.1.4-rc1-bin/
>> 
>> Signatures used for Spark RCs can be found in this file:
>> https://downloads.apache.org/spark/KEYS
>> 
>> The staging repository for this release can be found at:
>> https://repository.apache.org/content/repositories/orgapachespark-1532/
>> 
>> The documentation corresponding to this release can be found at:
>> https://dist.apache.org/repos/dist/dev/spark/v4.1.4-rc1-docs/
>> 
>> The list of bug fixes going into 4.1.4 can be found at the following URL:
>> https://issues.apache.org/jira/projects/SPARK/versions/12357252
>> 
>> FAQ
>> 
>> =========================
>> How can I help test this release?
>> =========================
>> 
>> If you are a Spark user, you can help us test this release by taking
>> an existing Spark workload and running on this release candidate, then
>> reporting any regressions.
>> 
>> If you're working in PySpark you can set up a virtual env and install
>> the current RC via "pip install 
>> https://dist.apache.org/repos/dist/dev/spark/v4.1.4-rc1-bin/pyspark-4.1.4.tar.gz";
>> and see if anything important breaks.
>> In the Java/Scala, you can add the staging repository to your project's 
>> resolvers and test
>> with the RC (make sure to clean up the artifact cache before/after so
>> you don't end up building with an out of date RC going forward).
>> 
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>> 
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