Found an issue[1] related to LOG4J, but it may not be serious enough to 
interrupt this preview release.

[1] https://github.com/apache/spark/pull/52475

Thanks,
Cheng Pan



> On Sep 26, 2025, at 16:54, Max Gekk <[email protected]> wrote:
> 
> +1
> 
> On Wed, Sep 24, 2025 at 3:49 PM Wenchen Fan <[email protected] 
> <mailto:[email protected]>> wrote:
>> +1
>> 
>> On Wed, Sep 24, 2025 at 7:29 PM <[email protected] 
>> <mailto:[email protected]>> wrote:
>>> Please vote on releasing the following candidate as Apache Spark version 
>>> 4.1.0-preview2.
>>> 
>>> The vote is open until Sat, 27 Sep 2025 05:26:22 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 4.1.0-preview2
>>> [ ] -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 v4.1.0-preview2-rc1 (commit c5ff48cc2b2):
>>> https://github.com/apache/spark/tree/v4.1.0-preview2-rc1
>>> 
>>> The release files, including signatures, digests, etc. can be found at:
>>> https://dist.apache.org/repos/dist/dev/spark/v4.1.0-preview2-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-1503/
>>> 
>>> The documentation corresponding to this release can be found at:
>>> https://dist.apache.org/repos/dist/dev/spark/v4.1.0-preview2-rc1-docs/
>>> 
>>> The list of bug fixes going into 4.1.0-preview2 can be found at the 
>>> following URL:
>>> https://issues.apache.org/jira/projects/SPARK/versions/12355581
>>> 
>>> 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/v4.1.0-preview2-rc1-bin/pyspark-4.1.0.dev2.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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>>> <mailto:[email protected]>
>>> 

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