+1 On Mon, Oct 27, 2025 at 10:49 AM Yang Jie <[email protected]> wrote:
> +1，thank you Hyukjin > > On 2025/10/27 02:37:01 Dongjoon Hyun wrote: > > +1 > > > > Thank you so much, Hyukjin. > > > > Dongjoon. > > > > On 2025/10/27 02:09:27 Hyukjin Kwon wrote: > > > Starting with my own +1 > > > > > > On Mon, 27 Oct 2025 at 11:07, <[email protected]> wrote: > > > > > > > Please vote on releasing the following candidate as Apache Spark > version > > > > 4.1.0-preview3. > > > > > > > > The vote is open until Wed, 29 Oct 2025 20:07:25 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-preview3 > > > > [ ] -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-preview3-rc1 (commit cdeb3b4f237): > > > > https://github.com/apache/spark/tree/v4.1.0-preview3-rc1 > > > > > > > > The release files, including signatures, digests, etc. can be found > at: > > > > > https://dist.apache.org/repos/dist/dev/spark/v4.1.0-preview3-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-1504/ > > > > > > > > The documentation corresponding to this release can be found at: > > > > > https://dist.apache.org/repos/dist/dev/spark/v4.1.0-preview3-rc1-docs/ > > > > > > > > The list of bug fixes going into 4.1.0-preview3 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-preview3-rc1-bin/pyspark-4.1.0.dev3.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). > > > > > > > > --------------------------------------------------------------------- > > > > To unsubscribe e-mail: [email protected] > > > > > > > > > > > > > > > --------------------------------------------------------------------- > > To unsubscribe e-mail: [email protected] > > > > > > --------------------------------------------------------------------- > To unsubscribe e-mail: [email protected] > >
