+1 On Wed, May 14, 2025 at 7:01 AM Gengliang Wang <ltn...@gmail.com> wrote:
> +1 > > On Tue, May 13, 2025 at 3:57 PM Hyukjin Kwon <gurwls...@apache.org> wrote: > >> +1 >> >> On Wed, 14 May 2025 at 07:29, Wenchen Fan <cloud0...@gmail.com> wrote: >> >>> Same as before, I'll start with my own +1. >>> >>> On Wed, May 14, 2025 at 12:28 AM Wenchen Fan <cloud0...@gmail.com> >>> wrote: >>> >>>> Please vote on releasing the following candidate as Apache Spark >>>> version 4.0.0. >>>> >>>> The vote is open until May 16 (PST) and passes if a majority +1 PMC >>>> votes are cast, with a minimum of 3 +1 votes. >>>> >>>> [ ] +1 Release this package as Apache Spark 4.0.0 >>>> [ ] -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 v4.0.0-rc6 (commit >>>> 9a99ecb03a2d35f5f38decd686b55511a5c7c535) >>>> https://github.com/apache/spark/tree/v4.0.0-rc6 >>>> >>>> The release files, including signatures, digests, etc. can be found at: >>>> https://dist.apache.org/repos/dist/dev/spark/v4.0.0-rc6-bin/ >>>> >>>> Signatures used for Spark RCs can be found in this file: >>>> https://dist.apache.org/repos/dist/dev/spark/KEYS >>>> >>>> The staging repository for this release can be found at: >>>> https://repository.apache.org/content/repositories/orgapachespark-1484/ >>>> >>>> The documentation corresponding to this release can be found at: >>>> https://dist.apache.org/repos/dist/dev/spark/v4.0.0-rc6-docs/ >>>> >>>> The list of bug fixes going into 4.0.0 can be found at the following >>>> URL: >>>> https://issues.apache.org/jira/projects/SPARK/versions/12353359 >>>> >>>> This release is using the release script of the tag v4.0.0-rc6. >>>> >>>> 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 and see if anything important breaks, in the Java/Scala >>>> you can add the staging repository to your projects resolvers and test >>>> with the RC (make sure to clean up the artifact cache before/after so >>>> you don't end up building with a out of date RC going forward). >>>> >>>
