+1 On Mon, May 19, 2025 at 5:21 PM Jungtaek Lim <kabhwan.opensou...@gmail.com> wrote:
> +1 (non-binding) > > On Tue, May 20, 2025 at 8:47 AM Ruifeng Zheng <ruife...@apache.org> wrote: > >> +1 >> >> On Tue, May 20, 2025 at 7:04 AM Hyukjin Kwon <gurwls...@apache.org> >> wrote: >> >>> +1 >>> >>> On Mon, 19 May 2025 at 21:27, Wenchen Fan <cloud0...@gmail.com> wrote: >>> >>>> Same as before, I'll start with my own +1. >>>> >>>> On Mon, May 19, 2025 at 8:25 PM 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 22 (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-rc7 (commit >>>>> fa33ea000a0bda9e5a3fa1af98e8e85b8cc5e4d4) >>>>> https://github.com/apache/spark/tree/v4.0.0-rc7 >>>>> >>>>> The release files, including signatures, digests, etc. can be found at: >>>>> https://dist.apache.org/repos/dist/dev/spark/v4.0.0-rc7-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-1485/ >>>>> >>>>> The documentation corresponding to this release can be found at: >>>>> https://dist.apache.org/repos/dist/dev/spark/v4.0.0-rc7-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-rc7. >>>>> >>>>> 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). >>>>> >>>>
