+1 2025年7月9日(水) 2:12 Rozov, Vlad <vro...@amazon.com.invalid>:
> +1 (non-binding) > > > > Thank you, > > > > Vlad > > > > *From: *Dongjoon Hyun <dongjoon.h...@gmail.com> > *Date: *Tuesday, July 8, 2025 at 8:09 AM > *To: *Hyukjin Kwon <gurwls...@apache.org> > *Cc: *"dev@spark.apache.org" <dev@spark.apache.org> > *Subject: *RE: [EXTERNAL] [VOTE] Release Spark 4.1.0-preview1 (RC1) > > > > +1 > > > > Dongjoon > > > > On Tue, Jul 8, 2025 at 05:41 Hyukjin Kwon <gurwls...@apache.org> wrote: > > Alright. +1 from myself :-). > > > > On Tue, Jul 8, 2025 at 9:39 PM <gurwls...@apache.org> wrote: > > Please vote on releasing the following candidate as Apache Spark version > 4.1.0-preview1. > > The vote is open until Sat, 12 Jul 2025 05:38:35 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-preview1 > [ ] -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-preview1-rc1 (commit f3ac67ee9b3): > https://github.com/apache/spark/tree/v4.1.0-preview1-rc1 > > The release files, including signatures, digests, etc. can be found at: > https://dist.apache.org/repos/dist/dev/spark/v4.1.0-preview1-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-1500/ > > The documentation corresponding to this release can be found at: > https://dist.apache.org/repos/dist/dev/spark/v4.1.0-preview1-rc1-docs/ > > The list of bug fixes going into 4.1.0-preview1 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-preview1-rc1-bin/pyspark-4.1.0-preview1.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: dev-unsubscr...@spark.apache.org > >
