+1 2026年1月7日(水) 10:33 Holden Karau <[email protected]>:
> +1 > > Twitter: https://twitter.com/holdenkarau > Fight Health Insurance: https://www.fighthealthinsurance.com/ > <https://www.fighthealthinsurance.com/?q=hk_email> > Books (Learning Spark, High Performance Spark, etc.): > https://amzn.to/2MaRAG9 <https://amzn.to/2MaRAG9> > YouTube Live Streams: https://www.youtube.com/user/holdenkarau > Pronouns: she/her > > > On Tue, Jan 6, 2026 at 4:58 PM Hyukjin Kwon <[email protected]> wrote: > >> Starting with my own +1 >> >> On Wed, 7 Jan 2026 at 09:42, <[email protected]> wrote: >> >>> Please vote on releasing the following candidate as Apache Spark version >>> 4.2.0-preview1. >>> >>> The vote is open until Fri, 09 Jan 2026 17:41:00 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 4.2.0-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 v4.2.0-preview1-rc1 (commit 33b4056eee8): >>> https://github.com/apache/spark/tree/v4.2.0-preview1-rc1 >>> >>> The release files, including signatures, digests, etc. can be found at: >>> https://dist.apache.org/repos/dist/dev/spark/v4.2.0-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-1512/ >>> >>> The documentation corresponding to this release can be found at: >>> https://dist.apache.org/repos/dist/dev/spark/v4.2.0-preview1-rc1-docs/ >>> >>> The list of bug fixes going into 4.2.0-preview1 can be found at the >>> following URL: >>> https://issues.apache.org/jira/projects/SPARK/versions/12356380 >>> >>> 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/v4.2.0-preview1-rc1-bin/pyspark-4.2.0.dev1.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] >>> >>>
