+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, Mar 10, 2026 at 12:07 PM Dongjoon Hyun <[email protected]> wrote: > +1 > > Thank you, Hyukjin. > > Dongjoon. > > On 2026/03/10 04:15:15 [email protected] wrote: > > Please vote on releasing the following candidate as Apache Spark version > 4.2.0-preview3. > > > > The vote is open until Thu, 12 Mar 2026 22:15:14 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 4.2.0-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 v4.2.0-preview3-rc1 (commit 9a4426f02e6): > > https://github.com/apache/spark/tree/v4.2.0-preview3-rc1 > > > > The release files, including signatures, digests, etc. can be found at: > > https://dist.apache.org/repos/dist/dev/spark/v4.2.0-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-1516/ > > > > The documentation corresponding to this release can be found at: > > https://dist.apache.org/repos/dist/dev/spark/v4.2.0-preview3-rc1-docs/ > > > > The list of bug fixes going into 4.2.0-preview3 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-preview3-rc1-bin/pyspark-4.2.0.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] > >
