Hi all, I'm cancelling RC5.
A performance regression was found for Python UDFs on nested data in 4.2. This needs to be investigated and fixed before we release, so I'll roll RC6 once a fix is in. Thanks to everyone who tested RC5. Huaxin On Tue, Jul 7, 2026 at 12:23 AM John Zhuge <[email protected]> wrote: > +1 (non-binding) Thanks Huaxin! > > On Mon, Jul 6, 2026 at 11:49 PM Uroš Bojanić <[email protected]> wrote: > >> +1 (non-binding) >> >> On 2026/07/02 06:24:36 [email protected] wrote: >> > Please vote on releasing the following candidate as Apache Spark >> version 4.2.0. >> > >> > The vote is open until Sun, 05 Jul 2026 00:24:35 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 4.2.0 >> > [ ] -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 v4.2.0-rc5 (commit 15d153e6a3d): >> > https://github.com/apache/spark/tree/v4.2.0-rc5 >> > >> > The release files, including signatures, digests, etc. can be found at: >> > https://dist.apache.org/repos/dist/dev/spark/v4.2.0-rc5-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-1525/ >> > >> > The documentation corresponding to this release can be found at: >> > https://dist.apache.org/repos/dist/dev/spark/v4.2.0-rc5-docs/ >> > >> > The list of bug fixes going into 4.2.0 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-rc5-bin/pyspark-4.2.0.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] >> >> > > -- > John Zhuge >
