-1 (non-binding) Found a PySpark packaging issue, and made a fix. https://github.com/apache/spark/pull/58428
Thanks, Cheng Pan > On Aug 31, 2026, at 21:37, Jungtaek Lim <[email protected]> wrote: > > Folks, please do not hesitate to test this RC; we generally did not make RC1 > pass, but we should use the RC1 to descope the defects and critical fixes, to > verify less things in the next RC, and iterate till we eventually have > consensus of OK sign on specific RC. > > On Mon, Aug 31, 2026 at 6:51 PM <[email protected] > <mailto:[email protected]>> wrote: >> Please vote on releasing the following candidate as Apache Spark version >> 4.3.0. >> >> The vote is open until Thu, 03 Sep 2026 03:51:35 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 4.3.0 >> [ ] -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 v4.3.0-rc1 (commit 3db813416c8): >> https://github.com/apache/spark/tree/v4.3.0-rc1 >> >> The release files, including signatures, digests, etc. can be found at: >> https://dist.apache.org/repos/dist/dev/spark/v4.3.0-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-1530/ >> >> The documentation corresponding to this release can be found at: >> https://dist.apache.org/repos/dist/dev/spark/v4.3.0-rc1-docs/ >> >> The list of bug fixes going into 4.3.0 can be found at the following URL: >> https://issues.apache.org/jira/projects/SPARK/versions/12356944 >> >> 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/v4.3.0-rc1-bin/pyspark-4.3.0.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 you don't end up building with an out of date RC going forward).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] >> <mailto:[email protected]> >>
