+1 (non-binding) Verified: - Tag v4.2.1-rc1 points to 72c18760854; version strings are 4.2.1 - GPG signatures and SHA-512 checksums of all 8 artifacts - Source tarball matches the git tag; no binary files; RAT passes - Binary LICENSE/NOTICE match LICENSE-binary/NOTICE-binary - Built from the source tarball with SBT (-Phive -Phive-thriftserver -Pyarn -Pkubernetes) - Smoke tested spark-4.2.1-bin-hadoop3 on JDK 21: SparkPi, spark-sql with Parquet/Hive ORC tables, PySpark (pip-installed sdist) with RDDs and UDFs - Spark Connect: pyspark_client 4.2.1 against a Connect server from the binary distribution (aggregations, toPandas, Python and pandas UDFs, CTAS) - Iceberg integration tests passed[1] (including two cases that are fixed in 4.2.1-rc1)
1. https://github.com/apache/iceberg/pull/18294 Thanks, Manu On Mon, Sep 28, 2026 at 5:14 PM <[email protected]> wrote: > Please vote on releasing the following candidate as Apache Spark version > 4.2.1. > > The vote is open until Thu, 01 Oct 2026 03:11:20 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 4.2.1 > [ ] -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 v4.2.1-rc1 (commit 72c18760854): > https://github.com/apache/spark/tree/v4.2.1-rc1 > > The release files, including signatures, digests, etc. can be found at: > https://dist.apache.org/repos/dist/dev/spark/v4.2.1-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-1531/ > > The documentation corresponding to this release can be found at: > https://dist.apache.org/repos/dist/dev/spark/v4.2.1-rc1-docs/ > > The list of bug fixes going into 4.2.1 can be found at the following URL: > https://issues.apache.org/jira/projects/SPARK/versions/12357191 > > 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/v4.2.1-rc1-bin/pyspark-4.2.1.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] > >
