+1 except for one issue. Verified checksums (sha512) and the GPG signature (Good signature, Holden's EdDSA key), confirmed the source tarball matches the git tag 77bbf77, built the binary dist and ran SparkPi + PySpark smoke tests on JDK 17 / Python 3.11 — all pass.
The signing key D05C…04AC is in dist/dev/spark/KEYS but not yet in downloads.apache.org/spark/KEYS linked from this email — could you propagate it so voters following the email can verify? Thank you! Xiao <[email protected]> 于2026年7月11日周六 21:33写道： > Please vote on releasing the following candidate as Apache Spark version > 4.1.3. > > The vote is open until Tue, 14 Jul 2026 22:33:21 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 4.1.3 > [ ] -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 v4.1.3-rc1 (commit 77bbf77e86a): > https://github.com/apache/spark/tree/v4.1.3-rc1 > > The release files, including signatures, digests, etc. can be found at: > https://dist.apache.org/repos/dist/dev/spark/v4.1.3-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-1527/ > > The documentation corresponding to this release can be found at: > https://dist.apache.org/repos/dist/dev/spark/v4.1.3-rc1-docs/ > > The list of bug fixes going into 4.1.3 can be found at the following URL: > https://issues.apache.org/jira/projects/SPARK/versions/12357063 > > 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/v4.1.3-rc1-bin/pyspark-4.1.3.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 you don't end up building with an out of date RC going forward).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] > >
