+1 (non-binding) Deployed to a Hadoop cluster (JDK 25, Hadoop 3.5.0) and run some queries, no issues found.
Thanks, Cheng Pan On Wed, Oct 28, 2026 at 12:26 AM Gengliang Wang <[email protected]> wrote: > > +1 > > On Tue, Oct 27, 2026 at 2:19 AM Uroš Bojanić <[email protected]> wrote: >> >> +1 (non-binding) >> >> Verified Apache Spark 4.3.0 RC3 (tag v4.3.0-rc3, commit 98bc0212c94): >> >> - Good GPG signatures and SHA512 sums on all artifacts (source, three >> binaries, the PySpark/SparkR tarballs) against KEYS. >> - Source tarball matches the tag (no jars/classes), and RELEASE in all three >> binaries records the same commit. >> - Built the source tarball with -Phive -Phive-thriftserver on JDK 17, got a >> clean BUILD SUCCESS across all 41 modules. >> - Re-ran the test suites for the Blocker fixes since RC2 (SPARK-60508, >> SPARK-60497, SPARK-60376, etc.); all 840 tests pass. >> - Ran quick smoke tests on JDK 17, 21 and 25: Java, Scala, SQL, PySpark and >> Spark Connect (Scala client); all look good. >> - Checked that the RC2 API audit findings are fixed (ShuffleLocationResponse >> visibility, missing docs, @since metadata). >> - Sanity-checked the binary dist (RELEASE, LICENSE/NOTICE/licenses all >> present) and ran dev/check-license; RAT passes. >> - Checked the docs: site and API docs are up for 4.3.0, and the migration >> guides have 4.2 to 4.3 sections. >> >> Thank you Jungtaek! >> >> On 2026-10-27 03:35 UTC [email protected] wrote: >> > Please vote on releasing the following candidate as Apache Spark version >> > 4.3.0. >> > >> > The vote is open until Thu, 29 Oct 2026 21:35:11 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-rc3 (commit 98bc0212c94): >> > https://github.com/apache/spark/tree/v4.3.0-rc3 >> > >> > The release files, including signatures, digests, etc. can be found at: >> > https://dist.apache.org/repos/dist/dev/spark/v4.3.0-rc3-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-1542/ >> > >> > The documentation corresponding to this release can be found at: >> > https://dist.apache.org/repos/dist/dev/spark/v4.3.0-rc3-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-rc3-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] >> > >> > >> >> --------------------------------------------------------------------- >> To unsubscribe e-mail: [email protected] >> --------------------------------------------------------------------- To unsubscribe e-mail: [email protected]
