+1 - Verified sha512 + GPG signatures on all artifacts (good sig, Huaxin's key 7092…38D1, present in the linked KEYS) - Confirmed tag v4.2.0-rc6 = commit 32f72996011; binary distros embed the same revision - Built spark-core (+ module deps) from the source tarball with ./build/mvn on JDK 17 — success - Ran SparkPi + a spark-shell Scala job (range agg + Spark SQL) — correct - pip-installed pyspark-4.2.0.tar.gz and ran DataFrame + Spark SQL + a Python UDF — correct - No open Blocker/Critical JIRAs for 4.2.0
Xiao Holden Karau <[email protected]> 于2026年7月11日周六 23:44写道： > +1 smoke test of pyspark and key signature of pyspark checked out, thanks > for getting this out :) > > On Sat, Jul 11, 2026 at 11:59 AM <[email protected]> wrote: > >> Please vote on releasing the following candidate as Apache Spark version >> 4.2.0. >> >> The vote is open until Tue, 14 Jul 2026 12:58:53 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-rc6 (commit 32f72996011): >> https://github.com/apache/spark/tree/v4.2.0-rc6 >> >> The release files, including signatures, digests, etc. can be found at: >> https://dist.apache.org/repos/dist/dev/spark/v4.2.0-rc6-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-1526/ >> >> The documentation corresponding to this release can be found at: >> https://dist.apache.org/repos/dist/dev/spark/v4.2.0-rc6-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-rc6-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] >> >> > > -- > Twitter: https://twitter.com/holdenkarau > Fight Health Insurance: https://www.fighthealthinsurance.com/ > <https://www.fighthealthinsurance.com/?q=hk_email> > Books (Learning Spark, High Performance Spark, etc.): > https://amzn.to/2MaRAG9 <https://amzn.to/2MaRAG9> > YouTube Live Streams: https://www.youtube.com/user/holdenkarau > Pronouns: she/her >
