+1 (binding) I verified: - v4.1.4-rc4 resolves to 45b9b176e6e27f530a86ac5421b03865b7ea6287 - SHA-512 checksums and signatures for all published artifacts - source contents match the tagged commit - LICENSE, NOTICE, and 4.1.4 version metadata - source build with JDK 17 and Hive support - JVM SparkPi and PySpark local smoke tests
The Maven staging hostname was not resolvable from my environment, so I did not verify the staged Maven artifacts. SparkR was not tested. L. C. Hsieh <[email protected]> 于2026年10月26日周一 14:35写道： > +1 > > On Thu, Oct 22, 2026 at 8:12 AM Uroš Bojanić <[email protected]> wrote: > >> Please vote on releasing the following candidate as Apache Spark version >> 4.1.4. >> >> The vote is open until Sun, 25 Oct 2026 09:01:25 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 4.1.4 >> [ ] -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 v4.1.4-rc4 (commit 45b9b176e6e): >> https://github.com/apache/spark/tree/v4.1.4-rc4 >> >> The release files, including signatures, digests, etc. can be found at: >> https://dist.apache.org/repos/dist/dev/spark/v4.1.4-rc4-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-1541/ >> >> The documentation corresponding to this release can be found at: >> https://dist.apache.org/repos/dist/dev/spark/v4.1.4-rc4-docs/ >> >> The list of bug fixes going into 4.1.4 can be found at the following URL: >> https://issues.apache.org/jira/projects/SPARK/versions/12357252 >> >> 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/v4.1.4-rc4-bin/pyspark-4.1.4.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] >> >>
