+1 2025年9月19日(金) 1:03 huaxin gao <huaxin.ga...@gmail.com>:
> +1 > Thanks Peter for driving the release! > > Huaxin > > On Thu, Sep 18, 2025 at 8:54 AM kazuyuki tanimura > <ktanim...@apple.com.invalid> wrote: > >> +1 (non-binding) >> >> Kazu >> >> >> On Sep 18, 2025, at 8:43 AM, Dongjoon Hyun <dongj...@apache.org> wrote: >> >> +1 >> >> Thank you for leading Apache Spark 3.5.7 release, Peter. >> >> Dongjoon >> >> On 2025/09/18 04:41:46 Zhou Jiang wrote: >> >> + 1 >> >> >> On Sep 17, 2025, at 16:14, pt...@apache.org wrote: >> >> Please vote on releasing the following candidate as Apache Spark version >> 3.5.7. >> >> The vote is open until Sat, 20 Sep 2025 17:13:14 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 3.5.7 >> [ ] -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 v3.5.7-rc1 (commit ed00d046951): >> https://github.com/apache/spark/tree/v3.5.7-rc1 >> >> The release files, including signatures, digests, etc. can be found at: >> https://dist.apache.org/repos/dist/dev/spark/v3.5.7-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-1502/ >> >> The documentation corresponding to this release can be found at: >> https://dist.apache.org/repos/dist/dev/spark/v3.5.7-rc1-docs/ >> >> The list of bug fixes going into 3.5.7 can be found at the following URL: >> https://issues.apache.org/jira/projects/SPARK/versions/12355975 >> >> 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/v3.5.7-rc1-bin/pyspark-3.5.7.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 you don't end up building with an out of date RC going forward).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: dev-unsubscr...@spark.apache.org >> >> >> --------------------------------------------------------------------- >> To unsubscribe e-mail: dev-unsubscr...@spark.apache.org >> >> >> >> --------------------------------------------------------------------- >> To unsubscribe e-mail: dev-unsubscr...@spark.apache.org >> >> >>
