+1 Twitter: https://twitter.com/holdenkarau 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
On Mon, Sep 16, 2024 at 10:55 AM Zhou Jiang <zhou.c.ji...@gmail.com> wrote: > + 1 > Sent from my iPhone > > On Sep 16, 2024, at 01:04, Dongjoon Hyun <dongjoon.h...@gmail.com> wrote: > > > > Please vote on releasing the following candidate as Apache Spark version > 4.0.0-preview2. > > The vote is open until September 20th 1AM (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 4.0.0-preview2 > [ ] -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 v4.0.0-preview2-rc1 (commit > f0d465e09b8d89d5e56ec21f4bd7e3ecbeeb318a) > https://github.com/apache/spark/tree/v4.0.0-preview2-rc1 > > The release files, including signatures, digests, etc. can be found at: > https://dist.apache.org/repos/dist/dev/spark/v4.0.0-preview2-rc1-bin/ > > Signatures used for Spark RCs can be found in this file: > https://dist.apache.org/repos/dist/dev/spark/KEYS > > The staging repository for this release can be found at: > https://repository.apache.org/content/repositories/orgapachespark-1468/ > > The documentation corresponding to this release can be found at: > https://dist.apache.org/repos/dist/dev/spark/v4.0.0-preview2-rc1-docs/ > > The list of bug fixes going into 4.0.0-preview2 can be found at the > following URL: > https://issues.apache.org/jira/projects/SPARK/versions/12353359 > > This release is using the release script of the tag v4.0.0-preview2-rc1. > > 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 and see if anything important breaks, in the Java/Scala > you can add the staging repository to your projects resolvers and test > with the RC (make sure to clean up the artifact cache before/after so > you don't end up building with a out of date RC going forward). > >
