+1 (non-binding) - validated basic test suite for Spark Kubernetes Operator.
> On Nov 17, 2025, at 16:28, Cheng Pan <[email protected]> wrote: > > +1 (non-binding) > > Verified basic functionalities of Connect JDBC Driver via BeeLine with > Connect Server, by running some TPC-H queries. > > Thanks, > Cheng Pan > > > >> On Nov 17, 2025, at 05:02, [email protected] wrote: >> >> Please vote on releasing the following candidate as Apache Spark version >> 4.1.0-preview4. >> >> The vote is open until Wed, 19 Nov 2025 14:02:40 PST and passes if a >> majority +1 PMC votes are cast, with >> a minimum of 3 +1 votes. >> >> [ ] +1 Release this package as Apache Spark 4.1.0-preview4 >> [ ] -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 v4.1.0-preview4-rc1 (commit c125aea395b): >> https://github.com/apache/spark/tree/v4.1.0-preview4-rc1 >> >> The release files, including signatures, digests, etc. can be found at: >> https://dist.apache.org/repos/dist/dev/spark/v4.1.0-preview4-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-1505/ >> >> The documentation corresponding to this release can be found at: >> https://dist.apache.org/repos/dist/dev/spark/v4.1.0-preview4-rc1-docs/ >> >> The list of bug fixes going into 4.1.0-preview4 can be found at the >> following URL: >> https://issues.apache.org/jira/projects/SPARK/versions/12355581 >> >> 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/v4.1.0-preview4-rc1-bin/pyspark-4.1.0.dev4.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 you don't end up building with an out of date RC going forward).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]
