+ (non-binding) — Sent from my iPhone Pardon the dumb thumb typos :) > On Sep 26, 2025, at 2:22 AM, Cheng Pan <[email protected]> wrote: > > +1 (non-binding) > > I tested it with Hadoop 3.4.2, in both SIMPLE and KERBEROS mode - > SparkPi, Connect Server, and History Server work as expected. > > Thanks, > Cheng Pan > >> On Fri, Sep 26, 2025 at 4:56 PM Max Gekk <[email protected]> wrote: >> >> +1 >> >>> On Wed, Sep 24, 2025 at 3:49 PM Wenchen Fan <[email protected]> wrote: >>> >>> +1 >>> >>> On Wed, Sep 24, 2025 at 7:29 PM <[email protected]> wrote: >>>> >>>> Please vote on releasing the following candidate as Apache Spark version >>>> 4.1.0-preview2. >>>> >>>> The vote is open until Sat, 27 Sep 2025 05:26:22 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 4.1.0-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 v4.1.0-preview2-rc1 (commit c5ff48cc2b2): >>>> https://github.com/apache/spark/tree/v4.1.0-preview2-rc1 >>>> >>>> The release files, including signatures, digests, etc. can be found at: >>>> https://dist.apache.org/repos/dist/dev/spark/v4.1.0-preview2-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-1503/ >>>> >>>> The documentation corresponding to this release can be found at: >>>> https://dist.apache.org/repos/dist/dev/spark/v4.1.0-preview2-rc1-docs/ >>>> >>>> The list of bug fixes going into 4.1.0-preview2 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-preview2-rc1-bin/pyspark-4.1.0.dev2.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] >
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