Spark 3.0 will still use the Hadoop 2.7 profile by default, I think. Hadoop 2.7 profile is much more stable than Hadoop 3.2 profile.
On Thu, Oct 31, 2019 at 3:54 PM Sean Owen <sro...@gmail.com> wrote: > This isn't a big thing, but I see that the pyspark build includes > Hadoop 2.7 rather than 3.2. Maybe later we change the build to put in > 3.2 by default. > > Otherwise, the tests all seems to pass with JDK 8 / 11 with all > profiles enabled, so I'm +1 on it. > > > On Thu, Oct 31, 2019 at 1:00 AM Xingbo Jiang <jiangxb1...@gmail.com> > wrote: > > > > Please vote on releasing the following candidate as Apache Spark version > 3.0.0-preview. > > > > The vote is open until November 3 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 3.0.0-preview > > [ ] -1 Do not release this package because ... > > > > To learn more about Apache Spark, please see http://spark.apache.org/ > > > > The tag to be voted on is v3.0.0-preview-rc2 (commit > 007c873ae34f58651481ccba30e8e2ba38a692c4): > > https://github.com/apache/spark/tree/v3.0.0-preview-rc2 > > > > The release files, including signatures, digests, etc. can be found at: > > https://dist.apache.org/repos/dist/dev/spark/v3.0.0-preview-rc2-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-1336/ > > > > The documentation corresponding to this release can be found at: > > https://dist.apache.org/repos/dist/dev/spark/v3.0.0-preview-rc2-docs/ > > > > The list of bug fixes going into 3.0.0 can be found at the following URL: > > https://issues.apache.org/jira/projects/SPARK/versions/12339177 > > > > 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 you don't end up building with an out of date RC going forward). > > > > =========================================== > > What should happen to JIRA tickets still targeting 3.0.0? > > =========================================== > > > > The current list of open tickets targeted at 3.0.0 can be found at: > > https://issues.apache.org/jira/projects/SPARK and search for "Target > Version/s" = 3.0.0 > > > > Committers should look at those and triage. Extremely important bug > > fixes, documentation, and API tweaks that impact compatibility should > > be worked on immediately. > > > > ================== > > But my bug isn't fixed? > > ================== > > > > In order to make timely releases, we will typically not hold the > > release unless the bug in question is a regression from the previous > > release. That being said, if there is something which is a regression > > that has not been correctly targeted please ping me or a committer to > > help target the issue. > > --------------------------------------------------------------------- > To unsubscribe e-mail: dev-unsubscr...@spark.apache.org > > -- [image: Databricks Summit - Watch the talks] <https://databricks.com/sparkaisummit/north-america>