The PR builder uses Hadoop 2.7 profile, which makes me think that 2.7 is more stable and we should make releases using 2.7 by default.
+1 On Fri, Nov 1, 2019 at 7:16 AM Xiao Li <lix...@databricks.com> wrote: > 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> >
