Now that all known blockers have once again been resolved, please vote on
releasing the following candidate as Apache Spark version 2.3.0. The vote
is open until Friday February 16, 2018 at 8:00:00 am UTC and passes if a
majority of at least 3 PMC +1 votes are cast.

[ ] +1 Release this package as Apache Spark 2.3.0

[ ] -1 Do not release this package because ...

To learn more about Apache Spark, please see

The tag to be voted on is v2.3.0-rc3:

List of JIRA tickets resolved in this release can be found here:

The release files, including signatures, digests, etc. can be found at:

Release artifacts are signed with the following key:

The staging repository for this release can be found at:

The documentation corresponding to this release can be found at:


What are the unresolved issues targeted for 2.3.0?

Please see At the time of writing, there are
currently no known release blockers.

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building with a out of date RC going forward).

What should happen to JIRA tickets still targeting 2.3.0?

Committers should look at those and triage. Extremely important bug fixes,
documentation, and API tweaks that impact compatibility should be worked on
immediately. Everything else please retarget to 2.3.1 or 2.4.0 as

Why is my bug not fixed?

In order to make timely releases, we will typically not hold the release
unless the bug in question is a regression from 2.2.0. That being said, if
there is something which is a regression from 2.2.0 and has not been
correctly targeted please ping me or a committer to help target the issue
(you can see the open issues listed as impacting Spark 2.3.0 at


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