+1.

Thank you all.

I tested the following additionally with OpenJDK 11.0.8.

    - PySpark UT on Python 3.7.7 with Pandas 0.23.2 / PyArrow 0.15.1.
    - JDBC integration suite
    - K8s integration suite (except SparkR test)
      (Minikube: K8s Client v1.18.8, K8s Server v1.17.11)

For SparkR, it would be great if someone can check the current status
because SparkR was removed from CRAN.

    - I used `R 3.5.2 (2018-12-20)` like 3.0.0 vote, but
`dev/make-distribution.sh`
      failed for me when I used the `--r` option. However, since the
release artifact has SparkR,
      I believe it's a problem on my env.

    - Jenkins is using `R 3.6.3 (2020-02-29)` and it seems to succeed,
      but K8s IT seems to fail consistently due to some unknown reasons.
      (https://github.com/apache/spark/pull/29533)
      "Run SparkR on simple dataframe.R example *** FAILED ***"

    - For Apache Spark 3.1, we are testing R 4.0 on `master` branch,
      but we don't have test coverage on `branch-3.0`.
      So, I'm wondering if Spark 3.0.1 supports R 4.0 without any issue.

In addition to the one which Xiao mentioned, we also had a late arrival on
the correctness area,
but it wasn't a registered blocker before the 3.0.1 RC3 vote. Given that,
it can be a part of 3.0.2.

    - [SPARK-31511][SQL] Make BytesToBytesMap iterators thread-safe
      https://github.com/apache/spark/pull/28286#issuecomment-682019408

Bests,
Dongjoon.

On Tue, Sep 1, 2020 at 7:54 AM Xiao Li <lix...@databricks.com> wrote:

> Want to change my vote to 0, because we are unable to produce an end-user
> query to hit this bug.
>
> Xiao
>
> On Mon, Aug 31, 2020 at 12:41 PM Xiao Li <lix...@databricks.com> wrote:
>
>> -1 due to a regression introduced by a fix in 3.0.1.
>>
>> See https://github.com/apache/spark/pull/29602
>>
>> Xiao
>>
>> On Mon, Aug 31, 2020 at 9:26 AM Tom Graves <tgraves...@yahoo.com.invalid>
>> wrote:
>>
>>> +1
>>>
>>> Tom
>>>
>>> On Friday, August 28, 2020, 09:02:31 AM CDT, 郑瑞峰 <ruife...@foxmail.com>
>>> wrote:
>>>
>>>
>>> Please vote on releasing the following candidate as Apache Spark version
>>> 3.0.1.
>>>
>>> The vote is open until Sep 2nd at 9AM 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 3.0.1
>>> [ ] -1 Do not release this package because ...
>>>
>>> To learn more about Apache Spark, please see http://spark.apache.org/
>>>
>>> There are currently no issues targeting 3.0.1 (try project = SPARK AND
>>> "Target Version/s" = "3.0.1" AND status in (Open, Reopened, "In Progress"))
>>>
>>> The tag to be voted on is v3.0.1-rc3 (commit
>>> dc04bf53fe821b7a07f817966c6c173f3b3788c6):
>>> https://github.com/apache/spark/tree/v3.0.1-rc3
>>>
>>> The release files, including signatures, digests, etc. can be found at:
>>> https://dist.apache.org/repos/dist/dev/spark/v3.0.1-rc3-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-1357/
>>>
>>> The documentation corresponding to this release can be found at:
>>> https://dist.apache.org/repos/dist/dev/spark/v3.0.1-rc3-docs/
>>>
>>> The list of bug fixes going into 3.0.1 can be found at the following URL:
>>> https://s.apache.org/q9g2d
>>>
>>> This release is using the release script of the tag v3.0.1-rc3.
>>>
>>> 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 3.0.1?
>>> ===========================================
>>>
>>> The current list of open tickets targeted at 3.0.1 can be found at:
>>> https://issues.apache.org/jira/projects/SPARK and search for "Target
>>> Version/s" = 3.0.1
>>>
>>> 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 an
>>> appropriate release.
>>>
>>> ==================
>>> 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.
>>>
>>>
>>>
>>
>> --
>> <https://databricks.com/sparkaisummit/north-america>
>>
>
>
> --
> <https://databricks.com/sparkaisummit/north-america>
>

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