I'd like to nominate SPARK-23290
<https://issues.apache.org/jira/browse/SPARK-23290> as a potential blocker
for the 2.3.0 release. It's a regression from 2.2.0 in that user pyspark
code that works in 2.2.0 now fails in the 2.3.0 RCs: the type return type
of date columns changed from object to datetime64[ns]. My understanding of
the Spark Versioning Policy <http://spark.apache.org/versioning-policy.html> is
that user code should continue to run in future versions of Spark with the
same major version number.
Thanks!
On Thu, Feb 1, 2018 at 9:50 AM, Tom Graves <tgraves...@yahoo.com.invalid>
wrote:
>
> Testing with spark 2.3 and I see a difference in the sql coalesce talking
> to hive vs spark 2.2. It seems spark 2.3 ignores the coalesce.
>
> Query:
> spark.sql("SELECT COUNT(DISTINCT(something)) FROM sometable WHERE dt >=
> '20170301' AND dt <= '20170331' AND something IS NOT
> NULL").coalesce(160000).show()
>
> in spark 2.2 the coalesce works here, but in spark 2.3, it doesn't.
> Anyone know about this issue or are there some weird config changes,
> otherwise I'll file a jira?
>
> Note I also see a performance difference when reading cached data. Spark
> 2.3. Small query on 19GB cached data, spark 2.3 is 30% worse. This is only
> 13 seconds on spark 2.2 vs 17 seconds on spark 2.3. Straight up reading
> from hive (orc) seems better though.
>
> Tom
>
>
>
> On Thursday, February 1, 2018, 11:23:45 AM CST, Michael Heuer <
> heue...@gmail.com> wrote:
>
>
> We found two classes new to Spark 2.3.0 that must be registered in Kryo
> for our tests to pass on RC2
>
> org.apache.spark.sql.execution.datasources.BasicWriteTaskStats
> org.apache.spark.sql.execution.datasources.ExecutedWriteSummary
>
> https://github.com/bigdatagenomics/adam/pull/1897
>
> Perhaps a mention in release notes?
>
> michael
>
>
> On Thu, Feb 1, 2018 at 3:29 AM, Nick Pentreath <nick.pentre...@gmail.com>
> wrote:
>
> All MLlib QA JIRAs resolved. Looks like SparkR too, so from the ML side
> that should be everything outstanding.
>
>
> On Thu, 1 Feb 2018 at 06:21 Yin Huai <yh...@databricks.com> wrote:
>
> seems we are not running tests related to pandas in pyspark tests (see my
> email "python tests related to pandas are skipped in jenkins"). I think we
> should fix this test issue and make sure all tests are good before cutting
> RC3.
>
> On Wed, Jan 31, 2018 at 10:12 AM, Sameer Agarwal <samee...@apache.org>
> wrote:
>
> Just a quick status update on RC3 -- SPARK-23274
> <https://issues.apache.org/jira/browse/SPARK-23274> was resolved
> yesterday and tests have been quite healthy throughout this week and the
> last. I'll cut the new RC as soon as the remaining blocker (SPARK-23202
> <https://issues.apache.org/jira/browse/SPARK-23202>) is resolved.
>
>
> On 30 January 2018 at 10:12, Andrew Ash <and...@andrewash.com> wrote:
>
> I'd like to nominate SPARK-23274
> <https://issues.apache.org/jira/browse/SPARK-23274> as a potential
> blocker for the 2.3.0 release as well, due to being a regression from
> 2.2.0. The ticket has a simple repro included, showing a query that works
> in prior releases but now fails with an exception in the catalyst optimizer.
>
> On Fri, Jan 26, 2018 at 10:41 AM, Sameer Agarwal <sameer.a...@gmail.com>
> wrote:
>
> This vote has failed due to a number of aforementioned blockers. I'll
> follow up with RC3 as soon as the 2 remaining (non-QA) blockers are
> resolved: https://s.apache. org/oXKi <https://s.apache.org/oXKi>
>
>
> On 25 January 2018 at 12:59, Sameer Agarwal <sameer.a...@gmail.com> wrote:
>
>
> Most tests pass on RC2, except I'm still seeing the timeout caused by
> https://issues.apache.org/
> jira/browse/SPARK-23055
> <https://issues.apache.org/jira/browse/SPARK-23055> ; the tests never
> finish. I followed the thread a bit further and wasn't clear whether it was
> subsequently re-fixed for 2.3.0 or not. It says it's resolved along with
> https://issues.apache.
> org/jira/browse/SPARK-22908
> <https://issues.apache.org/jira/browse/SPARK-22908> for 2.3.0 though I
> am still seeing these tests fail or hang:
>
> - subscribing topic by name from earliest offsets (failOnDataLoss: false)
> - subscribing topic by name from earliest offsets (failOnDataLoss: true)
>
>
> Sean, while some of these tests were timing out on RC1, we're not aware of
> any known issues in RC2. Both maven (https://amplab.cs.berkeley.
> edu/jenkins/view/Spark%20QA% 20Test%20(Dashboard)/job/
> spark-branch-2.3-test-maven- hadoop-2.6/146/testReport/org.
> apache.spark.sql.kafka010/ history/
> <https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Test%20(Dashboard)/job/spark-branch-2.3-test-maven-hadoop-2.6/146/testReport/org.apache.spark.sql.kafka010/history/>)
> and sbt (https://amplab.cs.berkeley. edu/jenkins/view/Spark%20QA%
> 20Test%20(Dashboard)/job/ spark-branch-2.3-test-sbt-
> hadoop-2.6/123/testReport/org. apache.spark.sql.kafka010/ history/
> <https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Test%20(Dashboard)/job/spark-branch-2.3-test-sbt-hadoop-2.6/123/testReport/org.apache.spark.sql.kafka010/history/>)
> historical builds on jenkins for org.apache.spark.sql. kafka010 look fairly
> healthy. If you're still seeing timeouts in RC2, can you create a JIRA with
> any applicable build/env info?
>
>
>
> On Tue, Jan 23, 2018 at 9:01 AM Sean Owen <so...@cloudera.com> wrote:
>
> I'm not seeing that same problem on OS X and /usr/bin/tar. I tried
> unpacking it with 'xvzf' and also unzipping it first, and it untarred
> without warnings in either case.
>
> I am encountering errors while running the tests, different ones each
> time, so am still figuring out whether there is a real problem or just
> flaky tests.
>
> These issues look like blockers, as they are inherently to be completed
> before the 2.3 release. They are mostly not done. I suppose I'd -1 on
> behalf of those who say this needs to be done first, though, we can keep
> testing.
>
> SPARK-23105 Spark MLlib, GraphX 2.3 QA umbrella
> SPARK-23114 Spark R 2.3 QA umbrella
>
> Here are the remaining items targeted for 2.3:
>
> SPARK-15689 Data source API v2
> SPARK-20928 SPIP: Continuous Processing Mode for Structured Streaming
> SPARK-21646 Add new type coercion rules to compatible with Hive
> SPARK-22386 Data Source V2 improvements
> SPARK-22731 Add a test for ROWID type to OracleIntegrationSuite
> SPARK-22735 Add VectorSizeHint to ML features documentation
> SPARK-22739 Additional Expression Support for Objects
> SPARK-22809 pyspark is sensitive to imports with dots
> SPARK-22820 Spark 2.3 SQL API audit
>
>
> On Mon, Jan 22, 2018 at 7:09 PM Marcelo Vanzin <van...@cloudera.com>
> wrote:
>
> +0
>
> Signatures check out. Code compiles, although I see the errors in [1]
> when untarring the source archive; perhaps we should add "use GNU tar"
> to the RM checklist?
>
> Also ran our internal tests and they seem happy.
>
> My concern is the list of open bugs targeted at 2.3.0 (ignoring the
> documentation ones). It is not long, but it seems some of those need
> to be looked at. It would be nice for the committers who are involved
> in those bugs to take a look.
>
> [1] https://superuser.com/ questions/318809/linux-os-x-
> tar-incompatibility-tarballs- created-on-os-x-give-errors- when-unt
> <https://superuser.com/questions/318809/linux-os-x-tar-incompatibility-tarballs-created-on-os-x-give-errors-when-unt>
>
>
> On Mon, Jan 22, 2018 at 1:36 PM, Sameer Agarwal <samee...@apache.org>
> wrote:
> > Please vote on releasing the following candidate as Apache Spark version
> > 2.3.0. The vote is open until Friday January 26, 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 https://spark.apache.org/
> >
> > The tag to be voted on is v2.3.0-rc2:
> > https://github.com/apache/ spark/tree/v2.3.0-rc2
> <https://github.com/apache/spark/tree/v2.3.0-rc2>
> > ( 489ecb0ef23e5d9b705e5e5bae4fa3 d871bdac91)
> >
> > List of JIRA tickets resolved in this release can be found here:
> > https://issues.apache.org/ jira/projects/SPARK/versions/ 12339551
> <https://issues.apache.org/jira/projects/SPARK/versions/12339551>
> >
> > The release files, including signatures, digests, etc. can be found at:
> > https://dist.apache.org/repos/ dist/dev/spark/v2.3.0-rc2-bin/
> <https://dist.apache.org/repos/dist/dev/spark/v2.3.0-rc2-bin/>
> >
> > Release artifacts are signed with the following key:
> > https://dist.apache.org/repos/ dist/dev/spark/KEYS
> <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-1262/
> <https://repository.apache.org/content/repositories/orgapachespark-1262/>
> >
> > The documentation corresponding to this release can be found at:
> > https://dist.apache.org/repos/ dist/dev/spark/v2.3.0-rc2-
> docs/_site/index.html
> <https://dist.apache.org/repos/dist/dev/spark/v2.3.0-rc2-docs/_site/index.html>
> >
> >
> > FAQ
> >
> > ============================== =========
> > What are the unresolved issues targeted for 2.3.0?
> > ============================== =========
> >
> > Please see https://s.apache.org/oXKi. 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 2.3.0 as
> > appropriate.
> >
> > ===================
> > 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
> > https://s.apache.org/WmoI).
> >
> >
> > Regards,
> > Sameer
>
>
>
> --
> Marcelo
>
> ------------------------------ ------------------------------ ---------
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>
>
>
>
>
> --
> Sameer Agarwal
> Computer Science | UC Berkeley
> http://cs.berkeley.edu/~ sameerag <http://cs.berkeley.edu/~sameerag>
>
>
>
>
>
>
