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 >>>>> >>>>> >>>>> 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 ; 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 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/) >>>>>> 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/) >>>>>> 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 >>>>>>>>> >>>>>>>>> >>>>>>>>> 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 >>>>>>>>> > (489ecb0ef23e5d9b705e5e5bae4fa3d871bdac91) >>>>>>>>> > >>>>>>>>> > List of JIRA tickets resolved in this release can be found here: >>>>>>>>> > 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/ >>>>>>>>> > >>>>>>>>> > Release artifacts are signed with the following key: >>>>>>>>> > 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/ >>>>>>>>> > >>>>>>>>> > 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 >>>>>>>>> > >>>>>>>>> > >>>>>>>>> > 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 >>>>>>>>> >>>>>>>>> ------------------------------------------------------------ >>>>>>>>> --------- >>>>>>>>> To unsubscribe e-mail: dev-unsubscr...@spark.apache.org >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>> >>>>>> >>>>>> -- >>>>>> Sameer Agarwal >>>>>> Computer Science | UC Berkeley >>>>>> http://cs.berkeley.edu/~sameerag >>>>>> >>>>> >>>> >>> >>
