I think https://issues.apache.org/jira/browse/SPARK-19280 should be a blocker
Best, Nan On Mon, Mar 20, 2017 at 8:18 PM, Felix Cheung <felixcheun...@hotmail.com> wrote: > I've been scrubbing R and think we are tracking 2 issues > > https://issues.apache.org/jira/browse/SPARK-19237 > > https://issues.apache.org/jira/browse/SPARK-19925 > > > > > ------------------------------ > *From:* holden.ka...@gmail.com <holden.ka...@gmail.com> on behalf of > Holden Karau <hol...@pigscanfly.ca> > *Sent:* Monday, March 20, 2017 3:12:35 PM > *To:* dev@spark.apache.org > *Subject:* Outstanding Spark 2.1.1 issues > > Hi Spark Developers! > > As we start working on the Spark 2.1.1 release I've been looking at our > outstanding issues still targeted for it. I've tried to break it down by > component so that people in charge of each component can take a quick look > and see if any of these things can/should be re-targeted to 2.2 or 2.1.2 & > the overall list is pretty short (only 9 items - 5 if we only look at > explicitly tagged) :) > > If your working on something for Spark 2.1.1 and it doesn't show up in > this list please speak up now :) We have a lot of issues (including "in > progress") that are listed as impacting 2.1.0, but they aren't targeted for > 2.1.1 - if there is something you are working in their which should be > targeted for 2.1.1 please let us know so it doesn't slip through the cracks. > > The query string I used for looking at the 2.1.1 open issues is: > > ((affectedVersion = 2.1.1 AND cf[12310320] is Empty) OR fixVersion = 2.1.1 > OR cf[12310320] = "2.1.1") AND project = spark AND resolution = Unresolved > ORDER BY priority DESC > > None of the open issues appear to be a regression from 2.1.0, but those > seem more likely to show up during the RC process (thanks in advance to > everyone testing their workloads :)) & generally none of them seem to be > > (Note: the cfs are for Target Version/s field) > > Critical Issues: > SQL: > SPARK-19690 <https://issues.apache.org/jira/browse/SPARK-19690> - Join > a streaming DataFrame with a batch DataFrame may not work - PR > https://github.com/apache/spark/pull/17052 (review in progress by > zsxwing, currently failing Jenkins)* > > Major Issues: > SQL: > SPARK-19035 <https://issues.apache.org/jira/browse/SPARK-19035> - rand() > function in case when cause failed - no outstanding PR (consensus on JIRA > seems to be leaning towards it being a real issue but not necessarily > everyone agrees just yet - maybe we should slip this?)* > Deploy: > SPARK-19522 <https://issues.apache.org/jira/browse/SPARK-19522> > - --executor-memory flag doesn't work in local-cluster mode - > https://github.com/apache/spark/pull/16975 (review in progress by vanzin, > but PR currently stalled waiting on response) * > Core: > SPARK-20025 <https://issues.apache.org/jira/browse/SPARK-20025> - Driver > fail over will not work, if SPARK_LOCAL* env is set. - > https://github.com/apache/spark/pull/17357 (waiting on review) * > PySpark: > SPARK-19955 <https://issues.apache.org/jira/browse/SPARK-19955> - Update > run-tests to support conda [ Part of Dropping 2.6 support -- which we > shouldn't do in a minor release -- but also fixes pip installability tests > to run in Jenkins ]- PR failing Jenkins (I need to poke this some more, > but seems like 2.7 support works but some other issues. Maybe slip to 2.2?) > > Minor issues: > Tests: > SPARK-19612 <https://issues.apache.org/jira/browse/SPARK-19612> - Tests > failing with timeout - No PR per-se but it seems unrelated to the 2.1.1 > release. It's not targetted for 2.1.1 but listed as affecting 2.1.1 - I'd > consider explicitly targeting this for 2.2? > PySpark: > SPARK-19570 <https://issues.apache.org/jira/browse/SPARK-19570> - Allow > to disable hive in pyspark shell - https://github.com/apache/sp > ark/pull/16906 PR exists but its difficult to add automated tests for > this (although if SPARK-19955 > <https://issues.apache.org/jira/browse/SPARK-19955> gets in would make > testing this easier) - no reviewers yet. Possible re-target?* > Structured Streaming: > SPARK-19613 <https://issues.apache.org/jira/browse/SPARK-19613> - Flaky > test: StateStoreRDDSuite.versioning and immutability - It's not targetted > for 2.1.1 but listed as affecting 2.1.1 - I'd consider explicitly targeting > this for 2.2? > ML: > SPARK-19759 <https://issues.apache.org/jira/browse/SPARK-19759> > - ALSModel.predict on Dataframes : potential optimization by not using > blas - No PR consider re-targeting unless someone has a PR waiting in the > wings? > > Explicitly targeted issues are marked with a *, the remaining issues are > listed as impacting 2.1.1 and don't have a specific target version set. > > Since 2.1.1 continues the 2.1.0 branch, looking at 2.1.0 shows 1 open > blocker in SQL( SPARK-19983 > <https://issues.apache.org/jira/browse/SPARK-19983> ), > > Query string is: > > affectedVersion = 2.1.0 AND cf[12310320] is EMPTY AND project = spark AND > resolution = Unresolved AND priority = targetPriority > > Continuing on for unresolved 2.1.0 issues in Major there are 163 (76 of > them in progress), 65 Minor (26 in progress), and 9 trivial (6 in progress). > > I'll be going through the 2.1.0 major issues with open PRs that impact the > PySpark component and seeing if any of them should be targeted for 2.1.1, > if anyone from the other components wants to take a look through we might > find some easy wins to be merged. > > Cheers, > > Holden :) > > -- > Cell : 425-233-8271 <(425)%20233-8271> > Twitter: https://twitter.com/holdenkarau >
