I'll work on resolving some of the ML QA blockers this week, but it'd be great to get help. *@committers & contributors who work on ML*, many of you have helped in the past, so please help take QA tasks wherever possible. (Thanks Yanbo & Felix for jumping in already.) Anyone is welcome to chip in of course! Joseph
On Thu, May 4, 2017 at 4:09 PM, Sean Owen <so...@cloudera.com> wrote: > The tests pass, licenses are OK, sigs, etc. I'd endorse it but we do still > have blockers, so I assume people mean we need there will be another RC at > some point. > > Blocker > SPARK-20503 ML 2.2 QA: API: Python API coverage > SPARK-20501 ML, Graph 2.2 QA: API: New Scala APIs, docs > SPARK-20502 ML, Graph 2.2 QA: API: Experimental, DeveloperApi, final, > sealed audit > SPARK-20509 SparkR 2.2 QA: New R APIs and API docs > SPARK-20504 ML 2.2 QA: API: Java compatibility, docs > SPARK-20500 ML, Graph 2.2 QA: API: Binary incompatible changes > > Critical > SPARK-20499 Spark MLlib, GraphX 2.2 QA umbrella > SPARK-20520 R streaming tests failed on Windows > SPARK-18891 Support for specific collection types > SPARK-20505 ML, Graph 2.2 QA: Update user guide for new features & APIs > SPARK-20364 Parquet predicate pushdown on columns with dots return empty > results > SPARK-20508 Spark R 2.2 QA umbrella > SPARK-20512 SparkR 2.2 QA: Programming guide, migration guide, vignettes > updates > SPARK-20513 Update SparkR website for 2.2 > SPARK-20510 SparkR 2.2 QA: Update user guide for new features & APIs > SPARK-20507 Update MLlib, GraphX websites for 2.2 > SPARK-20506 ML, Graph 2.2 QA: Programming guide update and migration guide > SPARK-19690 Join a streaming DataFrame with a batch DataFrame may not work > SPARK-7768 Make user-defined type (UDT) API public > SPARK-4502 Spark SQL reads unneccesary nested fields from Parquet > SPARK-17626 TPC-DS performance improvements using star-schema heuristics > > > On Thu, May 4, 2017 at 6:07 PM Michael Armbrust <mich...@databricks.com> > wrote: > >> Please vote on releasing the following candidate as Apache Spark version >> 2.2.0. The vote is open until Tues, May 9th, 2017 at 12:00 PST and >> passes if a majority of at least 3 +1 PMC votes are cast. >> >> [ ] +1 Release this package as Apache Spark 2.2.0 >> [ ] -1 Do not release this package because ... >> >> >> To learn more about Apache Spark, please see http://spark.apache.org/ >> >> The tag to be voted on is v2.2.0-rc2 >> <https://github.com/apache/spark/tree/v2.2.0-rc2> (1d4017b44d5e6ad >> 156abeaae6371747f111dd1f9) >> >> List of JIRA tickets resolved can be found with this filter >> <https://issues.apache.org/jira/browse/SPARK-20134?jql=project%20%3D%20SPARK%20AND%20fixVersion%20%3D%202.2.0> >> . >> >> The release files, including signatures, digests, etc. can be found at: >> http://home.apache.org/~pwendell/spark-releases/spark-2.2.0-rc2-bin/ >> >> Release artifacts are signed with the following key: >> https://people.apache.org/keys/committer/pwendell.asc >> >> The staging repository for this release can be found at: >> https://repository.apache.org/content/repositories/orgapachespark-1236/ >> >> The documentation corresponding to this release can be found at: >> http://people.apache.org/~pwendell/spark-releases/spark-2.2.0-rc2-docs/ >> >> >> *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. >> >> *What should happen to JIRA tickets still targeting 2.2.0?* >> >> 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 2.3.0 or 2.2.1. >> >> *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 2.1.1. >> > -- Joseph Bradley Software Engineer - Machine Learning Databricks, Inc. [image: http://databricks.com] <http://databricks.com/>
