Ur, Sean. I prefer a full release like 2.0.0-preview.
https://archive.apache.org/dist/spark/spark-2.0.0-preview/ And, thank you, Xingbo! Could you take a look at website generation? It seems to be broken on `master`. Bests, Dongjoon. On Fri, Sep 13, 2019 at 11:30 AM Xingbo Jiang <jiangxb1...@gmail.com> wrote: > Hi all, > > I would like to volunteer to be the release manager of Spark 3 preview, > thanks! > > Sean Owen <sro...@gmail.com> 于2019年9月13日周五 上午11:21写道： > >> Well, great to hear the unanimous support for a Spark 3 preview >> release. Now, I don't know how to make releases myself :) I would >> first open it up to our revered release managers: would anyone be >> interested in trying to make one? sounds like it's not too soon to get >> what's in master out for evaluation, as there aren't any major >> deficiencies left, although a number of items to consider for the >> final release. >> >> I think we just need one release, targeting Hadoop 3.x / Hive 2.x in >> order to make it possible to test with JDK 11. (We're only on Scala >> 2.12 at this point.) >> >> On Thu, Sep 12, 2019 at 7:32 PM Reynold Xin <r...@databricks.com> wrote: >> > >> > +1! Long due for a preview release. >> > >> > >> > On Thu, Sep 12, 2019 at 5:26 PM, Holden Karau <hol...@pigscanfly.ca> >> wrote: >> >> >> >> I like the idea from the PoV of giving folks something to start >> testing against and exploring so they can raise issues with us earlier in >> the process and we have more time to make calls around this. >> >> >> >> On Thu, Sep 12, 2019 at 4:15 PM John Zhuge <jzh...@apache.org> wrote: >> >>> >> >>> +1 Like the idea as a user and a DSv2 contributor. >> >>> >> >>> On Thu, Sep 12, 2019 at 4:10 PM Jungtaek Lim <kabh...@gmail.com> >> wrote: >> >>>> >> >>>> +1 (as a contributor) from me to have preview release on Spark 3 as >> it would help to test the feature. When to cut preview release is >> questionable, as major works are ideally to be done before that - if we are >> intended to introduce new features before official release, that should >> work regardless of this, but if we are intended to have opportunity to test >> earlier, ideally it should. >> >>>> >> >>>> As a one of contributors in structured streaming area, I'd like to >> add some items for Spark 3.0, both "must be done" and "better to have". For >> "better to have", I pick some items for new features which committers >> reviewed couple of rounds and dropped off without soft-reject (No valid >> reason to stop). For Spark 2.4 users, only added feature for structured >> streaming is Kafka delegation token. (given we assume revising Kafka >> consumer pool as improvement) I hope we provide some gifts for structured >> streaming users in Spark 3.0 envelope. >> >>>> >> >>>> > must be done >> >>>> * SPARK-26154 Stream-stream joins - left outer join gives >> inconsistent output >> >>>> It's a correctness issue with multiple users reported, being >> reported at Nov. 2018. There's a way to reproduce it consistently, and we >> have a patch submitted at Jan. 2019 to fix it. >> >>>> >> >>>> > better to have >> >>>> * SPARK-23539 Add support for Kafka headers in Structured Streaming >> >>>> * SPARK-26848 Introduce new option to Kafka source - specify >> timestamp to start and end offset >> >>>> * SPARK-20568 Delete files after processing in structured streaming >> >>>> >> >>>> There're some more new features/improvements items in SS, but given >> we're talking about ramping-down, above list might be realistic one. >> >>>> >> >>>> >> >>>> >> >>>> On Thu, Sep 12, 2019 at 9:53 AM Jean Georges Perrin <j...@jgp.net> >> wrote: >> >>>>> >> >>>>> As a user/non committer, +1 >> >>>>> >> >>>>> I love the idea of an early 3.0.0 so we can test current dev >> against it, I know the final 3.x will probably need another round of >> testing when it gets out, but less for sure... I know I could checkout and >> compile, but having a “packaged” preversion is great if it does not take >> too much time to the team... >> >>>>> >> >>>>> jg >> >>>>> >> >>>>> >> >>>>> On Sep 11, 2019, at 20:40, Hyukjin Kwon <gurwls...@gmail.com> >> wrote: >> >>>>> >> >>>>> +1 from me too but I would like to know what other people think too. >> >>>>> >> >>>>> 2019년 9월 12일 (목) 오전 9:07, Dongjoon Hyun <dongjoon.h...@gmail.com>님이 >> 작성: >> >>>>>> >> >>>>>> Thank you, Sean. >> >>>>>> >> >>>>>> I'm also +1 for the following three. >> >>>>>> >> >>>>>> 1. Start to ramp down (by the official branch-3.0 cut) >> >>>>>> 2. Apache Spark 3.0.0-preview in 2019 >> >>>>>> 3. Apache Spark 3.0.0 in early 2020 >> >>>>>> >> >>>>>> For JDK11 clean-up, it will meet the timeline and `3.0.0-preview` >> helps it a lot. >> >>>>>> >> >>>>>> After this discussion, can we have some timeline for `Spark 3.0 >> Release Window` in our versioning-policy page? >> >>>>>> >> >>>>>> - https://spark.apache.org/versioning-policy.html >> >>>>>> >> >>>>>> Bests, >> >>>>>> Dongjoon. >> >>>>>> >> >>>>>> >> >>>>>> On Wed, Sep 11, 2019 at 11:54 AM Michael Heuer <heue...@gmail.com> >> wrote: >> >>>>>>> >> >>>>>>> I would love to see Spark + Hadoop + Parquet + Avro compatibility >> problems resolved, e.g. >> >>>>>>> >> >>>>>>> https://issues.apache.org/jira/browse/SPARK-25588 >> >>>>>>> https://issues.apache.org/jira/browse/SPARK-27781 >> >>>>>>> >> >>>>>>> Note that Avro is now at 1.9.1, binary-incompatible with 1.8.x. >> As far as I know, Parquet has not cut a release based on this new version. >> >>>>>>> >> >>>>>>> Then out of curiosity, are the new Spark Graph APIs targeting 3.0? >> >>>>>>> >> >>>>>>> https://github.com/apache/spark/pull/24851 >> >>>>>>> https://github.com/apache/spark/pull/24297 >> >>>>>>> >> >>>>>>> michael >> >>>>>>> >> >>>>>>> >> >>>>>>> On Sep 11, 2019, at 1:37 PM, Sean Owen <sro...@apache.org> wrote: >> >>>>>>> >> >>>>>>> I'm curious what current feelings are about ramping down towards a >> >>>>>>> Spark 3 release. It feels close to ready. There is no fixed date, >> >>>>>>> though in the past we had informally tossed around "back end of >> 2019". >> >>>>>>> For reference, Spark 1 was May 2014, Spark 2 was July 2016. I'd >> expect >> >>>>>>> Spark 2 to last longer, so to speak, but feels like Spark 3 is >> coming >> >>>>>>> due. >> >>>>>>> >> >>>>>>> What are the few major items that must get done for Spark 3, in >> your >> >>>>>>> opinion? Below are all of the open JIRAs for 3.0 (which everyone >> >>>>>>> should feel free to update with things that aren't really needed >> for >> >>>>>>> Spark 3; I already triaged some). >> >>>>>>> >> >>>>>>> For me, it's: >> >>>>>>> - DSv2? >> >>>>>>> - Finishing touches on the Hive, JDK 11 update >> >>>>>>> >> >>>>>>> What about considering a preview release earlier, as happened for >> >>>>>>> Spark 2, to get feedback much earlier than the RC cycle? Could >> that >> >>>>>>> even happen ... about now? >> >>>>>>> >> >>>>>>> I'm also wondering what a realistic estimate of Spark 3 release >> is. My >> >>>>>>> guess is quite early 2020, from here. >> >>>>>>> >> >>>>>>> >> >>>>>>> >> >>>>>>> SPARK-29014 DataSourceV2: Clean up current, default, and session >> catalog uses >> >>>>>>> SPARK-28900 Test Pyspark, SparkR on JDK 11 with run-tests >> >>>>>>> SPARK-28883 Fix a flaky test: ThriftServerQueryTestSuite >> >>>>>>> SPARK-28717 Update SQL ALTER TABLE RENAME to use TableCatalog API >> >>>>>>> SPARK-28588 Build a SQL reference doc >> >>>>>>> SPARK-28629 Capture the missing rules in HiveSessionStateBuilder >> >>>>>>> SPARK-28684 Hive module support JDK 11 >> >>>>>>> SPARK-28548 explain() shows wrong result for persisted DataFrames >> >>>>>>> after some operations >> >>>>>>> SPARK-28372 Document Spark WEB UI >> >>>>>>> SPARK-28476 Support ALTER DATABASE SET LOCATION >> >>>>>>> SPARK-28264 Revisiting Python / pandas UDF >> >>>>>>> SPARK-28301 fix the behavior of table name resolution with >> multi-catalog >> >>>>>>> SPARK-28155 do not leak SaveMode to file source v2 >> >>>>>>> SPARK-28103 Cannot infer filters from union table with empty local >> >>>>>>> relation table properly >> >>>>>>> SPARK-28024 Incorrect numeric values when out of range >> >>>>>>> SPARK-27936 Support local dependency uploading from --py-files >> >>>>>>> SPARK-27884 Deprecate Python 2 support in Spark 3.0 >> >>>>>>> SPARK-27763 Port test cases from PostgreSQL to Spark SQL >> >>>>>>> SPARK-27780 Shuffle server & client should be versioned to enable >> >>>>>>> smoother upgrade >> >>>>>>> SPARK-27714 Support Join Reorder based on Genetic Algorithm when >> the # >> >>>>>>> of joined tables > 12 >> >>>>>>> SPARK-27471 Reorganize public v2 catalog API >> >>>>>>> SPARK-27520 Introduce a global config system to replace >> hadoopConfiguration >> >>>>>>> SPARK-24625 put all the backward compatible behavior change >> configs >> >>>>>>> under spark.sql.legacy.* >> >>>>>>> SPARK-24640 size(null) returns null >> >>>>>>> SPARK-24702 Unable to cast to calendar interval in spark sql. >> >>>>>>> SPARK-24838 Support uncorrelated IN/EXISTS subqueries for more >> operators >> >>>>>>> SPARK-24941 Add RDDBarrier.coalesce() function >> >>>>>>> SPARK-25017 Add test suite for ContextBarrierState >> >>>>>>> SPARK-25083 remove the type erasure hack in data source scan >> >>>>>>> SPARK-25383 Image data source supports sample pushdown >> >>>>>>> SPARK-27272 Enable blacklisting of node/executor on fetch >> failures by default >> >>>>>>> SPARK-27296 User Defined Aggregating Functions (UDAFs) have a >> major >> >>>>>>> efficiency problem >> >>>>>>> SPARK-25128 multiple simultaneous job submissions against k8s >> backend >> >>>>>>> cause driver pods to hang >> >>>>>>> SPARK-26731 remove EOLed spark jobs from jenkins >> >>>>>>> SPARK-26664 Make DecimalType's minimum adjusted scale configurable >> >>>>>>> SPARK-21559 Remove Mesos fine-grained mode >> >>>>>>> SPARK-24942 Improve cluster resource management with jobs >> containing >> >>>>>>> barrier stage >> >>>>>>> SPARK-25914 Separate projection from grouping and aggregate in >> logical Aggregate >> >>>>>>> SPARK-26022 PySpark Comparison with Pandas >> >>>>>>> SPARK-20964 Make some keywords reserved along with the ANSI/SQL >> standard >> >>>>>>> SPARK-26221 Improve Spark SQL instrumentation and metrics >> >>>>>>> SPARK-26425 Add more constraint checks in file streaming source to >> >>>>>>> avoid checkpoint corruption >> >>>>>>> SPARK-25843 Redesign rangeBetween API >> >>>>>>> SPARK-25841 Redesign window function rangeBetween API >> >>>>>>> SPARK-25752 Add trait to easily whitelist logical operators that >> >>>>>>> produce named output from CleanupAliases >> >>>>>>> SPARK-23210 Introduce the concept of default value to schema >> >>>>>>> SPARK-25640 Clarify/Improve EvalType for grouped aggregate and >> window aggregate >> >>>>>>> SPARK-25531 new write APIs for data source v2 >> >>>>>>> SPARK-25547 Pluggable jdbc connection factory >> >>>>>>> SPARK-20845 Support specification of column names in INSERT INTO >> >>>>>>> SPARK-24417 Build and Run Spark on JDK11 >> >>>>>>> SPARK-24724 Discuss necessary info and access in barrier mode + >> Kubernetes >> >>>>>>> SPARK-24725 Discuss necessary info and access in barrier mode + >> Mesos >> >>>>>>> SPARK-25074 Implement maxNumConcurrentTasks() in >> >>>>>>> MesosFineGrainedSchedulerBackend >> >>>>>>> SPARK-23710 Upgrade the built-in Hive to 2.3.5 for hadoop-3.2 >> >>>>>>> SPARK-25186 Stabilize Data Source V2 API >> >>>>>>> SPARK-25376 Scenarios we should handle but missed in 2.4 for >> barrier >> >>>>>>> execution mode >> >>>>>>> SPARK-25390 data source V2 API refactoring >> >>>>>>> SPARK-7768 Make user-defined type (UDT) API public >> >>>>>>> SPARK-14922 Alter Table Drop Partition Using Predicate-based >> Partition Spec >> >>>>>>> SPARK-15691 Refactor and improve Hive support >> >>>>>>> SPARK-15694 Implement ScriptTransformation in sql/core >> >>>>>>> SPARK-16217 Support SELECT INTO statement >> >>>>>>> SPARK-16452 basic INFORMATION_SCHEMA support >> >>>>>>> SPARK-18134 SQL: MapType in Group BY and Joins not working >> >>>>>>> SPARK-18245 Improving support for bucketed table >> >>>>>>> SPARK-19842 Informational Referential Integrity Constraints >> Support in Spark >> >>>>>>> SPARK-22231 Support of map, filter, withColumn, dropColumn in >> nested >> >>>>>>> list of structures >> >>>>>>> SPARK-22632 Fix the behavior of timestamp values for R's >> DataFrame to >> >>>>>>> respect session timezone >> >>>>>>> SPARK-22386 Data Source V2 improvements >> >>>>>>> SPARK-24723 Discuss necessary info and access in barrier mode + >> YARN >> >>>>>>> >> >>>>>>> >> --------------------------------------------------------------------- >> >>>>>>> To unsubscribe e-mail: dev-unsubscr...@spark.apache.org >> >>>>>>> >> >>>>>>> >> >>>> >> >>>> >> >>>> -- >> >>>> Name : Jungtaek Lim >> >>>> Blog : http://medium.com/@heartsavior >> >>>> Twitter : http://twitter.com/heartsavior >> >>>> LinkedIn : http://www.linkedin.com/in/heartsavior >> >>> >> >>> >> >>> >> >>> -- >> >>> John Zhuge >> >> >> >> >> >> >> >> -- >> >> Twitter: https://twitter.com/holdenkarau >> >> Books (Learning Spark, High Performance Spark, etc.): >> https://amzn.to/2MaRAG9 >> >> YouTube Live Streams: https://www.youtube.com/user/holdenkarau >> > >> > >> >> --------------------------------------------------------------------- >> To unsubscribe e-mail: dev-unsubscr...@spark.apache.org >> >>
