Thank you, Holden, Liang-Chi, Huaxin, Jungtaek. We included SPARK-49829, SPARK-50021, SPARK-50022 and reverted SPARK-49909 and SPARK-50011 to stabilize `branch-3.4`. As of now, all branch-3.4 CIs are healthy.
Commit Test: https://github.com/apache/spark/tree/branch-3.4 Scala 2.13 Test: https://github.com/apache/spark/actions/workflows/build_branch34.yml Python Test: https://github.com/apache/spark/actions/workflows/build_branch34_python.yml Since there is no other opinion, I'll prepare and start the Apache Spark 3.4.4 RC1 on next Monday (2024-10-21). Thank you again for your help. Dongjoon. On 2024/10/17 02:44:35 Jungtaek Lim wrote: > There is another open correctness issue for the 3.4 version line - PR is up > and approved by a non-committer, and I'm struggling to find a committer to > review and approve. > > Issue: https://issues.apache.org/jira/browse/SPARK-49829 > PR: https://github.com/apache/spark/pull/48297 > > I'd propose to include this PR into Spark 3.4.4 before calling the 3.4 > version line to be EOL. > > @Liang-Chi Hsieh <vii...@gmail.com> I hope you would be willing to review > the PR. Thanks in advance. > > 2024년 10월 17일 (목) 오전 6:16, huaxin gao <huaxin.ga...@gmail.com>님이 작성: > > > +1 > > > > On Wed, Oct 16, 2024 at 1:53 PM L. C. Hsieh <vii...@gmail.com> wrote: > > > >> +1 > >> > >> Thanks Dongjoon. > >> > >> > >> On Wed, Oct 16, 2024 at 11:41 AM Holden Karau <holden.ka...@gmail.com> > >> wrote: > >> > > >> > +1 on a 3.4.4 EOL release > >> > > >> > On Wed, Oct 16, 2024 at 9:37 AM Dongjoon Hyun <dongjoon.h...@gmail.com> > >> wrote: > >> >> > >> >> Hi, All. > >> >> > >> >> Since the Apache Spark 3.4.0 RC7 vote passed on Apr 6, 2023, > >> branch-3.4 has been maintained and served well until now. > >> >> > >> >> - https://github.com/apache/spark/releases/tag/v3.4.0 (tagged on Apr > >> 6, 2023) > >> >> - https://lists.apache.org/thread/0o61jn9cmg6r0f22ljgjg5c31z8fn0zn > >> (vote result on April 13th, 2023) > >> >> > >> >> As of today, branch-3.4 has 100 additional patches after v3.4.3 > >> (tagged on April 14th about 6 month ago) and reaches the end-of-life this > >> month according to the Apache Spark release cadence, > >> https://spark.apache.org/versioning-policy.html . > >> >> > >> >> $ git log --oneline v3.4.3..HEAD | wc -l > >> >> 100 > >> >> > >> >> Moreover, there are seven unreleased correctness patches. > >> >> > >> >> SPARK-47927 Nullability after join not respected in UDF > >> >> SPARK-48019 ColumnVectors with dictionaries and nulls are not > >> read/copied correctly > >> >> SPARK-48037 SortShuffleWriter lacks shuffle write related metrics > >> resulting in potentially inaccurate data > >> >> SPARK-48105 Fix the data corruption issue when state store unload and > >> snapshotting happens concurrently for HDFS state store > >> >> SPARK-48965 toJSON produces wrong values if DecimalType information is > >> lost in as[Product] > >> >> SPARK-49000 Aggregation with DISTINCT gives wrong results when dealing > >> with literals > >> >> SPARK-49836 The outer query is broken when the subquery uses window > >> function which receives time window as parameter > >> >> > >> >> Along with the recent Apache Spark 4.0.0-preview2 and 3.5.3 releases, > >> I hope the users can get a chance to have these last bits of Apache Spark > >> 3.4.x, and I'd like to propose to have Apache Spark 3.4.4 EOL Release vote > >> on October 21th and volunteer as the release manager. > >> >> > >> >> WDTY? > >> >> > >> >> Please let us know if you need more patches on branch-3.4. > >> >> > >> >> Thanks, > >> >> Dongjoon. > >> > > >> > > >> > > >> > -- > >> > Twitter: https://twitter.com/holdenkarau > >> > Fight Health Insurance: https://www.fighthealthinsurance.com/ > >> > Books (Learning Spark, High Performance Spark, etc.): > >> https://amzn.to/2MaRAG9 > >> > YouTube Live Streams: https://www.youtube.com/user/holdenkarau > >> > Pronouns: she/her > >> > >> --------------------------------------------------------------------- > >> To unsubscribe e-mail: dev-unsubscr...@spark.apache.org > >> > >> > --------------------------------------------------------------------- To unsubscribe e-mail: dev-unsubscr...@spark.apache.org
