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.
