Thank you, Sean! Bests, Dongjoon.
On Thu, Jan 3, 2019 at 2:50 PM Sean Owen <sro...@gmail.com> wrote: > Yes, that one's not going to be back-ported to 2.3. I think it's fine to > proceed with a 2.2 release with what's there now and call it done. > Note that Spark 2.3 would be EOL around September of this year. > > On Thu, Jan 3, 2019 at 2:31 PM Dongjoon Hyun <dongjoon.h...@gmail.com> > wrote: > >> Thank you for additional support for 2.2.3, Felix and Takeshi! >> >> >> The following is the update for Apache Spark 2.2.3 release. >> >> For correctness issues, two more patches landed on `branch-2.2`. >> >> SPARK-22951 fix aggregation after dropDuplicates on empty dataframes >> SPARK-25591 Avoid overwriting deserialized accumulator >> >> Currently, if we use the following JIRA search query, there exist one >> JIRA issue; SPARK-25206. >> >> Query: project = SPARK AND fixVersion in (2.3.0, 2.3.1, 2.3.2, >> 2.3.3, 2.4.0, 2.4.1, 3.0.0) AND fixVersion not in (2.2.0, 2.2.1, 2.2.2, >> 2.2.3) AND affectedVersion in (2.1.0, 2.1.1, 2.1.2, 2.1.3, 2.2.0, 2.2.1, >> 2.2.2, 2.2.3) AND labels in (Correctness, correctness) >> >> SPARK-25206 ( https://issues.apache.org/jira/browse/SPARK-25206 ) has >> >> Affected Version: 2.2.2, 2.3.1 >> Target Versions: 2.3.2, 2.4.0 >> Fixed Version: 2.4.0 >> >> Although SPARK-25206 is labeled as a correctness issue, 2.3.2 already >> missed it due to the technical difficulties and risks. Instead, it's marked >> as a known issue. As we see, it's not targeted to 2.3.3, too. >> >> I know the correctness issue policy on new releases. However, for me, >> Spark 2.2.3 is a little bit exceptional release since it's a farewell >> release and branch-2.2 is already EOL and too far from the active branch >> master. >> >> So, I'd like to put SPARK-25206 out of the scope of the farewell release >> and recommend the users to use the other latest release. For example, Spark >> 2.4.0 for SPARK-25206. >> >> How do you think about that? >> >> Bests, >> Dongjoon. >> >>> >>>
