Thank you, Takeshi! Dongjoon Hyun <dongjoon.h...@gmail.com> 于2019年1月8日周二 下午10:13写道：
> Great! Thank you, Takeshi! :D > > Bests, > Dongjoon. > > On Tue, Jan 8, 2019 at 8:47 PM Takeshi Yamamuro <linguin....@gmail.com> > wrote: > >> If there is no other volunteer for the release of 2.3.3, I'd like to. >> >> best, >> takeshi >> >> On Fri, Jan 4, 2019 at 11:49 AM Dongjoon Hyun <dongjoon.h...@gmail.com> >> wrote: >> >>> 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. >>>>> >>>>>> >>>>>> >> >> -- >> --- >> Takeshi Yamamuro >> >
