Yup, it would be great to release these more often.
> On Dec 9, 2019, at 4:25 PM, Takeshi Yamamuro <linguin....@gmail.com> wrote:
>
> +1; Looks great if we can in terms of user's feedbacks.
>
> Bests,
> Takeshi
>
> On Tue, Dec 10, 2019 at 3:14 AM Dongjoon Hyun <dongjoon.h...@gmail.com
> <mailto:dongjoon.h...@gmail.com>> wrote:
> Thank you, All.
>
> +1 for another `3.0-preview`.
>
> Also, thank you Yuming for volunteering for that!
>
> Bests,
> Dongjoon.
>
>
> On Mon, Dec 9, 2019 at 9:39 AM Xiao Li <lix...@databricks.com
> <mailto:lix...@databricks.com>> wrote:
> When entering the official release candidates, the new features have to be
> disabled or even reverted [if the conf is not available] if the fixes are not
> trivial; otherwise, we might need 10+ RCs to make the final release. The new
> features should not block the release based on the previous discussions.
>
> I agree we should have code freeze at the beginning of 2020. The preview
> releases should not block the official releases. The preview is just to
> collect more feedback about these new features or behavior changes.
>
> Also, for the release of Spark 3.0, we still need the Hive community to do us
> a favor to release 2.3.7 for having HIVE-22190
> <https://issues.apache.org/jira/browse/HIVE-22190>. Before asking Hive
> community to do 2.3.7 release, if possible, we want our Spark community to
> have more tries, especially the support of JDK 11 on Hadoop 2.7 and 3.2,
> which is based on Hive 2.3 execution JAR. During the preview stage, we might
> find more issues that are not covered by our test cases.
>
>
>
> On Mon, Dec 9, 2019 at 4:55 AM Sean Owen <sro...@gmail.com
> <mailto:sro...@gmail.com>> wrote:
> Seems fine to me of course. Honestly that wouldn't be a bad result for
> a release candidate, though we would probably roll another one now.
> How about simply moving to a release candidate? If not now then at
> least move to code freeze from the start of 2020. There is also some
> downside in pushing out the 3.0 release further with previews.
>
> On Mon, Dec 9, 2019 at 12:32 AM Xiao Li <gatorsm...@gmail.com
> <mailto:gatorsm...@gmail.com>> wrote:
> >
> > I got many great feedbacks from the community about the recent 3.0 preview
> > release. Since the last 3.0 preview release, we already have 353 commits
> > [https://github.com/apache/spark/compare/v3.0.0-preview...master
> > <https://github.com/apache/spark/compare/v3.0.0-preview...master>]. There
> > are various important features and behavior changes we want the community
> > to try before entering the official release candidates of Spark 3.0.
> >
> >
> > Below is my selected items that are not part of the last 3.0 preview but
> > already available in the upstream master branch:
> >
> > Support JDK 11 with Hadoop 2.7
> > Spark SQL will respect its own default format (i.e., parquet) when users do
> > CREATE TABLE without USING or STORED AS clauses
> > Enable Parquet nested schema pruning and nested pruning on expressions by
> > default
> > Add observable Metrics for Streaming queries
> > Column pruning through nondeterministic expressions
> > RecordBinaryComparator should check endianness when compared by long
> > Improve parallelism for local shuffle reader in adaptive query execution
> > Upgrade Apache Arrow to version 0.15.1
> > Various interval-related SQL support
> > Add a mode to pin Python thread into JVM's
> > Provide option to clean up completed files in streaming query
> >
> > I am wondering if we can have another preview release for Spark 3.0? This
> > can help us find the design/API defects as early as possible and avoid the
> > significant delay of the upcoming Spark 3.0 release
> >
> >
> > Also, any committer is willing to volunteer as the release manager of the
> > next preview release of Spark 3.0, if we have such a release?
> >
> >
> > Cheers,
> >
> >
> > Xiao
>
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> Takeshi Yamamuro
