+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> 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> 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> 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> 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]. >>> 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 >>> >>> --------------------------------------------------------------------- >>> To unsubscribe e-mail: dev-unsubscr...@spark.apache.org >>> >>> >> >> -- >> [image: Databricks Summit - Watch the talks] >> <https://databricks.com/sparkaisummit/north-america> >> > -- --- Takeshi Yamamuro
