Introducing English SDK for Apache Spark - Seeking Your Feedback and Contributions

ser-friendly. Thank you in advance for your attention and involvement. We look forward to hearing your thoughts and seeing your contributions! Best, Gengliang Wang

Re: Stickers and Swag

FYI now you can find the shopping information on https://spark.apache.org/community as well :) Gengliang > On Jun 14, 2022, at 7:47 PM, Hyukjin Kwon wrote: > > Woohoo > > On Tue, 14 Jun 2022 at 15:04, Xiao Li > wrote: >

Re: [ANNOUNCE] Apache Spark 3.2.1 released

Thanks to Huaxin for driving the release! Fengyu, this is a known issue that will be fixed in the 3.3 release. Currently, the "hadoop3.2" means 3.2 or higher. See the thread https://lists.apache.org/thread/yov8xsggo3g2qr2p1rrr2xtps25wkbvj for more details. On Sat, Jan 29, 2022 at 3:26 PM

Re: [ANNOUNCE] Apache Spark 3.2.0

/spark/spark-3.2.0/spark-3.2.0-bin-hadoop3.3.tgz > > FYI, unable to download from this location. > Also, I don’t see Hadoop 3.3 version in the dist > > > On Oct 19, 2021, at 9:39 AM, Bode, Meikel, NMA-CFD < > meikel.b...@bertelsmann.de> wrote: > >  > > Man

[ANNOUNCE] Apache Spark 3.2.0

Hi all, Apache Spark 3.2.0 is the third release of the 3.x line. With tremendous contribution from the open-source community, this release managed to resolve in excess of 1,700 Jira tickets. We'd like to thank our contributors and users for their contributions and early feedback to this release.

Re: spark 3.2 release date

browse/SPARK-36619 <https://issues.apache.org/jira/browse/SPARK-36619> is resolved. Gengliang Wang > On Aug 31, 2021, at 12:06 PM, infa elance wrote: > > What is the expected ballpark release date of spark 3.2 ? > > Thanks and Regards, > Ajay.

Re: [ANNOUNCE] Announcing Apache Spark 3.0.1

Congrats! Thanks for the work, Ruifeng! On Fri, Sep 11, 2020 at 9:51 PM Takeshi Yamamuro wrote: > Congrats and thanks, Ruifeng! > > > On Fri, Sep 11, 2020 at 9:50 PM Dongjoon Hyun > wrote: > >> It's great. Thank you, Ruifeng! >> >> Bests, >> Dongjoon. >> >> On Fri, Sep 11, 2020 at 1:54 AM 郑瑞峰

Re: Inner join with the table itself

Hi Michael, You can use `Explain` to see how your query is optimized. https://docs.databricks.com/spark/latest/spark-sql/language-manual/explain.html I believe your query is an actual cross join, which is usually

Spark-avro 4.0.0 is released

The 4.0.0 release adds support for Spark 2.2. The published artifact is compatible with both Spark 2.1 and 2.2. New Features: - Support for Spark 2.2 (#242 ): resolve compatibility issue with datasource write API changes