Great work! On Sun, Aug 25, 2019 at 6:03 AM Xiao Li <[email protected]> wrote:
> Thank you for your contributions! This is a great feature for Spark > 3.0! We finally achieve it! > > Xiao > > On Sat, Aug 24, 2019 at 12:18 PM Felix Cheung <[email protected]> > wrote: > >> That’s great! >> >> ------------------------------ >> *From:* ☼ R Nair <[email protected]> >> *Sent:* Saturday, August 24, 2019 10:57:31 AM >> *To:* Dongjoon Hyun <[email protected]> >> *Cc:* [email protected] <[email protected]>; user @spark/'user >> @spark'/spark users/user@spark <[email protected]> >> *Subject:* Re: JDK11 Support in Apache Spark >> >> Finally!!! Congrats >> >> On Sat, Aug 24, 2019, 11:11 AM Dongjoon Hyun <[email protected]> >> wrote: >> >>> Hi, All. >>> >>> Thanks to your many many contributions, >>> Apache Spark master branch starts to pass on JDK11 as of today. >>> (with `hadoop-3.2` profile: Apache Hadoop 3.2 and Hive 2.3.6) >>> >>> >>> https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Test%20(Dashboard)/job/spark-master-test-maven-hadoop-3.2-jdk-11/326/ >>> (JDK11 is used for building and testing.) >>> >>> We already verified all UTs (including PySpark/SparkR) before. >>> >>> Please feel free to use JDK11 in order to build/test/run `master` branch >>> and >>> share your experience including any issues. It will help Apache Spark >>> 3.0.0 release. >>> >>> For the follow-ups, please follow >>> https://issues.apache.org/jira/browse/SPARK-24417 . >>> The next step is `how to support JDK8/JDK11 together in a single >>> artifact`. >>> >>> Bests, >>> Dongjoon. >>> >> > > -- > [image: Databricks Summit - Watch the talks] > <https://databricks.com/sparkaisummit/north-america> >
