Re: JDK11 Support in Apache Spark
That's Awesome !!! Thanks to everyone that made this possible :cheers: Hichame From: cloud0...@gmail.com Sent: August 25, 2019 10:43 PM To: lix...@databricks.com Cc: felixcheun...@hotmail.com; ravishankar.n...@gmail.com; dongjoon.h...@gmail.com; d...@spark.apache.org; user@spark.apache.org Subject: Re: JDK11 Support in Apache Spark Great work! On Sun, Aug 25, 2019 at 6:03 AM Xiao Li mailto:lix...@databricks.com>> 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 mailto:felixcheun...@hotmail.com>> wrote: That’s great! From: ☼ R Nair mailto:ravishankar.n...@gmail.com>> Sent: Saturday, August 24, 2019 10:57:31 AM To: Dongjoon Hyun mailto:dongjoon.h...@gmail.com>> Cc: d...@spark.apache.org<mailto:d...@spark.apache.org> mailto:d...@spark.apache.org>>; user @spark/'user @spark'/spark users/user@spark mailto:user@spark.apache.org>> Subject: Re: JDK11 Support in Apache Spark Finally!!! Congrats On Sat, Aug 24, 2019, 11:11 AM Dongjoon Hyun mailto:dongjoon.h...@gmail.com>> 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. -- [Databricks Summit - Watch the talks]<https://databricks.com/sparkaisummit/north-america>
Re: JDK11 Support in Apache Spark
Great work! On Sun, Aug 25, 2019 at 6:03 AM Xiao Li 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 > wrote: > >> That’s great! >> >> -- >> *From:* ☼ R Nair >> *Sent:* Saturday, August 24, 2019 10:57:31 AM >> *To:* Dongjoon Hyun >> *Cc:* d...@spark.apache.org ; user @spark/'user >> @spark'/spark users/user@spark >> *Subject:* Re: JDK11 Support in Apache Spark >> >> Finally!!! Congrats >> >> On Sat, Aug 24, 2019, 11:11 AM Dongjoon Hyun >> 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> >
Re: JDK11 Support in Apache Spark
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 wrote: > That’s great! > > -- > *From:* ☼ R Nair > *Sent:* Saturday, August 24, 2019 10:57:31 AM > *To:* Dongjoon Hyun > *Cc:* d...@spark.apache.org ; user @spark/'user > @spark'/spark users/user@spark > *Subject:* Re: JDK11 Support in Apache Spark > > Finally!!! Congrats > > On Sat, Aug 24, 2019, 11:11 AM Dongjoon Hyun > 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>
Re: JDK11 Support in Apache Spark
That’s great! From: ☼ R Nair Sent: Saturday, August 24, 2019 10:57:31 AM To: Dongjoon Hyun Cc: d...@spark.apache.org ; user @spark/'user @spark'/spark users/user@spark Subject: Re: JDK11 Support in Apache Spark Finally!!! Congrats On Sat, Aug 24, 2019, 11:11 AM Dongjoon Hyun mailto:dongjoon.h...@gmail.com>> 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.
Re: JDK11 Support in Apache Spark
Finally!!! Congrats On Sat, Aug 24, 2019, 11:11 AM Dongjoon Hyun 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. >
Re: JDK11 Support in Apache Spark
Congratulations on the great work! Sincerely, DB Tsai -- Web: https://www.dbtsai.com PGP Key ID: 42E5B25A8F7A82C1 On Sat, Aug 24, 2019 at 8:11 AM Dongjoon Hyun 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. - To unsubscribe e-mail: user-unsubscr...@spark.apache.org
JDK11 Support in Apache Spark
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.
