Thanks Sergey, Congratulations.
May I add that Hive 0.14 and above can also deploy Spark as its executions engine and with Spark on Hive on Spark execution engine you have a winning combination. BTW we are just discussing the merits of TEZ + LLAP versus Spark as the execution engine for Spark. With Hive on Spark vs Hive on MapReduce the performance gains are order of magnitude. HTH Dr Mich Talebzadeh LinkedIn * https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>* http://talebzadehmich.wordpress.com On 31 May 2016 at 21:39, Sergey Shelukhin <ser...@apache.org> wrote: > The Apache Hive team is proud to announce the the release of Apache Hive > version 2.0.1. > > The Apache Hive (TM) data warehouse software facilitates querying and > managing large datasets residing in distributed storage. Built on top of > Apache Hadoop (TM), it provides: > > * Tools to enable easy data extract/transform/load (ETL) > > * A mechanism to impose structure on a variety of data formats > > * Access to files stored either directly in Apache HDFS (TM) or in other > data storage systems such as Apache HBase (TM) > > * Query execution via Apache Hadoop MapReduce and Apache Tez frameworks. > > For Hive release details and downloads, please visit: > https://hive.apache.org/downloads.html > > Hive 2.0.1 Release Notes are available here: > https://issues.apache.org/jira/secure/ReleaseNote.jspa?version=12334886&sty > leName=Text&projectId=12310843 > > We would like to thank the many contributors who made this release > possible. > > Regards, > > The Apache Hive Team > > >
