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



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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
> <https://issues.apache.org/jira/secure/ReleaseNote.jspa?version=12334886&styleName=Text&projectId=12310843>
>
> We would like to thank the many contributors who made this release
> possible.
>
> Regards,
>
> The Apache Hive Team
>
>
>

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