[ANNOUNCE] Apache Hive 3.1.1 Released
The Apache Hive team is proud to announce the release of Apache Hive version 3.1.1. 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, among others: * 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, Apache Tez and Apache Spark frameworks. For Hive release details and downloads, please visit: https://hive.apache.org/downloads.html Hive 3.1.1 Release Notes are available here: https://issues.apache.org/jira/secure/ReleaseNote.jspa?version=12344240&styleName=Text&projectId=12310843 We would like to thank the many contributors who made this release possible. Regards, The Apache Hive Team
Announce: MR3 0.4 released
I am pleased to announce the release of MR3 0.4. A new feature of MR3 0.4 is its support for Hive 3.1.0 and Hadoop 3.1.0. As with previous releases, I have published a blog article that evaluates the performance of popular SQL-on-Hadoop systems. It compares the following systems using both sequential tests and concurrency tests: 1. Hive-LLAP included in HDP 2.6.4 1'. Hive-LLAP included in HDP 3.0.1 2. Presto 0.203e (with cost-based optimization enabled) 2'. Presto 0.208e (with cost-based optimization enabled) 3. SparkSQL 2.2.0 included in HDP 2.6.4 3'. SparkSQL 2.3.1 included in HDP 3.0.1 4. Hive 3.1.0 running on top of Tez 4'. Hive on Tez included in HDP 3.0.1 5. Hive 3.1.0 running on top of MR3 0.4 6. Hive 2.3.3 running on top of MR3 0.4 I use three clusters (11 nodes, 21 nodes, 42 nodes) in the experiment. The blog article can be found at: https://mr3.postech.ac.kr/blog/2018/10/31/performance-evaluation-0.4/ You can download MR3 0.4 at: https://mr3.postech.ac.kr/download/home/ --- Sungwoo Park
