Thanks Shaofeng. I think this is one of the most remarkable releases since 2.0. A few highlights: [KYLIN-3521] - Enable Cube Planner by default [KYLIN-2565] - Support Hadoop 3.0 [KYLIN-3033] - Support HBase 2.0 [KYLIN-3418] - User interface for hybrid model [KYLIN-3427] - Convert to HFile in Spark [KYLIN-3441] - Merge cube segments in Spark [KYLIN-3442] - Fact distinct columns in Spark [KYLIN-3453] - Improve cube size estimation for TOPN, COUNT DISTINCT and a lot of bug fixes and improvement on stability.
With Warm regards Billy Liu ShaoFeng Shi <[email protected]> 于2018年9月19日周三 上午8:31写道： > > The Apache Kylin team is pleased to announce the immediate availability of > the 2.5.0 release. > > This is a major release after 2.4, with more than 100 enhancements and bug > fixes. All of the changes in this release can be found in: > https://kylin.apache.org/docs/release_notes.html > > You can download the source release and binary packages from Apache Kylin's > download page: https://kylin.apache.org/download/ > > Apache Kylin is an open source Distributed Analytics Engine designed to > provide SQL interface and multi-dimensional analysis (OLAP) on Apache Hadoop, > supporting extremely large datasets. > > Apache Kylin lets you query massive dataset at sub-second latency in 3 steps: > 1. Identify a star schema or snowflake schema data set on Hadoop. > 2. Build Cube on Hadoop. > 3. Query data with ANSI-SQL and get results in sub-second, via ODBC, JDBC or > RESTful API. > > Thanks to everyone who has contributed to the 2.5.0 release. > > We welcome your help and feedback. For more information on how to > report problems, and to get involved, visit the project website at > https://kylin.apache.org/ > > -- > Best regards, > > Shaofeng Shi 史少锋 >
