Apache Kylin™ is an open source Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop supporting extremely large datasets, originally contributed from eBay Inc.
Apache Kylin™ lets you query massive dataset at sub-second latency in 3 steps.
- Identify a Star Schema on Hadoop.
- Build Cube from the identified tables.
- Query with ANSI-SQL and get results in sub-second, via ODBC, JDBC or RESTful API.
WHAT IS KYLIN?
– Extremely Fast OLAP Engine at Scale:
– ANSI SQL Interface on Hadoop:
– Interactive Query Capability:
– MOLAP Cube:
– Seamless Integration with BI Tools:
– Other Highlights:
– Compression and Encoding Support
– Incremental Refresh of Cubes
– Leverage HBase Coprocessor for query latency
– Both approximate and precise Query Capabilities for Distinct Count
– Approximate Top-N Query Capability
– Easy Web interface to manage, build, monitor and query cubes
– Security capability to set ACL at Cube/Project Level
– Support LDAP and SAML Integration
Apache Kylin v2.2.0 was released. This is a major release after 2.1, with over 70 bug fixes and improvements:
- [KYLIN-2703] – Manage ACL through Apache Ranger
- [KYLIN-2752] – Make HTable name prefix configurable
- [KYLIN-2761] – Table Level ACL
- [KYLIN-2775] – Streaming Cube Sample
- [KYLIN-2535] – Use ResourceStore to manage ACL files
- [KYLIN-2604] – Use global dict as the default encoding for precise distinct count in web
- [KYLIN-2606] – Only return counter for precise count_distinct if query is exactAggregate
- [KYLIN-1794] – Enable job list even some job metadata parsing failed
- [KYLIN-2600] – Incorrectly set the range start when filtering by the minimum value
- [KYLIN-2705] – Allow removing model’s “partition_date_column” on web