|Apache Kylin Gets Table Level ACL Management|
|Written by Kay Ewbank|
|Tuesday, 21 November 2017|
There's an updated version of Apache Kylin, the "Extreme OLAP Engine for Big Data" with improvements including table-level ACL management.
Kylin is an open source distributed analytics engine designed to provide a SQL interface and multi-dimensional analysis (OLAP) on Apache. It was originally developed at eBay before becoming an Apache project.
The Kylin OLAP Engine is made up of a metadata engine, a query engine, a job engine and a storage engine. It also includes a REST Server to service client requests. The query engine is based on Apache Calcite.
Apache Kylin lets you query massive data sets in three steps:
Kylin currently offers integration capability with BI Tools inlcuding Tableau, PowerBI and Excel.
The main improvements to the new release are to ACL. You can now manage ACL through Apache Ranger, a framework to enable, monitor and manage data security across the Hadoop platform. It provides centralized security administration to manage all security related tasks in a central UI or using REST APIs, and supports fine grained authorization.
The ability to manage Kylin ACL through Ranger brings it into line with other elements of the Hadoop ecosystem, where Ranger can be used to manage HDFS, Yarn, Hive, and HBase.
Ranger can now control access rights for Kylin projects and cubes, and Kylin provides an abstract class and authorization interfaces for use by the Ranger plugin.
Table level ACL has also been added to control whether a user can query data from a table. The table level ACL is set at the project level. When an instance starts for the first time or upgrades from lower version, every user by default has access to all tables that have been loaded to the project, but it's now possible to modify the table level ACL.
A new Streaming Cube sample has also been added. This will generate the sample tables, model and cube for a Hive-based data source. It has been added because until now there has been no easy way to generate such a sample for a Kafka-based streaming cube.
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|Last Updated ( Tuesday, 21 November 2017 )|