Rating is available when the video has been rented.
This feature is not available right now. Please try again later.
Published on Jul 27, 2016
Hongbin Ma and Luke Han (Kyligence) / Rohit Jain (Esgyn)
Part 1: Apache Kylin is an open source distributed analytics engine that provides a SQL interface and multi-dimensional analysis on Hadoop supporting extremely large datasets. In the forthcoming Kylin release, we optimized query performance by exploring the potentials of parallel storage on top of HBase. This talk explains how that work was done.
Part 2: Customers are looking for one database engine to address all their varied needs--from transactional to analytical workloads--against structured, semi-structured, and unstructured data (Gartner’s term Hybrid Transactional/Analytical Processing, or HTAP, perhaps comes closest to describing this nirvana.) But can it be achieved? The motivation of this talk is to establish a framework for assessing the maturity and capabilities of query engines on Apache Hadoop ecosystem storage engines such as HBase in meeting these diverse needs.