文章基本信息
- 标题：Business Analytics in (a) Blink
- 本地全文：下载
- 作者：Ronald Barber. Peter Bendel. Marco Czech.. Oliver Draese. Frederick Ho# Namik Hrle. Stratos Idreos§. Min-Soo Kim.. Oliver Koeth. Jae-Gil Lee.. Tianchao Tim Li. Guy Lohman. Konstantinos Morfonios△. Rene Mueller. Keshava Murthy# Ippokratis Pandis. Lin Qiao.. Vijayshankar Raman. Richard Sidle. Knut Stolze. Sandor Szabo.
- 期刊名称：Bulletin of the Technical Committee on Data Engineering
- 出版年度：2012
- 卷号：35
- 期号：01
- 出版社：IEEE Computer Society
- 摘要：The Blink project¡¯s ambitious goal is to answer all Business Intelligence (BI) queries in mere seconds, regardless of the database size, with an extremely low total cost of ownership. Blink is a new DBMS aimed primarily at read-mostly BI query processing that exploits scale-out of commodity multi-core processors and cheap DRAM to retain a (copy of a) data mart completely in main memory. Additionally, it exploits proprietary compression technology and cache-conscious algorithms that reduce memory bandwidth consumption and allow most SQL query processing to be performed on the compressed data. Blink always scans (portions of) the data mart in parallel on all nodes, without using any indexes or materialized views, and without any query optimizer to choose among them. The Blink technology has thus far been incorporated into two IBM accelerator products generally available since March 2011. We are now working on the next generation of Blink, which will significantly expand the ¡°sweet spot¡± of the Blink technology to much larger, disk-based warehouses and allow Blink to ¡°own¡± the data, rather than copies of it.
