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cgmOLAP: Efficient Parallel Generation and Querying of Terabyte Size ROLAP Data Cubes

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Title cgmOLAP: Efficient Parallel Generation and Querying of Terabyte Size ROLAP Data Cubes
Author Chen, Y.; Rau-Chaplin, A.; Dehne, F.; Eavis, T.; Green, D.; Sithirasenan, Elankayer
Publication Title Proceedings of the 22nd International Conference on Data Engineering, 2006. ICDE '06.
Year Published 2006
Publisher IEEE
Abstract We present the cgmOLAP server, the first fully functional parallel OLAP system able to build data cubes at a rate of more than 1 Terabyte per hour. cgmOLAP incorporates a variety of novel approaches for the parallel computation of full cubes, partial cubes, and iceberg cubes as well as new parallel cube indexing schemes. The cgmOLAP system consists of an application interface, a parallel query engine, a parallel cube materialization engine, meta data and cost model repositories, and shared server components that provide uniform management of I/O, memory, communications, and disk resources.
Peer Reviewed Yes
Published Yes
Publisher URI http://ieeexplore.ieee.org/servlet/opac?punumber=10757
Alternative URI http://dx.doi.org/10.1109/ICDE.2006.32
Conference name 22nd International Conference on Data Engineering, 2006. ICDE '06.
Location Atlanta, Georgia, USA
Date From 2006-04-03
Date To 2006-04-07
Date Accessioned 2009-11-12
Date Available 2009-12-23T07:13:46Z
Language en_AU
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject PRE2009-Cross discipline
Publication Type Conference Publications (Full Written Paper - Refereed)
Publication Type Code e1a

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