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

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Overview This demo presents 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. The cgmOLAP demo system will be running on two 32 processor Linux-based clusters, one located in Canada the other in Australia.

Further White Paper Details
Publisher	Concordia University	File Format	PDF
Date Published	March 2005
Format	White Papers
Topics	Processors, Application Servers, Parallel Processing

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