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Implementing Real Time OLAP with MDDC (MultiDimensional Dynamic Clustering

Implementing Real Time OLAP with MDDC (MultiDimensional Dynamic Clustering
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Author(s): Michael W. Martin (North Carolina State University, USA) and Rada Chirkova (North Carolina State University, USA)
Copyright: 2006
Pages: 2
Source title: Emerging Trends and Challenges in Information Technology Management
Source Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-59904-019-6.ch178
ISBN13: 9781616921286
EISBN13: 9781466665361

Abstract

Data warehouse applications increasingly must update and maintain data in real time while simultaneously executing efficient OLAP (Online Analytical Processing) queries. The size and corresponding performance challenges of these data warehouses are growing at a staggering rate. This paper introduces, MDDC, a new technique that supports efficient OLAP queries without the extensive use of materialized views or secondary indexes. This technique is dynamic and does not require data reorganization. This is especially important for real-time data warehouses that must continually update data without downtime to reorganize data structures. This technique is similar to MHC (Multidimensional Hierarchical Clustering) but provides better symmetry and is completely dynamic. MDDC could utilize any number of host data structures including B-trees.

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