Abstract
AbstractWhile there are several studies on cube storage for range queries and dynamic updates, very few works have been done on addressing parallel cube storage structure in share nothing environments to improve the query performance. In this paper, we investigate the approach of how to answer range sum queries in a share nothing ennvironment, and present an effective parallel hierarchical data cube storage structure (PHDC for short), which provides better load balancing for both range sum queries and updates. Analytical and experimental results show that PHDC have better load-balance and achieve optimum speed-up for a very high percentage of range queries on multidimensional data cube.KeywordsRange QueryData CubePartition PointDynamic UpdateMultidimensional CubeThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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