Abstract:

Although the closed cube is a high-efficiency and important technology for data cube compression, there is no research on its parallel algorithm at present. In this paper, a novel parallel approach combining the C-Cubing technology with the MapReduce framework is proposed. In this approach, the representative tuple and closed mask of each data cell for every data block are computed in the Map process, and the closed cells are obtained by the aggregation in the Reduce process. Experimental results show that the proposed approach greatly increases the computation speed of closed cubes in large-scale datasets.

Key words: data warehouse, online analytical processing, parallel algorithm, closed cube, MapReduce technology