关键词: 联机分析处理, 外壳片段立方体, Map/Reduce技术, 并行计算

Abstract: In the high-dimensional and dimension hierarchical big data materializing, this paper proposes an efficient parallel shell fragments cube construction algorithm using Map/Reduce framework. The algorithm achieves parallel building and querying of shell fragments cube. For each data partition, map process of the construction algorithm calculates all possible data unit or prefixB encoding; Reduce process aggregates to calculate the ultimate shell fragments and measure index table. Experiments show that the parallel shell fragments cube algorithm not only combines the parallelism and scalability of Map/Reduce framework, but also combines the compression strategy and inverted index structure of shell fragments cube. The parallel shell fragments cube algorithm can effectively avoid the explosion of data volumes while materializing high-dimensional data, and provides the quick build and query operations.

Key words: On-Line Analysis Processing（OLAP）, shell fragments cube, Map/Reduce, parallel computation