中文摘要：

为解决高维聚集海量数据的存储与查询问题，通过分段共享数据立方体技术，将高维数据立方体划分成若干个低维数据立方体，并利用并行处理技术来创建这些分割的分段共享数据立方体及其聚集数据立方体，以实现高维数据立方体的并行创建和增量更新维护。理论分析与实验结果都表明，相对于以往的完全数据立方体创建和部分数据立方体创建等方法，基于分段共享数据立方体方法的性能有显著的提高。

英文摘要：

For the cube with d dimensions, it can generate 2d cuboids. But in a high--dimensional cube, it might not be practical to build all these cuboids. To deal with this problem, a novel approach for Online Analytical Processing （OLAP） in high--dimensional datasets by partitioning the high dimensional cube into some low--dimensional shell segment mini--Cubes was proposed. OLAP queries were computed online by dynamically constructing cuboids from these shell segment mini--cubes through the parallel and distributed processing system. With this design, for high --dimensional OLAP, the total space that needs to store such shell segment mini--cubes was negligible in comparison with a high--dimensional cube. The methods of shell mini--cube was compared to other existed ones such as full cube and partial cube by experiment. The analytical and experimental results showed that the algorithms of segment mini--cubes proposed were more efficient than the other existing ones.