基于维层次的语义Cube存储与增量更新技术研究

Research on Storage and Incremental Update Technology of Semantic Cube Based on Dimension Hierarchy

利用维的层次性为每一个维建立一个索引,同时保存相应的层次信息和预聚集数据,提出了基于维层次的语义Cube。在进行数据更新时,使用更新前后的差值自下而上对受到更新单元影响的祖先节点进行增量更新,在进行模式更新时,无须重构Cube,即可实现增量更新。由于其存储结构的灵活性,在高效完成增量更新的同时实现了Cube上进行上探、下钻等语义操作。理论分析和实验结果均表明,提出的基于维层次的语义Cube与传统Cube相比,性能显著提高。

By using the dimension technique on the cube, the paper proposed the highly performance DHSC （Semantic Cube based on Dimension Hierarchy）. DHSC stores the pre-aggregate data and dimension hierarchy information through the index of each dimensions, thus, it could optimize the query efficiency and update efficiency, and also support the cube semantic operation such as roll up and drill down. The DHSC could incrementally update the all affected ancestor notes while updating the data cell by insertion and deletion in it, and also incrementally model update, As a result, this algorithm could greatly reduce the update time. Author had compared the performances of DHSC with the previous ones （ e, g. SDDC）, The analytical and experimental results show that the performances of DHSC proposed are more efficient.