层次前缀立方的快速计算

PrefixCube was proposed to be an efficient cube structure by augmenting BU-BST Condensing with intra-cuboid prefix-sharing. PrefixCube not only has got efficient cube compression ratio but also has made a good compromise among cube compression, restoring and updating costs, and query characteristics. However, it does not directly support dimension hierarchies, on which rollup and drilldown queries quite naturally arise in OLAP. In this paper we extend the PrefixCube architecture for incorporating hierarchical data cubes, i.e. cubes with hierarchical dimensions, and hence get HierPrefixCube. We show that HierPrefixCube retains the advantages on computation and organization of PrefixCube while being able to directly and sufficiently support aggregate queries on levels of dimension hierarchy.