一种数据立方高效索引机制——CuboidTree

An efficient indexing mechanism for data cube-CuboidTree

提出了一种高效的数据立方索引机制CuboidTree ,利用Z Order编码以保持同一数据小方内立方元组之间的多维空间邻近性 ,将数据立方查询归结为针对其中某个特定数据小方的查询 ,从而将同一数据小方中的立方元组聚簇在一起以加速响应数据立方查询 .对模拟数据和真实数据进行的实验表明 ,CuboidTree不仅可以明显地提高数据立方范围查询的性能 ,而且节省了存储空间 。

A new efficient indexing mechanism for data cube named CuboidTree was proposed. Z Order was used to preserve multidimensional spatial proximity of those cube tuples in a cuboid. Cube query came down to the query against a cubiod of that cube, and the query response by clustering those cube tuples of the same cubiod was speeded up. Performance studies were conducted by using both synthetic and real world data. It proved that CuboidTree could speed up query processing and reduce storage overhead. Thanks to it, the performance improvement on cube query will be more effective with the number of cube dimensions increasing.