HIGH-DIMENSIONAL HIERARCHICAL OLAP: A PREFIX– INDEX HIERARCHICAL CUBING APPROACH

The pre-computation of data cubes is critical for improving the response time of OLAP(online analytical processing) systems and accelerating data mining tasks in large data warehouses. However, as the sizes of data warehouses grow, the time it takes to perform this pre-computation becomes a significant performance bottleneck. In a high dimensional OLAP, it might not be practical to build all these cuboids and their indices. In this paper, we propose a multi-dimensional hierarchical cubing algorithm, Prefix-index hierarchical cubing, based on an extension of the previous minimal cubing approach. This method partitions the high dimensional data cube into low dimensional cube segments. Such an approach permits a significant reduction of CPU and I/O overhead. Experimental results show that the proposed method is significantly more efficient than other existing cubing methods