Frag-shells cube based on hierarchical dimension encoding tree

Pre-computation of data cube can greatly improve the performance of OLAP (online analytical processing). There are a lot of effective pre-computation methods of data cube. But in practice, appropriate pre-computation method for the characteristics of data set plays a crucial role in improving the efficiency of data cube pre-computation. In view of the high-dimensional and hierarchical dimension of water census data characteristic, Frag-Shells cube based on hierarchical dimension encoding tree has been proposed in this paper. In order to improve the retrieval efficiency and reduce redundant information in hierarchical dimensions, we have proposed hierarchical dimension encoding tree (HDE-Tree) to index the hierarchical dimension in Frag-Shells cube. In order to increase the efficiency of cube construction, improved Frag-Shells cube calculation method has been used to compute the tuples of non-hierarchical dimension fragments. In order to compress the size of data cube, the TID-List compression method has been used to decrease the storage cost of inverted index in each tuple. Experiments show that the Frag-Shells cube based on hierarchical dimension encoding tree can reduce the construction time and storage cost of data cube which has high-dimensional and dimensions hierarchical figures.