Abstract
MOLAP (multidimensional OLAP) systems are storing data as cubes in multidimensional arrays. Data cubes can be sparse, which slows down the performance of MOLAPs and requests useless additional data storage. Many compression algorithms have been introduced to deal with the sparsity of MOLAP data cubes. In this paper we present a new compression algorithm based on the bitmap compression technique. Instead of the linear structure used by the classical bitmap, we use a balanced tree structure to store the compressed data in order to reduce the search time. We demonstrate in this paper that our algorithm performs a search in the compressed structure in a logarithmic time which overcomes the linear time needed by classical bitmap compression methods. We finally show some empirical results in which our proposed algorithm has been tested over multiple datasets and compared to the classical bitmap algorithm.
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