Abstract
Aiming at the on-line analytical processing technology, this paper proposes a parallel compressed data cube algorithm based on Hadoop architecture. The algorithm divides a single data cube into several independent sub-compressed data cubes, and then uses Hadoop architecture to realize the parallel construction and query of the entire data cube. Experiments show that the parallel compressed data cube algorithm combines the parallelism and high scalability of the Hadoop architecture on the one hand, and on the other hand, it can realize faster query operation on data cube by means of a self-indexing of the compressed data cube. So it has good research value and practical application significance.
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