Optimal Multidimensional Query Processing Using Tree Striping

In this paper, we propose a new technique for multidimensional query processing which can be widely applied in database systems. Our new technique, called tree striping, generalizes the well-known inverted lists and multidimensional indexing approaches. A theoretical analysis of our generalized technique shows that both, inverted lists and multidimensional indexing approaches, are far from being optimal. A consequence of our analysis is that the use of a set of multidimensional indexes provides considerable improvements over one d-dimensional index (multidimensional indexing) or d one-dimensional indexes (inverted lists). The basic idea of tree striping is to use the optimal number k of lower-dimensional indexes determined by our theoretical analysis for efficient query processing. We confirm our theoretical results by an experimental evaluation on large amounts of real and synthetic data. The results show a speed-up of up to 310% over the multidimensional indexing approach and a speed-up factor of up to 123 (12,300%) over the inverted-lists approach.