Multi-resolution Algorithms for Building Spatial Histograms

Liu, Q., Yuan, Y. and Lin, X.

    Selectivity estimation of queries not only provides useful information to the query processing optimization but also may give users a preview of processing results. In this paper, we investigate the problem of selectivity estimation in the context of a spatial dataset. Specifically, we focus on the calculation of four relations, contains, contained, overlap and disjoint, between data objects and a query rectangle using Euler-histograms. We first provide a multi-resolution algorithm which can lead to the exact solutions but at the cost of storage space. To conform to a given storage space, we also provide an approximate algorithm based on a hybrid multi-resolution paradigm. Our experiments suggest that our algorithms greatly out-perform the existing techniques.
Cite as: Liu, Q., Yuan, Y. and Lin, X. (2003). Multi-resolution Algorithms for Building Spatial Histograms. In Proc. Fourteenth Australasian Database Conference (ADC2003), Adelaide, Australia. CRPIT, 17. Schewe, K.-D. and Zhou, X., Eds. ACS. 145-151.
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