Experimental evaluation demonstrates multi-stage algorithms improve spatial distance join processing speeds by up to tenfold, highlighting enhanced efficiency for online spatial queries.
A spatial distance join is a relatively new type of operation introduced for spatial and multimedia database applications. Additional requirements for ranking and stopping cardinality are often combined with the spatial distance join in on-line query processing or internet search environments. These requirements pose new challenges as well as opportunities for more efficient processing of spatial distance join queries. In this paper, we first present an efficient k -distance join algorithm that uses spatial indexes such as R-trees. Bi-directional node expansion and plane-sweeping techniques are used for fast pruning of distant pairs, and the plane-sweeping is further optimized by novel strategies for selecting a sweeping axis and direction. Furthermore, we propose adaptive multi-stage algorithms for k -distance join and incremental distance join operations. Our performance study shows that the proposed adaptive multi-stage algorithms outperform previous work by up to an order of magnitude for both k -distance join and incremental distance join queries, under various operational conditions.
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Shin et al. (2000) studied this question.
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