Issue No. 01 - January/February (2003 vol. 15)
<p><b>Abstract</b>—Efficient processing of spatial joins is very important due to their high cost and frequent application in spatial databases and other areas involving multidimensional data. This paper proposes <it>slot index spatial join</it> (SISJ), an algorithm that joins a nonindexed data set with one indexed by an R-tree. We explore two optimization techniques that reduce the space requirements and the computational cost of SISJ and we compare it, analytically and experimentally, with other spatial join methods for two cases: 1) when the nonindexed input is read from disk and 2) when it is an intermediate result of a preceding database operator in a complex query plan. The importance of buffer splitting between consecutive join operators is also demonstrated through a two-join case study and a method that estimates the optimal splitting is proposed. Our evaluation shows that SISJ outperforms alternative methods in most cases and is suitable for limited memory conditions.</p>
Spatial databases, query processing, join processing, database index, spatial index, buffer management.
D. Papadias and N. Mamoulis, "Slot Index Spatial Join," in IEEE Transactions on Knowledge & Data Engineering, vol. 15, no. , pp. 211-231, 2003.