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Issue No.01 - January/February (2003 vol.15)
pp: 211-231
<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.
Nikos Mamoulis, Dimitris Papadias, "Slot Index Spatial Join", IEEE Transactions on Knowledge & Data Engineering, vol.15, no. 1, pp. 211-231, January/February 2003, doi:10.1109/TKDE.2003.1161591
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