Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/41635
Title: Multi-point queries in large spatial databases
Authors: Hoong, K.N.
Hon, W.L. 
Keywords: Algorithm
Query processing
Spatial range queries
Issue Date: 2007
Source: Hoong, K.N.,Hon, W.L. (2007). Multi-point queries in large spatial databases. Proceedings of the 3rd IASTED International Conference on Advances in Computer Science and Technology, ACST 2007 : 408-413. ScholarBank@NUS Repository.
Abstract: This paper revisits multi-point range query (MPRQ) for 2-d spatial database. In a previous paper, we introduced an efficient algorithm, PRQ, to answer the query for the case where database resides in main memory. This paper extends the algorithm to the general case in which the database is large and has to reside on disk. The MPRQ is defined as: Given a set of query points, P = {p1, p2, ..., pn}, and a search distance d, report all points in the spatial database that are within a distance d of some point pi in P. The simple method of performing Repeated Range Query (RRQ), i.e. the standard range query for each query point pi (1 £ i £ n) and combining the results is inefficient as it involves multiple searches on the database. We show that PRQ-Disk still achieve better results and outperform RRQ-Disk, as in the case of main memory. Extensive experiments using various real-life datasets, different Rtree variants (including bulk-loaded ones), over different query paths P, search distances d, and LRU buffering show that PRQ-Disk outperforms RRQ-Disk in terms of both query time and I/Os.
Source Title: Proceedings of the 3rd IASTED International Conference on Advances in Computer Science and Technology, ACST 2007
URI: http://scholarbank.nus.edu.sg/handle/10635/41635
ISBN: 9780889866560
Appears in Collections:Staff Publications

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