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Buffer Queries
July/August 2003 (vol. 15 no. 4)
pp. 895-910

Abstract—A class of commonly asked queries in a spatial database is known as buffer queries. An example of such a query is to “find house-power line pairs that are within 50 meters of each other.” A buffer query involves two spatial data sets and a distance d. The answer to this query are pairs of objects, one from each input set, that are within distance d of each other. Given nonpoint spatial objects, evaluation of buffer queries could be a costly operation, even when the numbers of objects in the input data sets are relatively small. This paper addresses the problem of how to evaluate this class of queries efficiently. A fundamental problem with buffer query evaluation is to find an efficient algorithm for solving the minimum distance (minDist) problem for lines and regions. An efficient minDist algorithm, which only requires a subsequence of segments from each object to be examined, is derived. Finding a fast minDist algorithm is the first step in evaluating a buffer query efficiently. It is observed that many, and sometimes even most, candidates can be proven in the answer without resorting to the relatively expensive minDist operation. A candidate is first evaluated with a least expensive technique—called 0-object filtering. If it fails, a more costly operation, called 1-object filtering, is applied. Finally, if both filterings fail, the most expensive minDist algorithm is invoked. To show the effectiveness of the these techniques, they are incorporated into the well-known tree join algorithm and tested with real-life as well as artificial data sets. Extensive experiments show that the proposed algorithm outperforms existing techniques by a wide margin in both execution time as well as IO accesses. More importantly, the performance gain improves drastically with the increase of distance values.

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Index Terms:
Buffer query, distance-related query, minimum distance, spatial query evaluation, filtering, refinement, spatial join.
Edward P.F. Chan, "Buffer Queries," IEEE Transactions on Knowledge and Data Engineering, vol. 15, no. 4, pp. 895-910, July-Aug. 2003, doi:10.1109/TKDE.2003.1209007
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