| Adaptive multi-stage distance join processing |
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International Conference on Management of Data
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Proceedings of the 2000 ACM SIGMOD international conference on Management of data
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Dallas, Texas, United States
Pages: 343 - 354
Year of Publication: 2000
ISBN:1-58113-217-4
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Authors
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Hyoseop Shin
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School of Computer Engr, Seoul National University, Seoul, Korea
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Bongki Moon
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Dept. of Computer Science, University of Arizona, Tucson, AZ
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Sukho Lee
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School of Computer Engr, Seoul National University, Seoul, Korea
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Downloads (6 Weeks): 2, Downloads (12 Months): 34, Citation Count: 11
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ABSTRACT
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.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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