Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/2275

Range aggregate processing in spatial databases

Authors Tao, Y
Papadias, D
Issue Date 2004
Source IEEE transactions on knowledge and data engineering, v. 16, (12), 2004, DEC, p. 1555-1570
Summary A range aggregate query returns summarized information about the points falling in a hyper-rectangle (e.g., the total number of these points instead of their concrete ids). This paper studies spatial indexes that solve such queries efficiently and proposes the aggregate Point-tree (aP-tree), which achieves logarithmic cost to the data set cardinality ( independently of the query size) for two-dimensional data. The aP-tree requires only small modifications to the popular multiversion structural framework and, thus, can be implemented and applied easily in practice. We also present models that accurately predict the space consumption and query cost of the aP-tree and are therefore suitable for query optimization. Extensive experiments confirm that the proposed methods are efficient and practical.
Subjects
ISSN 1041-4347
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Language English
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