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Range Aggregate Processing in Spatial Databases
December 2004 (vol. 16 no. 12)
pp. 1555-1570
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.

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Index Terms:
Database, spatial database, range queries, aggregation.
Yufei Tao, Dimitris Papadias, "Range Aggregate Processing in Spatial Databases," IEEE Transactions on Knowledge and Data Engineering, vol. 16, no. 12, pp. 1555-1570, Dec. 2004, doi:10.1109/TKDE.2004.93
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