Abstract
Determining the best execution plan for a spatial query requires tools for measuring (more precisely, estimating) the number of (spatial) data items that are retrieved by a query as well as its cost, in terms of I/O and CPU effort. As in traditional databases, spatial query optimization tools include cost-based models, exploiting analytical formulae for selectivity and cost of a query, and histogram-based techniques.
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© 2006 Springer-Verlag London Limited
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Manolopoulos, Y., Nanopoulos, A., Papadopoulos, A.N., Theodoridis, Y. (2006). Query Optimization Issues. In: R-Trees: Theory and Applications. Advanced Information and Knowledge Processing. Springer, London. https://doi.org/10.1007/978-1-84628-293-5_8
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DOI: https://doi.org/10.1007/978-1-84628-293-5_8
Publisher Name: Springer, London
Print ISBN: 978-1-85233-977-7
Online ISBN: 978-1-84628-293-5
eBook Packages: Computer ScienceComputer Science (R0)