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International Symposium on Spatial and Temporal Databases

SSTD 2001: Advances in Spatial and Temporal Databases pp 175–193Cite as

Wavelet-Based Cost Estimation for Spatial Queries

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2121))

Abstract

Query cost estimation is an important and well-studied problem in relational database systems. In this paper we study the cost estimation problem in the context of spatial database systems.

We introduce a new method that provides accurate cost estimation for spatial selections, or window queries, by building wavelet-based histograms for spatial data. Our method is based upon two techniques: (a) A representation transformation in which geometric objects are represented by points in higher-dimensional space and window queries correspond to semi-infinite range-sum queries, and (b) Multiresolution wavelet decomposition that provides a time-efficient and space-efficient approximation of the underlying distribution of the multidimensional point data, especially for semi-infinite range-sum queries. We also show for the first time how a wavelet decomposition of a dense multidimensional array derived from a sparse array through a partial-sum computation can still be computed efficiently using sparse techniques by doing the processing implicitly on the original data. Our method eliminates the drawbacks of the partition-based histogram methods in previous work, and even with very small space allocation it gives excellent cost estimation over a broad range of spatial data distributions and queries.

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Author information

Authors and Affiliations

  1. IBM T J. Watson Research Center, Hawthorne, NY, 10532

    Min Wang & Sriram Padmanabhan

  2. Dept. of Computer Science, Duke University, Durham, NC, 27708-0129

    Jeffrey Scott Vitter & Lipyeow Lim

Authors
  1. Min Wang
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  2. Jeffrey Scott Vitter
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  3. Lipyeow Lim
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  4. Sriram Padmanabhan
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Aalborg University, Fredrik Bajers Vej 7E, 9220, Aalborg Øst, Denmark

    Christian S. Jensen

  2. Praktische Informatik IV, FernUniversität Hagen, 58084, Hagen, Germany

    Markus Schneider

  3. Fachbereich Mathematik und Informatik, Philipps-Universität Marburg, 35032, Marburg, Germany

    Bernhard Seeger

  4. Department of Computer Science and Engineering, University of California, Riverside, CA, 92521, USA

    Vassilis J. Tsotras

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© 2001 Springer-Verlag Berlin Heidelberg

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Wang, M., Vitter, J.S., Lim, L., Padmanabhan, S. (2001). Wavelet-Based Cost Estimation for Spatial Queries. In: Jensen, C.S., Schneider, M., Seeger, B., Tsotras, V.J. (eds) Advances in Spatial and Temporal Databases. SSTD 2001. Lecture Notes in Computer Science, vol 2121. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47724-1_10

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  • DOI: https://doi.org/10.1007/3-540-47724-1_10

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42301-0

  • Online ISBN: 978-3-540-47724-2

  • eBook Packages: Springer Book Archive

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