Selectivity Estimation for Spatial Joins with Geometric Selections

  • Chengyu Sun
  • Divyakant Agrawal
  • Amr El Abbadi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2287)


Spatial join is an expensive operation that is commonly used in spatial database systems. In order to generate efficient query plans for the queries involving spatial join operations, it is crucial to obtain accurate selectivity estimates for these operations. In this paper we introduce a framework for estimating the selectivity of spatial joins constrained by geometric selections. The center piece of the framework is Euler Histogram, which decomposes the estimation process into estimations on vertices, edges and faces. Based on the characteristics of different datasets, different probabilistic models can be plugged into the framework to provide better estimation results. To demonstrate the effectiveness of this framework, we implement it by incorporating two existing probabilistic models, and compare the performance with the Geometric Histogram [1] and the algorithm recently proposed by Mamoulis and Papadias [2].


Geographical Information System Grid Granularity Area Selectivity Spatial Database Spatial Object 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Ning An, Zhen-Yu Yang, and Anand Sivasubramaniam. Selectivity estimation for spatial joins. In ICDE 2001, Proceedings of the 17th International Conference on Data Engineering, pages 368–375, April 2001.Google Scholar
  2. 2.
    Nikos Mamoulis and Dimitris Papadias. Selectivity estimation of complex spatial queries. In SSTD’01, Proceedings of the 7th International Symposium on Spatial and Temporal Databases, July 2001.Google Scholar
  3. 3.
    Philippe Rigaux, Michel Scholl, and Agnès Voisard. Spatial Databases with Applications to GIS, chapter 1.3.1, page 14. Morgan Kaufmann Publishers, 2001.Google Scholar
  4. 4.
    R. Beigel and Egemen Tanin. The geometry of browsing. In Proceedings of the Latin American Symposium on Theoretical Informatics, 1998, Brazil, pages 331–340, 1998.Google Scholar
  5. 5.
    Chengyu Sun, Divyakant Agrawal, and Amr El Abbadi. Exploring spatial datasets with histograms. In ICDE 2002, Proceedings of the 18th International Conference on Data Engineering, Feburary 2002.Google Scholar
  6. 6.
    Christos Faloutsos, Bernhard Seeger, Agma J. M. Traina, and Caetano Traina Jr. Spatial join selectivity using power laws. SIGMOD Record, 29(2):177–188, 2000.CrossRefGoogle Scholar
  7. 7.
    Chengyu Sun, Divyakant Agrawal, and Amr El Abbadi. Selectivity estimation for spatial joins with geometric selections (extended version). Technical report, Computer Science Department, University of California, Santa Barbara, 2002.
  8. 10.
    Larry C. Munn and Christopher S. Arneson. Draft 1:100,000-scale digital soils map of wyoming. Technical report, University of Wyoming Agricultural Experiment Station, 1999.Google Scholar
  9. 11.
    Michael Stonebraker, James Frew, Kenn Gardels, and Jeff Meredith. The sequoia 2000 benchmark. In Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, Washington, D.C., May 26–28, 1993, pages 2–11, 1993.Google Scholar
  10. 12.
    Wael M. Badawy and Walid G. Aref. On local heuristics to speed up polygonpolygon intersection tests. In ACM-GIS’ 99, Proceedings of the 7th International Symposium on Advances in Geographic Information Systems, pages 97–102, 1999.Google Scholar
  11. 13.
    Ravi K. Kothuri and Siva Ravada. Efficient processing of large spatial queries using interior approximation. In Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases (SSTD 2001), pages 404–421, 2001.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Chengyu Sun
    • 1
  • Divyakant Agrawal
    • 1
  • Amr El Abbadi
    • 1
  1. 1.Department of Computer ScienceUniversity of CaliforniaSanta Barbara

Personalised recommendations