Advertisement

Query processing of spatial objects: Complexity versus redundancy

  • Michael Schiwietz
  • Hans-Peter Kriegel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 692)

Abstract

The management of complex spatial objects in applications, such as geography and cartography, imposes stringent new requirements on spatial database systems, in particular on efficient query processing. As shown before, the performance of spatial query processing can be improved by decomposing complex spatial objects into simple components. Up to now, only decomposition techniques generating a linear number of very simple components, e.g. triangles or trapezoids, have been considered. In this paper, we will investigate the natural trade-off between the complexity of the components and the redundancy, i.e. the number of components, with respect to its effect on efficient query processing. In particular, we present two new decomposition methods generating a better balance between the complexity and the number of components than previously known techniques. We compare these new decomposition methods to the traditional undecomposed representation as well as to the well-known decomposition into convex polygons with respect to their performance in spatial query processing. This comparison points out that for a wide range of query selectivity the new decomposition techniques clearly outperform both the undecomposed representation and the convex decomposition method. More important than the absolute gain in performance by a factor of up to an order of magnitude is the robust performance of our new decomposition techniques over the whole range of query selectivity.

Keywords

Query Processing Object Representation Point Query Spatial Object Simple Polygon 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [AA 83]
    Ta. Asano and Te. Asano, Minimum partition of polygonal regions into trapezoids, Proc. 24th IEEE Annual Symp. on Foundations of Computer Science, 1983, 233–241.Google Scholar
  2. [BKS 93]
    T. Brinkhoff, H.-P. Kriegel, and R. Schneider, Comparison of approximations of complex objects used for approximation-based query processing in spatial databases, in Proc. 9th Int. Conf. on Data Engineering, Vienna, Austria, 1993.Google Scholar
  3. [BKSS 90]
    N. Beckmann, H.-P. Kriegel, R. Schneider, and B. Seeger, The R*-tree: An efficient and robust access method for points and rectangles, Proceedings ACM SIGMOD Int Conf. on Management of Data, Atlantic City, NJ, 1990, 322–331.Google Scholar
  4. [Bra 92]
    A. Braun, A graphic-oriented tool for analyzing spatial objects: ‘its design and application to real world data', Master thesis, Institute for Computer Science, University of Munich, Germany, 1992, (in German).Google Scholar
  5. [CD 85]
    B. Chazelle and D.P. Dobkin, Optimal convex decompositions, in computational geometry, Proceedings Comp. Geometry, Elsevier Science, Netherland, 1985, 63–134.Google Scholar
  6. [Fra 91]
    A.U. Frank, Properties of geographic data, Proceedings 2nd Symp. on Large Spatial Databases, SSD'91, ETH Zurich, 1991, 225–234, in: Lecture Notes in Computer Science, Vol. 525, Springer, 1991.Google Scholar
  7. [Kei 83]
    J.M. Keil, Decomposing polygons into simpler components, Ph.D. thesis, Department of Computer Science, University of Toronto, 1983.Google Scholar
  8. [KS 85]
    J.M. Keil and J.R. Sack, Minimum decomposition of polygonal objects, in Computational Geometry, G.T. Toissant (Ed.), Amsterdam, Netherland, 1985, 197–216.Google Scholar
  9. [KBS 91]
    H.-P. Kriegel, T. Brinkhoff, and R. Schneider, An efficient map overlay algorithm based on spatial access methods and Computational Geometry, Int. Workshop on Database Management Systems for Geographical Applications, Capri, Italy, 1991, in: Geographic Database Management Systems, Springer, 1992, 194–211.Google Scholar
  10. [KHS 91]
    H.-P. Kriegel, H. Horn, and M. Schiwietz, The performance of object decomposition techniques for spatial query processing, Proceedings 2nd Symp. on Large Spatial Databases, SSD'91, Zurich, 1991, 257–276.Google Scholar
  11. [Law 72]
    C.L. Lawson, Generation of a triangular grid with application to contour plotting, CIT Jet Propulsion Laboratory, Technical Memorandum 299, Pasadena, CA, 1972.Google Scholar
  12. [NHS 84]
    J. Nievergelt, H. Hinterberger, and K.C. Sevik, The Grid File: an adaptable, symmetric multikey file structure, ACM Transactions on Database Systems, Vol. 9, 1, 1984,38–71.Google Scholar
  13. [Ore 89]
    J. Orenstein,Redundancy in spatial databases, Proceedings 1st International Symposium on Large Spatial Databases, SSD'89, Santa Barbara, CA, 1989.Google Scholar
  14. [OM 86]
    J. Orenstein and F. A. Manola, Spatial data modeling and query processing in PROBE, Technical Report CCA-86-05, Xerox Advanced Inform. Technology Devision, 1986.Google Scholar
  15. [PS 88]
    F.P. Preparata and M.I. Shamos, Computational Geometry, Springer, New York, 1988.Google Scholar
  16. [Sam 90]
    H. Samet, The Design and Analysis of Spatial Data Structures, Addison-Wesley, 1990.Google Scholar
  17. [Schi 93]
    M. Schiwietz, Storage and Query Processing of Complex Spatial Objects, Ph.D. thesis, (in German), Inst for Computer Science, University of Munich, Germany, 1993.Google Scholar
  18. [Schn 92]
    R. Schneider, A Storage and Access Structure of Spatial Database Systems, Ph.D. thesis, (in German), Institute for Computer Science, University of Munich, Germany, 1992.Google Scholar
  19. [SK 91]
    R. Schneider and H.-P. Kriegel, The TR*-tree: a new representation of polygonal objects supporting spatial queries and operations, Proceedings 7th Workshop on Computational Geometry, Bern, Switzerland, 1991, in: Lecture Notes in Computer Science, Vol. 553, Springer, 1991, 249–264.Google Scholar
  20. [See 89]
    B. Seeger, Design and implementation of multidimensional access methods, Ph.D. thesis, (in German), Depart. of Computer Science, University of Bremen, Germany, 1989.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Michael Schiwietz
    • 1
  • Hans-Peter Kriegel
    • 1
  1. 1.Institute for Computer ScienceUniversity of MunichMunich 40Germany

Personalised recommendations