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Performance comparison of point and spatial access methods

  • Hans-Peter Kriegel
  • Michael Schiwietz
  • Ralf Schneider
  • Bernhard Seeger
System And Performance Issues
Part of the Lecture Notes in Computer Science book series (LNCS, volume 409)

Abstract

In the past few years a large number of multidimensional point access methods, also called multiattribute index structures, has been suggested, all of them claiming good performance. Since no performance comparison of these structures under arbitrary (strongly correlated nonuniform, short "ugly") data distributions and under various types of queries has been performed, database researchers and designers were hesitant to use any of these new point access methods. As shown in a recent paper, such point access methods are not only important in traditional database applications. In new applications such as CAD/CIM and geographic or environmental information systems, access methods for spatial objects are needed. As recently shown such access methods are based on point access methods in terms of functionality and performance. Our performance comparison naturally consists of two parts. In part I we will compare multidimensional point access methods, whereas in part II spatial access methods for rectangles will be compared. In part I we present a survey and classification of existing point access methods. Then we carefully select the following four methods for implementation and performance comparison under seven different data files (distributions) and various types of queries: the 2-level grid file, the BANG file, the hB-tree and a new scheme, called the BUDDY hash tree. We were surprised to see one method to be the clear winner which was the BUDDY hash tree. It exhibits an at least 20 % better average performance than its competitors and is robust under ugly data and queries. In part II we compare spatial access methods for rectangles. After presenting a survey and classification of existing spatial access methods we carefully selected the following four methods for implementation and performance comparison under six different data files (distributions) and various types of queries: the R-tree, the BANG file, PLOP hashing and the BUDDY hash tree. The result presented two winners: the BANG file and the BUDDY hash tree. This comparison is a first step towards a standardized tested or benchmark. We offer our data and query files to each designer of a new point or spatial access method such that he can run his implementation in our testbed.

Keywords

access methods performance comparison spatial database systems 

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References

  1. [Com 79]
    D. Comer: ‘The Ubiquitous B-tree', Computing Surveys, Vol.11, No.2, 121–137, 1979CrossRefGoogle Scholar
  2. [Bur 83]
    W.A. Burkhard: ‘Interpolation-based index maintenance', BIT 23, 274–294, 1983Google Scholar
  3. [Fre 87]
    M. Freeston: ‘The BANG file: a new kind of grid file', Proc. ACM SIGMOD Int. Conf. on Management of Data, 260–269, 1987Google Scholar
  4. [Gre 89]
    D. Greene: ‘An Implementation and Performance Analysis of Spatial Data Access Methods', Proc. 5th Int. Conf. on Data Engineering, 606–615, 1989Google Scholar
  5. [Gün 89]
    O. Günther: The design of the cell tree: An object-oriented index structure for geometric databases, in Proc. Fifth Intl. Conf. on Data Engineering, Feb. 6–10, 1989, Los AngelesGoogle Scholar
  6. [Gut 84]
    A. Guttman: ‘R-trees: a dynamic index structure for spatial searching', Proc. ACM SIGMOD Int. Conf. on Management of Data, 47–57, 1984Google Scholar
  7. [Hin 85]
    K. Hinrichs: 'The grid file system: implementation and case studies for applications', Dissertation No. 7734, Eidgenössische Technische Hochschule (ETH), Zuerich, 1985Google Scholar
  8. [HSW 88]
    A. Hutflesz, H.-W. Six, P. Widmayer: ‘Twin grid files: space optimizing access schemes', Proc. ACM SIGMOD Int. Conf. on Management of Data, 183–190, 1988Google Scholar
  9. [Kri 84]
    H.P. Kriegel: ‘Performance comparison of index structures for multikey retrieval', Proc. ACM SIGMOD Int. Conf. on Management of Data, 186–196, 1984Google Scholar
  10. [KS 86]
    H.P. Kriegel, B. Seeger: ‘Multidimensional order preserving linear hashing with partial expansions', Proc. Int. Conf. on Database Theory, Lecture Notes in Computer Science 243, 203–220, 1986Google Scholar
  11. [KS 87]
    H.P. Kriegel, B. Seeger: ‘Multidimensional quantile hashing is very efficient for non-uniform distributions', Proc. 3rd Int. Conf. on Data Engineering, 10–17, 1987, extended version will appear in Information ScienceGoogle Scholar
  12. [KS 88]
    H.P. Kriegel, B. Seeger: ‘PLOP-Hashing: a grid file without directory', Proc. 4th Int. Conf. on Data Engineering, 369–376, 1988Google Scholar
  13. [LS 89]
    D.B. Lomet, B. Salzberg: The hB-tree: A robust multiattribute search structure, in Proc. of the Fifth Int. Conf. on Data Engineering, Feb. 6–10, 1989, Los Angeles, also available as Technical Report TR-87-05, School of Information Technology, Wang Institute of Graduate Studies.Google Scholar
  14. [NHS 84]
    J. Nievergelt, H. Hinterberger, K.C. Sevcik: ‘The grid file: an adaptable, symmetric multikey file structure', ACM Trans. on Database Systems, Vol. 9, 1, 38–71, 1984CrossRefGoogle Scholar
  15. [NH 85]
    J. Nievergelt, K. Hinrichs: 'storage and access structures for geometric data bases', Proc. Int. Conf. on Foundsations of Data Organization, 335–345, 1985Google Scholar
  16. [OM 84]
    J.A. Orenstein, T.H. Merrett: ‘A class of data structures for associative searching', Proc 3rd ACM SIGACT-SIGMOD Symposium on Principles of Database Systems, 181–190, 1984Google Scholar
  17. [Oto 84]
    E. J. Otoo: ‘A mapping function for the directory of a multidimensional extendible hashing', Proc. 10th Int. Conf. on Very Large Databases, 491–506, 1984Google Scholar
  18. [Oto 86]
    E. J. Otoo,: ‘Balanced multidimensional extendible hash tree', Proc. 5th ACM SIGACT-SIGMOD Symposium on Principles of Database Systems, 110–113, 1986Google Scholar
  19. [Ouk 85]
    M. Ouksel: ‘The interpolation based grid file', Proc. 4th ACM SIGACT-SIGMOD Symposium on Principles of Database Systems, 1985Google Scholar
  20. [Rob 81]
    J. T. Robinson: ‘The K-D-B-tree: a search structure for large multidimensional dynamic indexes', Proc. ACM SIGMOD Int. Conf. on Management of Data, 10–18, 1981Google Scholar
  21. [See 89]
    Seeger, B.: ‘Design and implementation of multidimensional access methods’ in German), PhD thesis, Department of Computer Science, University of Bremen.Google Scholar
  22. [SFK 89]
    B. Seeger, S. Frank, H.P. Kriegel: The buddy hash tree, English version in preparation, German version available as a Technical ReportGoogle Scholar
  23. [SFR 87]
    Sellis, T., Roussopoulos, N., Faloutsos, C.: ‘The R+-tree: a dynamic index for multi-dimensional objects', Proc. 13th Int. Conf. on Engeneering, 1988.Google Scholar
  24. [SK 88]
    B. Seeger, H. P. Kriegel: ‘Design and implementation of spatial access methods', Proc. 14th Int. Conf. on Very Large Databases, 360–371, 1988Google Scholar
  25. [Tam 82]
    M. Tamminen: ‘The extendible cell method for closest point problems', BIT 22, 27–41, 1982Google Scholar
  26. [WK 85]
    K.-Y. Whang, R. Krishnamurthy: 'Multilevel grid files', Technical Report, IBM Research Lab., Yorktown Heights, 1985Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1990

Authors and Affiliations

  • Hans-Peter Kriegel
    • 1
  • Michael Schiwietz
    • 1
  • Ralf Schneider
    • 1
  • Bernhard Seeger
    • 1
  1. 1.Praktische InformatikUniversity of BremenBremen 33West Germany

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