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Extending a spatial access structure to support additional standard attributes

  • Spatial Query Processing
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Advances in Spatial Databases (SSD 1995)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 951))

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Abstract

In recent years, many access structures have been proposed supporting access to objects via their spatial location. However, additional non-geometric properties are always associated with geometric objects, and in practice it is often necessary to use select conditions based on spatial and standard attributes. An obvious idea to improve the performance of queries with mixed select conditions is to extend spatial access structures with additional dimensions for standard attributes. Whereas this idea seems to be simple and promising at first glance, a closer look brings up serious problems, especially with select conditions containing arithmetic expressions or select conditions for non-point objects and with Boolean operators like or and not.

In this paper we present a solution to overcome the problems sketched above which is based on three pillars: (1) We present powerful basic techniques to deal with arithmetic conditions containing mathematical operations (like ‘+’, ‘−’, ‘*’, and ‘∖’) and range queries for non-point objects. (2) We introduce a technique which allows to decompose select conditions containing Boolean operators and to reduce the processing of such a select condition to the processing of its elementary parts. (3) We show how other operations like joins and distance-scans can be integrated into this query processing architecture.

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References

  1. J.L. Bentley. Multidimensional binary search trees used for associative searching. Communications of the ACM, 18(9):509–517, 1975.

    Google Scholar 

  2. L. Becker, K. Hinrichs, and U. Finke. A New Algorithm for Computing Joins with Grid Files. In Proc. IEEE Int'l. Conf. on Data Eng., pages 190–197, Vienna, Austria, April 1993.

    Google Scholar 

  3. N. Beckmann, H.-P. Kriegel, R. Schneider, and B. Seeger. The R*-tree: an efficient and robust access method for points and rectangles. In Proceedings of the ACM SIGMOD Int. Conf. on Management of Data, pages 322–331, Atlantic City, 1990.

    Google Scholar 

  4. J.P. Cheiney, P. Faudemay, R. Michel, and J.M. Thevenin. A Reliable Parallel Backend Using Multiattribute Clustering and Select-Join Operator. In Procs. VLDB, pages 220–227, 1986.

    Google Scholar 

  5. M. Freeston. The BANG file: a new kind of grid file. In Proc. of the ACM SIGMOD Intl. Conf. on Management of Data, pages 260–269, San Francisco, 1987.

    Google Scholar 

  6. O. Günther and J. Bilmes. Tree-based access methods for spatial databases: implementation and performance evaluation. IEEE Trans. on Knowledge and Data Engineering, pages 342–356, 1991.

    Google Scholar 

  7. A. Guttman. R-trees: A dynamic index structure for spatial searching. In Proc. of the ACM SIGMOD Intl. Conf. on Management of Data, pages 47–57, Boston, 1984.

    Google Scholar 

  8. R.H. Güting. Geo-Relational-Algebra: A Model and Query Language for Geometric Database Systems. In J.W. Schmidt, S. Ceri, and M. Missikoff, editors,’ Advances in Database Technology — EDBT'. Proc. of the Intl. Conf. on Extending Database Technology, pages 506–527, 1988.

    Google Scholar 

  9. R.H. Güting. Gral: An Extensible Relational Database System for Geometric Applications. In Proc. of the 15th Intl. Conf. on Very Large Databases, 1989.

    Google Scholar 

  10. A. Henrich. A distance-scan algorithm for spatial access structures. In Proc. of the 2nd ACM Workshop on Advances in Geographic Information Systems, 1994. to appear.

    Google Scholar 

  11. K. Hinrichs. The grid file system: implementation and case studies of applications. Dissertation Nr. 7734, ETH Zürich, 1985.

    Google Scholar 

  12. A. Henrich and J. Möller. Die Nutzung mehrdimensionaler Zugriffsstrukturen für Standardattribute. In Proc. GI-Fachtagung Datenbanksysteme in Büro, Technik und Wissenschaft, Dresden, 1995. to appear.

    Google Scholar 

  13. A. Henrich, H.-W. Six, and P. Widmayer. Paging binary trees with external balancing. In Proc. 15th Intl. Conf. on Graph-Theoretic Concepts in Computer Science, pages 260–276, Aachen, 1989.

    Google Scholar 

  14. A. Henrich, H.-W. Six, and P. Widmayer. The LSD-tree: spatial access to multidimensional point and non point objects. In Proc. 16th Intl. Conf. on Very Large Data Bases, pages 45–53, Amsterdam, 1989.

    Google Scholar 

  15. A. Hutflesz, H.-W. Six, and P. Widmayer. The R-File: An Efficient Access Structure for Proximity Queries. In Proc. IEEE 6th Int. Conf. on Data Engineering, pages 372–379, 1990.

    Google Scholar 

  16. M. Kitsuregawa, L. Harada, and M. Takagi. Join Strategies on KD-Tree Indexed Relations. In Proc. IEEE Conference on Data Engineering, pages 85–93, 1989.

    Google Scholar 

  17. M.J. van Kreveld and M.H. Overmars. Divided k-d Trees. Algorithmica, 6:840–858, 1991.

    Google Scholar 

  18. D.B. Lomet and B. Salzberg. A Robust Multi-Attribute Search Structure. In Proc. IEEE 5th Intl. Conf. on Data Engineering, pages 296–304, 1989.

    Google Scholar 

  19. J. Nievergelt, H. Hinterberger, and K.C. Sevcik. The Grid File: an adaptable, symmetric multikey file structure. ACM Transactions on Database Systems, 9(1):38–71, 1984.

    Google Scholar 

  20. E.A. Ozkarahan and C.H. Bozsahin. Join Strategies Using Data Space Partitioning. New Generation Computing, 6:19–39, 1988.

    Google Scholar 

  21. B.C. Ooi, K.J. McDonell, and R. Sacks-Davis. Spatial kd-Tree: An Indexing Mechanism for Spatial Databases. In IEEE COMPSAC, pages 433–438, 1987.

    Google Scholar 

  22. J.T. Robinson. The K-D-B-Tree: A Search Structure for Large Multdimensional Dynamic Indexes. In Proc. of the ACM SIGMOD Intl. Conf. on Management of Data, pages 10–18, 1981.

    Google Scholar 

  23. B. Seeger and H.-P. Kriegel. Techniques for design and implementation of efficient spatial access methods. In Proc. 14th Intl. Conf. on Very Large Databases, pages 360–371, 1988.

    Google Scholar 

  24. B. Seeger and H.-P. Kriegel. The buddy-tree: an efficient and robust access method for spatial data base systems. In Proc. of the 16th Intl. Conf. on Very Large Data Bases, pages 590–601, Brisbane, 1990.

    Google Scholar 

  25. T. Sellis, N. Roussopoulos, and C. Faloutsos. The R+-tree: a dynamic index for multi-dimensional objects. In Proc. 13th International Conference on Very Large Data Bases, pages 507–518, 1987.

    Google Scholar 

  26. J.A. Thom, K. Ramamohanarao, and L. Naish. A Superjoin Algorithm for Deductive Databases. In Procs. VLDB, pages 189–196, 1986.

    Google Scholar 

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Max J. Egenhofer John R. Herring

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© 1995 Springer-Verlag Berlin Heidelberg

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Henrich, A., Möller, J. (1995). Extending a spatial access structure to support additional standard attributes. In: Egenhofer, M.J., Herring, J.R. (eds) Advances in Spatial Databases. SSD 1995. Lecture Notes in Computer Science, vol 951. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60159-7_9

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  • DOI: https://doi.org/10.1007/3-540-60159-7_9

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  • Online ISBN: 978-3-540-49536-9

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