Advertisement

Bulk-Loading xBR\(^+\)-trees

  • George Roumelis
  • Michael VassilakopoulosEmail author
  • Antonio Corral
  • Yannis Manolopoulos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9893)

Abstract

Spatial indexes are important in spatial databases for efficient execution of queries involving spatial constraints. The xBR\(^+\)-tree is a balanced disk-resident quadtree-based index structure for point data, which is very efficient for processing such queries. Bulk-loading refers to the process of creating an index from scratch as a whole, when the dataset to be indexed is available beforehand, instead of creating (loading) the index gradually, when the dataset items are available one-by-one. In this paper, we present an algorithm for bulk-loading xBR\(^+\)-trees for big datasets residing on disk, using a limited amount of RAM. Moreover, using real and artificial datasets of various cardinalities, we present an experimental comparison of this algorithm vs. the algorithm loading items one-by-one, regarding performance (I/O and execution time) and the characteristics of the xBR\(^+\)-trees created. We also present experimental results regarding the efficiency of bulk-loaded xBR\(^+\)-trees vs. xBR\(^+\)-trees where items are loaded one-by-one for query processing.

Keywords

Spatial indexes Bulk-loading xBR\(^+\)-trees Query processing 

References

  1. 1.
    Shekhar, S., Chawla, S.: Spatial Databases - A Tour. Prentice Hall, Upper Saddle River (2003)Google Scholar
  2. 2.
    Van den Bercken, J., Seeger, B.: An evaluation of generic bulk loading techniques. In: VLDB Conference, pp. 461–470 (2001)Google Scholar
  3. 3.
    Roumelis, G., Vassilakopoulos, M., Loukopoulos, T., Corral, A., Manolopoulos, Y.: The xBR\(^+\)-tree: an efficient access method for points. In: Chen, Q., Hameurlain, A., Toumani, F., Wagner, R., Decker, H. (eds.) DEXA 2015. LNCS, vol. 9261, pp. 43–58. Springer, Heidelberg (2015)CrossRefGoogle Scholar
  4. 4.
    Roumelis, G., Vassilakopoulos, M., Corral, A.: Performance comparison of xBR-trees and R*-trees for single dataset spatial queries. In: Eder, J., Bielikova, M., Tjoa, A.M. (eds.) ADBIS 2011. LNCS, vol. 6909, pp. 228–242. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  5. 5.
    Beckmann, N., Kriegel, H.P., Schneider, R., Seeger, B.: The R*-tree: an efficient and robust access method for points and rectangles. In: SIGMOD Conference, pp. 322–331 (1990)Google Scholar
  6. 6.
    Arge, L., Hinrichs, K.H., Vahrenhold, J., Vitter, J.S.: Efficient bulk operations on dynamic R-trees. Algorithmica 33(1), 104–128 (2002)MathSciNetCrossRefzbMATHGoogle Scholar
  7. 7.
    Van den Bercken, J., Seeger, B., Widmayer, P.: A generic approach to bulk loading multidimensional index structures. In: VLDB Conference, pp. 406–415 (1997)Google Scholar
  8. 8.
    Roussopoulos, N., Leifker, D.: Direct spatial search on pictorial databases using packed R-trees. In: SIGMOD Conference, pp. 17–31 (1985)Google Scholar
  9. 9.
    Kamel, I., Faloutsos, C.: On packing R-trees. In: CIKM Conference, pp. 490–499 (1993)Google Scholar
  10. 10.
    Leutenegger, S.T., Edgington, J.M., Lopez, M.A.: STR: a simple and efficient algorithm for R-Tree packing. In: ICDE Conference, pp. 497–506 (1997)Google Scholar
  11. 11.
    Achakeev, D., Seeger, B., Widmayer, P.: Sort-based query-adaptive loading of R-trees. In: CIKM Conference, pp. 2080–2084 (2012)Google Scholar
  12. 12.
    Achakeev, D., Schmidt, M., Seeger, B.: Sort-based parallel loading of R-trees. In: BigSpatial Workshop, pp. 62–70 (2012)Google Scholar
  13. 13.
    Van den Bercken, J., Seeger, B., Widmayer, P.: A generic approach to bulk loading multidimensional index structures. In: VLDB Conference, pp. 406–415 (1997)Google Scholar
  14. 14.
    Ciaccia, P., Patella, M.: Bulk loading the M-tree. In: Australian Database Conference, pp. 15–26 (1998)Google Scholar
  15. 15.
    Berchtold, S., Böhm, C., Kriegel, H.-P.: Improving the query performance of high-dimensional index structures by bulk load operations. In: Schek, H.-J., Saltor, F., Ramos, I., Alonso, G. (eds.) EDBT 1998. LNCS, vol. 1377, pp. 216–230. Springer, Heidelberg (1998)Google Scholar
  16. 16.
    Hjaltason, G.R., Samet, H., Sussmann, Y.J.: Speeding up bulk-loading of quadtrees. In: ACM GIS Conference, pp. 50–53 (1997)Google Scholar
  17. 17.
    Hjaltason, G.R., Samet, H.: Improved bulk-loading algorithms for quadtrees. In: ACM GIS Conference, pp. 110–115 (1999)Google Scholar
  18. 18.
    Hjaltason, G.R., Samet, H.: Speeding up construction of PMR quadtree-based spatial indexes. VLDB J. 11(2), 109–137 (2002)CrossRefGoogle Scholar
  19. 19.
    Vassilakopoulos, M., Manolopoulos, Y.: External balanced regular (x-BR) trees: new structures for very large spatial databases. In: Advances in Informatics: Selected Papers of the 7th Panhellenic Conference on Informatics. World Scientific Publishing Co., pp. 324–333 (2000)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • George Roumelis
    • 1
  • Michael Vassilakopoulos
    • 2
    Email author
  • Antonio Corral
    • 3
  • Yannis Manolopoulos
    • 1
  1. 1.Department of InformaticsAristotle University of ThessalonikiThessalonikiGreece
  2. 2.Department of Electrical and Computer EngineeringUniversity of ThessalyVolosGreece
  3. 3.Department of InformaticsUniversity of AlmeriaAlmeriaSpain

Personalised recommendations