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The VLDB Journal

, Volume 18, Issue 3, pp 719–738 | Cite as

The RUM-tree: supporting frequent updates in R-trees using memos

  • Yasin N. Silva
  • Xiaopeng Xiong
  • Walid G. Aref
Regular Paper

Abstract

The problem of frequently updating multi-dimensional indexes arises in many location-dependent applications. While the R-tree and its variants are the dominant choices for indexing multi-dimensional objects, the R-tree exhibits inferior performance in the presence of frequent updates. In this paper, we present an R-tree variant, termed the RUM-tree (which stands for R-tree with update memo) that reduces the cost of object updates. The RUM-tree processes updates in a memo-based approach that avoids disk accesses for purging old entries during an update process. Therefore, the cost of an update operation in the RUM-tree is reduced to the cost of only an insert operation. The removal of old object entries is carried out by a garbage cleaner inside the RUM-tree. In this paper, we present the details of the RUM-tree and study its properties. We also address the issues of crash recovery and concurrency control for the RUM-tree. Theoretical analysis and comprehensive experimental evaluation demonstrate that the RUM-tree outperforms other R-tree variants by up to one order of magnitude in scenarios with frequent updates.

Keywords

Indexing techniques Frequent updates Spatio-temporal databases Performance 

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References

  1. 1.
    Antonin Guttman, A.: R-trees: a dynamic index structure for spatial searching. In: SIGMOD (1984)Google Scholar
  2. 2.
    Beckmann, N., Kriegel, H.-P., Schneider, R., Seeger, B.: The R*-tree: an efficient and robust access method for points and rectangles. In: SIGMOD (1990)Google Scholar
  3. 3.
    Brinkhoff, T.: A framework for generating network-based moving objects. GeoInformatica 6(2), (2002)Google Scholar
  4. 4.
    Chakka, P.V., Everspaugh, A., Patel, J.M.: Indexing large trajectory data sets with SETI. In: Proceeding of the Conference on Innovative Data Systems Research, CIDR (2003)Google Scholar
  5. 5.
    Chakrabarti, K., Mehrotra S.: Dynamic granular locking approach to phantom protection in r-trees. In: ICDE (1998)Google Scholar
  6. 6.
    Cheng, R., Xia, Y., Prabhakar, S., Shah, R.: Change tolerant indexing for constantly evolving data. In: ICDE (2005)Google Scholar
  7. 7.
    Hadjieleftheriou, M., Kollios G., Tsotras, V.J., Gunopulos, D.: Efficient indexing of spatiotemporal objects. In: EDBT, pp. 251–268, Prague, March (2002)Google Scholar
  8. 8.
    Kalashnikov D.V., Prabhakar S., Hambrusch S.E.: Main memory evaluation of monitoring queries over moving objects. Distrib. Parallel Databases 15(2), 117–135 (2004)CrossRefGoogle Scholar
  9. 9.
    Kamel, I., Faloutsos, C.: Hilbert R-tree: an improved R-tree using fractals. In: VLDB, pp. 500–509 (1994)Google Scholar
  10. 10.
    Kim, K., Cha, S.K., Kwon, K.: Optimizing multidimensional index trees for main memory access. In: SIGMOD (2001)Google Scholar
  11. 11.
    Kollios, G., Gunopulos, D., Tsotras, V.J.: On indexing mobile objects. In: PODS (1999)Google Scholar
  12. 12.
    Kwon, D., Lee, S., Lee, S.: Indexing the current positions of moving objects using the lazy update R-tree. In: Mobile Data Management, MDM (2002)Google Scholar
  13. 13.
    Lee, M.-L., Hsu, W., Jensen, C.S., Teo, K.L.: Supporting Frequent Updates in R-Trees: A Bottom-Up Approach. In VLDB, (2003)Google Scholar
  14. 14.
    Manolopoulos, Y., Nanopoulos, A., Papadopoulos, A.N., Theodoridis, Y.: R-trees have grown everywhere. In: Technical Report, Available at http://citeseer.ist.psu.edu/706599.html (2003)
  15. 15.
    Nascimento, M.A., Silva, J.R.O.: Towards historical R-trees. In: Proceeding of the ACM Symposium on Applied Computing, SAC, pp. 235–240, February (1998)Google Scholar
  16. 16.
    Pfoser, D., Jensen, C.S., Theodoridis, Y.: Novel approaches in query processing for moving object trajectories. In: VLDB, pp. 395–406, September (2000)Google Scholar
  17. 17.
    Porkaew, K., Lazaridis, I., Mehrotra, S.: Querying mobile objects in spatio-temporal databases. In: SSTD, pp. 59–78, Redondo Beach, July (2001)Google Scholar
  18. 18.
    Prabhakar S., Xia Y., Kalashnikov D.V., Aref W.G., Hambrusch S.E.: Query indexing and velocity constrained indexing: scalable techniques for continuous queries on moving objects. IEEE Trans. Comput. 51(10), 1124–1140 (2002)CrossRefMathSciNetGoogle Scholar
  19. 19.
    Procopiuc, C.M., Agarwal, P.K., Har-Peled, S.: STAR-tree: an efficient self-adjusting index for moving objects. In: Proceeding of the Workshop on Algorithm Engineering and Experimentation, ALENEX, pp. 178–193, January (2002)Google Scholar
  20. 20.
    Roussopoulos, N., Leifker, D.: Direct spatial search on pictorial databases using packed r-trees. In: SIGMOD, pp. 17–31 (1985)Google Scholar
  21. 21.
    Saltenis, S., Jensen, C.S.: Indexing of moving objects for location-based services. In: ICDE (2002)Google Scholar
  22. 22.
    Saltenis S., Jensen C.S.: Indexing of now-relative spatio-bitemporal data. VLDB J. 11(1), 1–16 (2002)CrossRefGoogle Scholar
  23. 23.
    Saltenis, S., Jensen, C.S., Leutenegger, S.T., Lopez, M.A.: Indexing the positions of continuously moving objects. In: SIGMOD (2000)Google Scholar
  24. 24.
    Sellis, T.K.: Nick Roussopoulos, and Christos Faloutsos. The r+-tree: a dynamic index for multi-dimensional objects. In: VLDB, pp. 507–518 (1987)Google Scholar
  25. 25.
    Tao, Y., Papadias, D.: Efficient historical R-trees. In: SSDBM, pp. 223–232, July (2001)Google Scholar
  26. 26.
    Tao, Y., Papadias, D.: MV3R-tree: a spatio-temporal access method for timestamp and interval queries. In: VLDB (2001)Google Scholar
  27. 27.
    Tao, Y., Papadias, D., Sun, J.: The TPR*-tree: an optimized spatio-temporal access method for predictive queries. In: VLDB (2003)Google Scholar
  28. 28.
    Theodoridis, Y., Vazirgiannis, M., Sellis, T.: Spatio-temporal indexing for large multimedia applications. In: Proceedings of the IEEE Conference on Multimedia Computing and Systems, ICMCS, June (1996)Google Scholar
  29. 29.
    Xiong, X., Aref, W.G.: R-trees with update memos. In: ICDE (2006)Google Scholar

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Yasin N. Silva
    • 1
  • Xiaopeng Xiong
    • 1
  • Walid G. Aref
    • 1
  1. 1.Department of Computer SciencesPurdue UniversityWest LafayetteUSA

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