Advertisement

Growing Node Policies of a Main Memory Index Structure for Moving Objects Databases

  • Kyounghwan An
  • Bonghee Hong
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3180)

Abstract

Recent studies on main memory index structures focus mainly on cache-conscious structures to minimize L2 cache misses; for example, in one dimensional data, CSB+-tree eliminated pointers to pack more entries in a node, and in multi-dimensional data, CR-tree compressed MBRs in order to increase utilization of the L2 cache line. Previous studies used a fixed node size that is a multiple of the cache line size. If a node overflows, it splits , regardless of the search performance. Since the time of split is determined by only the node size, the split may increase a node’s probability of being accessed. However, if the node size is not fixed, the previous case can be avoided. In this paper, we suggest a new cost model to determine whether to grow or split a node. In the cost model, we consider all relevant factors, such as cache misses, instruction counts, TLB misses, and the probability that nodes will be accessed. Use of our growing node policy has the following advantages: (i) it can have the effect of a delayed split that does not depend on the insertion order, and (ii) it can reduce the number of generated nodes and the height of the tree.

Keywords

Cost Model Decision Function Range Query Search Performance Node Size 
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. 1.
    Guttman, A.: R-trees: A Dynamic Index Structure for Spatial Searching. In: Proceedings of ACM SIGMOD Conference, pp. 47–57 (1984)Google Scholar
  2. 2.
    Hankins, R.A., Patel, J.M.: Effect of Node Size on the Performance of Cache- Conscious B+-trees. In: SIGMETRICS 2003, pp. 283–294 (2003)Google Scholar
  3. 3.
    Kamel, I., Faloutsos, C.: On Packing R-trees. In: Proceedings of ACM CIKM Conference, pp. 490–499 (1993)Google Scholar
  4. 4.
    Kim, K.H., Cha, S.K., Kwon, K.J.: Optimizing Multidimensional Index Trees for Main Memory Access. In: Proc. of ACM SIGMOD Conf., pp. 139–150 (2001)Google Scholar
  5. 5.
    Lehman, T.J., Carey, M.J.: A Study of Index Structures for Main Memory Database Management Systems. In: Proceedings of VLDB Conference, pp. 294–303 (1986)Google Scholar
  6. 6.
    Pagel, B.U., Six, H.W., Toben, H., Widmayer, P.: Towards an Analysis of Range Query Performance. In: Proceedings of ACM PODS, pp. 214–221 (1993)Google Scholar
  7. 7.
    Rao, J., Ross, K.A.: Making B+-trees Cache Conscious in Main Memory. In: Proceedings of ACM SIGMOD Conference, pp. 475–486 (2000)Google Scholar
  8. 8.
    Theodoridis, Y., Nascimento, M.: Generating Spatiotemporal Datasets on the WWW. ACM SIGMOD Record 29(3), 39–43 (2000)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Kyounghwan An
    • 1
  • Bonghee Hong
    • 1
  1. 1.Department of Computer EngineeringBusan National UniversityBusanRepublic of Korea

Personalised recommendations