PCR-Tree: An Enhanced Cache Conscious Multi-dimensional Index Structures

  • Young Soo Min
  • Chang Yong Yang
  • Jae Soo Yoo
  • Jeong Min Shim
  • Seok Il Song
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3180)


Recently, to relieve the performance degradation caused by the bottleneck between CPU and main memory, cache conscious multi-dimensional index structures have been proposed. The ultimate goal of them is to reduce the space for entries so as to widen index trees, and minimize the number of cache misses. They can be classified into two approaches according to their space reduction methods. One approach is to compress MBRs by quantizing coordinate values to the fixed number of bits. The other approach is to store only the sides of MBRs that are different from their parents. In this paper, we investigate the existing multi-dimensional index structures for main memory database sy stems through experiments under the various work loads. Then, we propose a new index structure that exploits the properties of the both techniques. We implement existing multi-dimensional index structures and the proposed index structure, and perform various experiments to show that our approach outperforms others.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Ailamaki, A., DeWitt, D.J., Hill, M.D., Wood, D.A.: DBMSs on a Modern Processor: Where Does Time Go? In: Proceedings of VLDB Conference, pp. 266–277 (1999)Google Scholar
  2. 2.
    Manegold, S., Boncz, P.A., Kersten, M.L.: Optimizing database architecture for the new bottleneck: Memory access. VLDB Journal 9(3), 231–246 (2000)CrossRefGoogle Scholar
  3. 3.
    Rao, J., Ross, K.A.: Cache Conscious Indexing for Decision-Support in Main Memory. In: Proceedings of VLDB Conference, pp. 78–79 (1999)Google Scholar
  4. 4.
    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
  5. 5.
    Bohannon, P., Mcllroy, P., Rastogi, R.: Main-Memory Index Structures with Fixed-Size Partial Keys. In: Proceedings of ACM SIGMOD Conference, pp. 163–174 (2001)Google Scholar
  6. 6.
    Chen, S., Gibbons, P.B., Mowry, T.C.: Improving Index Performance through Prefetching. In: Proceedings of ACM SIGMOD Conference, pp. 235–246 (2001)Google Scholar
  7. 7.
    Kim, K.H., Cha, S.K., Kwon, K.J.: Optimizing Multidimensional Index trees for Main Memory Access. In: Proceeding of ACM SIGMOD Conference, pp. 139–150 (2001)Google Scholar
  8. 8.
    Sitzmann, I., Stuckey, P.J.: Compacting discriminator information for spatial trees. In: Proceedings of the Thirteenth Australasian Database Conference, pp. 167–176 (2002)Google Scholar
  9. 9.
    Guttman, A.: R-trees: A Dynamic Index Structure for Spatial Searching. In: Proceedings of ACM SIGMOD Conference, pp. 47–47 (1984)Google Scholar
  10. 10.
    Leutenegger, S.T., Edgington, J.M., Lopez, M.A.: STR: A Simple and Efficient Algorithm for R-tree Packing. In: Proceedings of ICDE Conference, pp. 497–506 (1997)Google Scholar
  11. 11.

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Young Soo Min
    • 1
  • Chang Yong Yang
    • 1
  • Jae Soo Yoo
    • 1
  • Jeong Min Shim
    • 2
  • Seok Il Song
    • 3
  1. 1.Department of Computer and Communication EngineeringChungbuk National UniversityCheongju ChungbukKorea
  2. 2.Electronics and Telecommunications Research InstituteDaejeonKorea
  3. 3.Department of Computer EngineeringChungju National UniversityChungju ChungbukKorea

Personalised recommendations