Database processing models in parallel processing systems

  • Sakti Pramanik
  • Myoung Ho Kim
Parallel Hashing And Sorting
Part of the Lecture Notes in Computer Science book series (LNCS, volume 368)


This paper investigates database processing in parallel processing systems. The objective is to maximize throughput and minimize response time through conflict free data accesses. We propose abstract models as a general framework, and then present two specific parallel processing strategies for two common types of database applications. One is optimal file distribution for partial match queries, and the other is a multidirectory hasing scheme where database accesses are based on primary keys. We show that these proposed parallel processing strategies perform better than those proposed earlier. This work presents a new basis on which design of parallel processing database systems for various applications can be facilitated more systematically.


Parallel Processing File System Access Structure Partial Match Distribution Method 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

6. References

  1. [1]
    Aho, A.V. and Ullman, J.D., "Optimal Partial-Match Retriveal When Fields Are Independently Specified," ACM Trans. Database Systems, vol. 4 no. 2, June 1979, pp. 168–179.Google Scholar
  2. [2]
    Boral, H. and Dewitt, D.J., "Database Machines: An Idea Whose Time Has Passed? A Critique of the Future of Database Machines," Database machines, Leilich, H.O. and Missikoff, M., eds., Springer-Verlag, 1983, pp. 166–187.Google Scholar
  3. [3]
    Du, H.C. and Sobolewski, J.S., "Disk Allocation for Cartesian Product Files on Multiple-Disk Systems," ACM Trans. Database Systems, vol. 7 no. 1, March 1982, pp. 82–101.Google Scholar
  4. [4]
    Kakuta,T., Miyazaki,N., Shibayama,S., Yokota,H. and Murakami,K., "The Design and Implementation of Relational Database Machine Delta," Database Machines, Fourth International Workshop, March 1985, pp. 13–34.Google Scholar
  5. [5]
    Kim, M.H., "Data Distribution Strategies for Parallel Database Accesses", Ph.D. dissertation, Computer Science Department, Michigan State University, 1989.Google Scholar
  6. [6]
    Kim, M.H. and Pramanik, S., "Optimal File Distribution For Partial Match Retrieval," Proc. ACM SIGMOD Conf., 1988, pp. 173–182.Google Scholar
  7. [7]
    Pramanik, S. and Chou, H.-Y., "Performance of Multi Directory Hashing," Technical Report, Computer Science Department, Michigan State University, Oct. 10, 1987.Google Scholar
  8. [8]
    Pramanik, S. and Kim, M.H., "Parallel Processing of Large Node B-trees," IEEE Trans. on Computers (to be published).Google Scholar
  9. [9]
    Rothnie, J.B.Jr. and Lozano, T., "Attribute based file organization in a paged memory environment," Comm. ACM, vol.17, no.2, 1974, pp. 63–69.Google Scholar
  10. [10]
    Su, S.Y.W., L.H. Nguyen, A. Eman and G. J. Lipovski, "The Architectural Features and Implementation Techniques of multicell CASSM," IEEE Trans. on Computers, June 1979, pp. 430–445.Google Scholar
  11. [11]
    Stone, H., "Parallel Querying of Large Database: A Case Study," IEEE Computer, Oct. 1987, pp. 11–21.Google Scholar
  12. [12]
    Sung, Y.Y., "Performance Analysis of Disk Modulo Allocation Method for Cartesian Product Files," IEEE Trans. on Software Eng., Vol. SE-13, No. 9, Sept. 1987, pp. 1018–1026.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1989

Authors and Affiliations

  • Sakti Pramanik
    • 1
  • Myoung Ho Kim
    • 1
  1. 1.Computer Science DepartmentMichigan State UniversityEast Lansing

Personalised recommendations