Two-way join optimization in partitioned database systems

  • Fang Li
  • Lawrence V. Saxton
Complexity And Optimization
Part of the Lecture Notes in Computer Science book series (LNCS, volume 326)


The optimization of two-way joins is studied in order to minimize the response time in a partitioned database. We assume that the background communication network is capable of parallel transmission, which differentiates the response time measure from the total cost measure. However, we do not make the standard simplifying assumption that communications between different sites is uniform, which results in a nonlinear optimization formulation of the problem. Subsequently, we derive a fast polynomial algorithm to solve the problem. Two less general algorithms are also proposed to explore the effect of local semijoins and remote semijoins as reducers. Finally, computational experiments are carried out to investigate the trade-off between the computation time and the quality of solutions as well as to analyze the sensitivity of the solutions to various parameters of our model.


Fragment Size Query Processing Selectivity Factor Transmission Schedule Response Time Measure 
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.


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  1. [1]
    Apers, P. M. G., Hevner, A. R. and Yao, S. B., "Optimization Algorithms for Distributed Queries", IEEE Transactions on Software Engineering, Vol. SE-9 No. 1, Jan. 1983, 57–68.Google Scholar
  2. [2]
    Bernstein, P. A. and Goodman, N., "Query Processing in a System for Distributed Database (SDD-1)", ACM Transactions on Database Systems, Vol. 6, No. 4, Dec. 1981, 602–625.Google Scholar
  3. [3]
    Ceri, S. and Gottlob, G., "Optimizing Joins between Two Partitioned Relations in Distributed Databases", Journal of Parallel and Distributed Computing, Vol. 3, 1986, 183–205.Google Scholar
  4. [4]
    Ceri, S. and Pelagatti, G., Distributed database Principle and Systems, McGraw-Hill Book Company, New York, 1985.Google Scholar
  5. [5]
    Daniels, D. et al., "An Introduction to Distributed Query Compilation in R*.", Distributed Data Bases, H. J. Schneider, ed., North-Holland, 1982.Google Scholar
  6. [6]
    Epstein, R., Stonebraker M. and Wong, E., "Distributed Query Processing in a Relational Database", Proceedings SIGMOD International Conference on Management of Data, May 1978, 169–180.Google Scholar
  7. [7]
    Gavish, B. and Segev, A., "Set Query Optimization in Horizontally Partitioned Distributed Database Systems", ACM Transaction on Distributed Database Management Systems, Vol. 11, No. 3, 1986, 265–293.Google Scholar
  8. [8]
    Hevner, A. R. and Yao, S. B., "Query Processing in Distributed Database systems", IEEE Transaction on Software Engineering, Vol. SE-5, No. 3, May 1979, 177–187, 69–88.Google Scholar
  9. [9]
    Lafortune, S. and Wong, E., "A State Transition Model for Distributed Query Processing", ACM Transactions on Database System, Vol. 11, No. 3, Sept. 1986, 294–322.Google Scholar
  10. [10]
    Maier, D., The Theory of Relational Databases, Computer Science Press, Rockville, Maryland, 1983.Google Scholar
  11. [11]
    Pelagatti, G., and Manning, E. D., "A Model of an Access Strategy in a Distributed Database System", In Proceedings of the IFIP-TC2, Database Architecture, 1979Google Scholar
  12. [12]
    Segev, A., "Optimization of Join Operations in Horizontal Partitioned Database Systems", ACM Transactions on Database Systems, Vol. 11, No. 1, March 1986, 48–80.Google Scholar
  13. [13]
    Stonebraker, M. and Neuhold, E., "A Distributed Database Version of INGRES", In Proceedings of the 3rd Berkeley Workshop on the Distributed Data Management and Computer Networks, 1977.Google Scholar
  14. [14]
    Syslo, M. M., Deo, N. and Kowalik, J., "Discrete Optimization Algorithms with Pascal Programs", Prentice-Hall, Inc., Englewood Cliffs, New Jersey, 1983.Google Scholar
  15. [15]
    Williams, R., et al., "R*: An overview of the architecture", IBM Res. Rep. RJ3325, 1981.Google Scholar
  16. [16]
    Yu, C. T., Chang, C. C. and Chang, Y., "Two Surprising Results in Processing Simple Queries in Distributed Databases", Proceedings of the IEEE 6th International Computer Software and Application Conference, 1982, 377–384.Google Scholar
  17. [17]
    Yu, C. T., Chang, C. C., "On the design of a query processing strategy in a distributed databases", Proceedings of the ACM SIGMOD Database Week, 1983, 30–39.Google Scholar
  18. [18]
    Yu, C. T. and Chang, C. C., "Distributed Query Processing", Computing Surveys, Vol. 16, No. 4, December 1984, 399–433.Google Scholar
  19. [19]
    Yu, C. T. and Chang, C. C. et al., "Query Processing in a Fragmented Relational Distributed Systems: Mermaid", IEEE Transaction on Software Engineering, Vol. SE-11, No. 8, August 1985, 795–810.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1988

Authors and Affiliations

  • Fang Li
    • 1
  • Lawrence V. Saxton
    • 1
  1. 1.Department of Computer ScienceUniversity of ReginaReginaCanada

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