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    Abstract:

    The parallel query optimization for multi-join expressions is one of the key factors to improve the performance of database systems. In this paper, an approach to solve the problems of the parallel query optimization for multi-join expressions by adopting GA algorithms is proposed. To improve the execution efficiency of the query processors, the authors exploit heuristics to seek the optimum parallel scheduling execution plan for multi-join expressions. The detailed testing results and performance analysis are presented.The experiment results show that the GA algorithm with heuristic knowledge is effective for parallel query processing of multi-joins,and plays an important role in improving the performance of database systems.

    Reference
    [1] Chen, M.S., Yu, P.S., Wu, K.L. Optimization of parallel execution for multi-join queries. IEEE Transactions on Knowledge and Data Engineering, 1996,8(3):416~428.
    [2] Steinbrunn, M., Moerkotte, G., Kemper, A. Heuristic and randomized optimization for the join ordering problem. VLDB Journal, 1997,6(3):191~208.
    [3] Wilschut, A.N., Flokstra, J., Apers, P.M.G. Parallel evaluation of multi-join queries. In: Michael, J.C., Donovan, A.S., eds. Proceedings of the ACM-SIGMOD'95. San Jose, CA: Academic Press, 1995. 115~126.
    [4] Chen, M.S., Yu, P.S., Wu, K.L. Scheduling and processor allocation for parallel execution of multi-join queries. In: Proceedings of the 8th International Conference on Data Engineering. Arizona: I.C.S. Press, 1992. 58~67.
    [5] Zhou Ming, Sun Shu-dong. The Principle and Application of Genetic Algorithm. Beijing: National Defense Industry Press, 1999 (in Chinese). 周明,孙树栋.遗传算法原理及应用.北京:国防工业出版社, 1999.
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曹阳,方强,王国仁,于戈.基于遗传算法的多连接表达式并行查询优化.软件学报,2002,13(2):250-257

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History
  • Received:April 20,2001
  • Revised:September 24,2001
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