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基于遗传算法的多连接表达式并行查询优化 被引量:25

Parallel Query Optimization Techniques for Multi-Join Expressions Based onGenetic Algorithm
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摘要 多连接表达式的并行查询优化是提高数据库性能的关键问题之一.提出了使用遗传算法来解决多连接表达式的并行查询优化问题.为了提高查询处理器的执行效率,采用启发式规则来搜索最优的多连接表达式并行调度执行计划.文中给出了详细的测试结果和性能分析.实验结果表明,结合启发式知识的遗传算法是解决多连并行查询优化的有效途径,对提高数据库的性能起到重要作用. 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.
出处 《软件学报》 EI CSCD 北大核心 2002年第2期250-257,共8页 Journal of Software
基金 国家教育部高等学校骨干教师资助项目 教育部高等学校优秀青年教师教学和科研奖励基金资助项目 教育部跨世纪人才基金资助项目~~
关键词 遗传算法 多连接表达式 并行调度 并行查询 优化 数据库 genetic algorithm multi-join expression query optimization parallel scheduling
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参考文献4

  • 1Chen, 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.
  • 2Steinbrunn, M., Moerkotte, G., Kemper, A. Heuristic and randomized optimization for the join ordering problem. VLDB Journal, 1997,6(3):191~208.
  • 3Wilschut, 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.
  • 4Chen, 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.

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