Parallel query optimization techniques for multi-join expressions based on genetic algorithm

被引：0
|
作者：
Cao, Yang [1 ]
Fang, Qiang [1 ]
Wang, Guo-Ren [1 ]
Yu, Ge [1 ]
机构：
[1] Sch. of Info. Sci. and Eng., Northeastern Univ., Shenyang 110004, China
来源：
Ruan Jian Xue Bao/Journal of Software | 2002年 / 13卷 / 02期
关键词：
Genetic algorithms - Heuristic methods - Information retrieval - Optimization - Parallel processing systems - Query languages - Scheduling - Trees (mathematics);
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The parallel query optimization for multi-join expressions is one of the key factors to improve the performance of database systems. 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 heuristic 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.
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页码：250 / 257
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