摘要
数据库查询优化技术对提高数据库的查询效率,增强数据库性能有重要作用。针对大型数据库中多表连接查询效率低的问题,提出了一种基于粒子群算法的改进查询优化算法。针对多表连接查询的特征,对粒子采用树形编码的方式,并提出了一种计算数据库查询执行代价的模型。实验表明,使用粒子群算法优化后的查询策略比原始查询策略的查询执行代价低,有效提高了系统的查询效率。
Database query optimization techniques plays an important role in the query efficiency of the database and enhancement of database performance.Aiming at the problem of Low efficiency in a large database of multi-table join query, this thesis proposes an improved query optimization algorithm based on particle swarm optimization algorithm. According to the characteristics of the multi-table join query, using tree coding method to theparticle, and put forward the calculation of database query execution cost model. Experiments show that use of particle swarm algorithm optimized query strategy has lower cost than the original query strategy, the improved model effectively improve the query efficiency of the system.
作者
申华
SHEN Hua （South China Institute of Software Engineering, Guangzhou University, Guangzhou 510990,China）
出处
《电脑知识与技术》
2014年第9期5806-5809,共4页
Computer Knowledge and Technology
关键词
查询优化
粒子群算法
执行代价估计
树形编码
query optimization
particle swarm optimization
execution cost estimation
tree encoding
