基于粒子群算法的数据库查询优化

Optimization of database query application research based on particle swarm algorithm

研究粒子群算法在数据库查询优化中的应用问题。为了解决大型数据库信息检索困难、查询效率低的问题,提出了一种基于粒子群算法优化数据库查询技术方案。算法提出了一种数据库查询执行计划代价模型,主要包括了查询多链接次序以及副本的选择问题,准确定义了数据库查询执行代价,采用提出的粒子群算法来优化并求解该执行代价问题,从而使得分组数目更少、数据定位更精确。实例验证结果表明,通过属性表现和违规行为任何教师都可以被准确定位,减少了分组,为数据库查询提供了优化。

This paper studied on particle swarm algorithm in database query optimization problems in application. In order to solve large-scale database information retrieval difficult, query efficiency low at the end of the problem, this paper proposed one kind based on the particle swarm optimization algorithm for database query technology. The algorithm mainly proposed a database query execution plan cost model, including the query multiple link order and replica selection problem, accurate definition of database query execution costs, then using the particle swarm algorithm to optimize the execution cost and solving problems, so that the data packet being fewer in number and more accurate positioning. The final test results show that, verified any tea-chefs through attribute and irregularities can be accurate positioning, reduces the packet, for the database query provides optimization.