首页> 外文期刊>Concurrency, practice and experience >Join query optimization in the distributed database system using an artificial bee colony algorithm and genetic operators
【24h】

Join query optimization in the distributed database system using an artificial bee colony algorithm and genetic operators

机译:使用人工蜂殖民地算法和遗传算子加入分布式数据库系统中的查询优化

获取原文
获取原文并翻译 | 示例
           

摘要

As the main factor in the distributed database systems, query optimization is aimed at finding anoptimal execution plan to reduce the runtime. In such systems, because of the repeated relationson various sites, the query optimization is very challenging. Moreover, the query optimizationissue with large-scale distributed databases is an NP-hard problem. Therefore, in this paper,an Artificial Bee Colony Algorithm based on Genetic Operators (ABC-GO) is proposed to finda solution to join the query optimization problems in the distributed database systems. TheABC algorithm has the global–local search capabilities and genetic operators to create newcandidate solutions for improving the performance of the ABC algorithm. The obtained resultshave shown that the cost of the query evaluation is minimized and the quality of Top-K queryplans is improved for a given distributed query. Moreover, this method decreases the overhead.However, it needs a longer execution time.
机译:作为分布式数据库系统中的主要因素,查询优化旨在找到一个最佳执行计划减少运行时。在这样的系统中,因为重复的关系在各种网站上,查询优化非常具有挑战性。此外,查询优化具有大规模分布式数据库的问题是一个NP难题问题。因此,在本文中,提出了一种基于遗传算子(ABC-Go)的人造蜂殖民地算法加入分布式数据库系统中查询优化问题的解决方案。这ABC算法具有全球本地搜索功能和遗传运营商以创建新的提高ABC算法性能的候选解决方案。获得的结果已经表明查询评估的成本最小化,顶级k查询的质量对于给定的分布式查询,改进了计划。此外,该方法降低了开销。但是,它需要更长的执行时间。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号