摘要
分布式空间查询优化是提高分布式空间数据库性能的关键问题之一。本文针对区域分片的数据分布特征,在已有的跨边界连接转化及优化规则基础上,依据片段连接的分配规则将全局查询映射为局部片段连接,提出不同站点上交矩形大面积优先的任务排序策略以及基于子任务的代价模型的分布式并行查询动态任务调整方法。经过实验表明,该方法不仅进一步提高了分布式空间查询的效率,有效解决分布式空间并行查询的负载平衡问题。
Distributed query optimization is one of key issues to improve the performance of distributed spatial database. This paper aims at proposing a hybrid task schedule method combining with the static assignment and the dynamic adjustment. According to the characteristics of zonal fragmentation and the existing rules of transformation and optimization based on cross-border topological join, firstly, the fragment joins in each site are performed by the larger area of FMBR fit first. Then these tasks are further readjusted between all sites based on the cost model of query tasks. At last, the result of experiment shows that this method not only further improves the efficiency of the distributed spatial query, but also solves the load-balancing problem in effectively.
出处
《科技通报》
北大核心
2014年第1期110-116,共7页
Bulletin of Science and Technology
关键词
分布式空间数据库
空间查询优化
并行调度
区域分割分片
distributed spatial database
spatial query optimization
parallel schedule
zonal fragmentation
