摘要
与传统关系数据库不同,数据流管理系统主要处理并发的连续查询.由于查询可能随时增删,所以其主要关注适合查询增删的并发连续查询优化,而不是单条查询优化.提出适合频繁增删查询环境下的数据流窗口连接优化算法.对于新注册的查询以类似最小生成树算法写出数据流的探测序列,然后在不更改其他查询探测序列顺序的情况下尽量合并,减少重复计算.注册或删除查询并不影响其他的查询计划,不需要执行繁琐的查询计划迁移.理论分析和实验证明,该算法简单,优化性能在可接受的范围内,尤其适合查询更新频率较高的系统.
Different from traditional database systems, a data stream management system (DSMS) mainly processes concurrently continuous queries. Because queries would be added or deleted at any moment, the focus of query optimization for a DSMS is to find an algorithm that adapts to add and delete queries frequently. Furthermore, as window join is one of the highest cost operations of continuous queries, window join optimization will notably improve a DSMS performance. Therefore, a window join optimization algorithm is proposed. For each new query, all the probing sequences of each data stream are built like minimum spanning tree algorithm. To complete concurrent window joins, the probing sequences which start from a same stream should be built into one tree whose root node is the stream. If prefixes of probing sequences are the same, they can be grouped into one branch of the tree to reduce the duplicate calculation. Because the algorithm does not execute cost comparison of grouping common join predicate, adding or deleting a query does not influence other query not needed. Theoretics and experimental results show performance is acceptable. plans, and complicated dynamic plan migration is that the algorithm is simple and optimization
出处
《计算机研究与发展》
EI
CSCD
北大核心
2007年第6期1000-1007,共8页
Journal of Computer Research and Development
基金
江苏省高技术基金项目(BG2004034)
江苏省2004年度研究生创新计划基金项目(xm04-36)~~
关键词
窗口连接
多查询优化
最小生成树
连续查询
window join
multiple query optimization
minimum spanning tree
continuous query