基于大纲的数据流自适应聚集算子的实现  

Implementation of adaptive aggregate operator based on synopsis

作　　者：田海生[1] 陈立军[2] 

机构地区：[1]中国科学院研究生院,北京100039 [2]北京大学计算机系,北京100871

出　　处：《计算机应用》2007年第10期2383-2387,共5页journal of Computer Applications

摘　　要：采用基于大纲的数据流自适应聚集算子的批处理(Batchingprocessing)算法处理数据流,Batching算法能够随着流速的变化动态调整自己的执行策略,以便更好地利用有限的系统资源提供尽可能好的查询质量,并且可以在Batching算法的基础上根据不同的流聚集算子提出相应的优化算法,进一步提高查询质量并真正达到或接近实时查询。实验结果已在北大Argus数据流管理系统中得到成功应用。In this article we proposed a Batching Processing algorithm based synopsis, which can adjust its processing policy according to the arriving data rates in order to achieve better query quality under limited system resource. In addition, according to the characteristics of aggregate we can use some optimized algorithm to gain real time or nearly real time query results. We present prototype-based experimental results on the Argus DSMS to characterize the efficiency and effectiveness of our approach at the end of this paper.

关 键 词：数据流管理系统 数据流 自适应 批处理 聚集算子 滑动窗口 

分 类 号：TP311.131[自动化与计算机技术—计算机软件与理论]