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基于滑动窗口的在线数据流增量聚集查询
引用本文:刘学军,胡 平,徐宏炳,董逸生.基于滑动窗口的在线数据流增量聚集查询[J].计算机工程,2007,33(21):45-46,4.
作者姓名:刘学军  胡 平  徐宏炳  董逸生
作者单位:[1]南京工业大学信息科学与工程学院,南京210009 [2]东南大学计算机科学与工程学院,南京210096
摘    要:增量查询技术由于能有效处理大量、快速、源源不断到达的数据流,因此备受关注。滑动窗口是动态数据流环境下的一种典型的窗口类型。该文研究了基于滑动窗口的数据流聚集查询,提出了一种新的增量聚集查询算法,采用了多种增量计算方法和查询共享技术,实现了多窗口资源共享。实验验证了该方法的有效性。

关 键 词:数据流  聚集查询  增量计算  窗口共享
文章编号:1000-3428(2007)21-0045-02
修稿时间:2007-04-09

Incremental Aggregation Query over Online Data Streams Based on Sliding Window
LIU Xue-jun,HU Ping,XU Hong-bing,DONG Yi-sheng.Incremental Aggregation Query over Online Data Streams Based on Sliding Window[J].Computer Engineering,2007,33(21):45-46,4.
Authors:LIU Xue-jun  HU Ping  XU Hong-bing  DONG Yi-sheng
Affiliation:1. College of Information Science and Engineering, Nanjing University of Technology, Nanjing 210009; 2. College of Computer Science and Engineering, Southeast University, Nanjing 210096
Abstract:In order to deal with the huge amounts of data and increasingly stringent response-time requirements, incremental queries processing has recently emerged as a possible solution. Sliding window is one of the most classical windows in dynamic data streams environment. This paper studies aggregation query whith is an important class of continuous operators, and proposes a kind of novel aggregate query algorithms from sliding window over data streams. Many incremental computation approaches and resource sharing techniques in sliding-window aggregations are introduced. Experiments show the feasibility and effectiveness of the approach.
Keywords:data stream  aggregation query  incremental computation  window sharing
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