计算机应用 ›› 2010, Vol. 30 ›› Issue (12): 3371-3373.

• 数据库与数据挖掘 • 上一篇    下一篇

基于社区划分的联机分析处理查询优化方案

何昭青1,周攀2,杨科华3   

  1. 1. 湖南长沙第一师范学校信息技术系
    2.
    3. 湖南大学计算机与通信学院
  • 收稿日期:2010-05-25 修回日期:2010-07-20 发布日期:2010-12-22 出版日期:2010-12-01
  • 通讯作者: 何昭青

Community-partition-based online analytical processing query optimization

  • Received:2010-05-25 Revised:2010-07-20 Online:2010-12-22 Published:2010-12-01
  • Contact: HE Zhao-Qing 何昭青

摘要: 针对P2P环境下的联机分析处理(OLAP)查询节点数目不断增加时,易造成网络拥塞、查询效率降低的问题,提出一种基于社区划分的OLAP查询优化方案。该方案构建一个虚拟的社区网,并在此结构上设计了一种基于社区划分的多维数据集(CPDS)的OLAP查询优化算法。实验结果表明,该算法能有效避免因网络节点数目递增而导致的网络负载加剧问题,能有效地减少网络拥塞,优化了OLAP的查询效率,进一步提高P2P环境下OLAP的决策分析性能。

关键词: 联机分析处理, 数据立方体, 点对点网络, 虚拟社区

Abstract: In the Peer-to-Peer (P2P) environment, when the number of nodes of On-Line Analysis Processing (OLAP) query increase, network congestion will be aggravated and OLAP query efficiency will be reduced. Therefore, this paper proposed an optimized OLAP query method based on community partition. A visual community network was constructed with the method, and an algorithm of Community Partition Data-cube Search (CPDS) was designed in this structure. The results of experiment show that this algorithm can effectively avoid increasing network burden, when network OLAP nodes increase. Therefore, this method reduces congestion of network and optimizes efficiency of OLAP query, which improves the performance of decision-analysis of OLAP in P2P environment.

Key words: On-Line Analysis Processing (OLAP), data cube, P2P network, visual community