I/O parallelism is considered to be a promising approach to achieving highperformance in parallel data warehousing systems where huge amounts of data and complex analyticalqueries have to be processed. This paper prop...I/O parallelism is considered to be a promising approach to achieving highperformance in parallel data warehousing systems where huge amounts of data and complex analyticalqueries have to be processed. This paper proposes a parallel secondary data cube storage structure(PHC for short) to efficiently support the processing of range sum queries and dynamic updates ondata cube using parallel computing systems. Based on PHC, two parallel algorithms for processingrange sum queries and updates are proposed also. Both the algorithms have the same time complexity,O(log^d n/P). The analytical and experimental results show that PHC and the parallel algorithms havehigh performance and achieve optimum speedup.展开更多
传统网络环境和P2P环境中,客户端向OLAP服务器提交OLAP查询,并从服务器获取查询结果,OLAP服务器的负载将随着客户端的增加而急剧增加。设计了一种基于P2P(Peer-to-Peer,点对点技术)技术的DQDC(Distributed Query Data Cube,多维数据集...传统网络环境和P2P环境中,客户端向OLAP服务器提交OLAP查询,并从服务器获取查询结果,OLAP服务器的负载将随着客户端的增加而急剧增加。设计了一种基于P2P(Peer-to-Peer,点对点技术)技术的DQDC(Distributed Query Data Cube,多维数据集的分布式查询)算法,实现P2P网络中语义级的多节点Data Cube数据共享,从而提高系统整体的决策分析性能。展开更多
文摘I/O parallelism is considered to be a promising approach to achieving highperformance in parallel data warehousing systems where huge amounts of data and complex analyticalqueries have to be processed. This paper proposes a parallel secondary data cube storage structure(PHC for short) to efficiently support the processing of range sum queries and dynamic updates ondata cube using parallel computing systems. Based on PHC, two parallel algorithms for processingrange sum queries and updates are proposed also. Both the algorithms have the same time complexity,O(log^d n/P). The analytical and experimental results show that PHC and the parallel algorithms havehigh performance and achieve optimum speedup.
文摘传统网络环境和P2P环境中,客户端向OLAP服务器提交OLAP查询,并从服务器获取查询结果,OLAP服务器的负载将随着客户端的增加而急剧增加。设计了一种基于P2P(Peer-to-Peer,点对点技术)技术的DQDC(Distributed Query Data Cube,多维数据集的分布式查询)算法,实现P2P网络中语义级的多节点Data Cube数据共享,从而提高系统整体的决策分析性能。
