数据仓库中物化视图技术研究

Lijuan Zhou, M. Xu, Qian Shi, Zhongxiao Hao
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引用次数: 3

摘要

随着企业对决策支持信息的需求和计算机技术的快速发展,数据仓库技术应运而生。数据仓库是从多个(可能是异构的)自治的分布式数据库中收集的信息的存储库。存储在数据仓库中的信息以视图的形式存在,称为物化视图。数据仓库的设计是研究和发展数据仓库的核心问题之一。数据仓库的选择是数据仓库设计中最重要的决策之一。选择视图以实现对建立和运行数据仓库的效率以及总成本的影响。因此,我们开发了一种算法来选择一组视图来实现数据仓库,以便在给定查询响应时间的约束下最小化视图维护的总成本。我们称之为查询成本视图选择问题(QC_VSP)。本文首先提出了查询成本视图选择问题模型。其次,给出了QC_VSP的三种算法;为了求解它,我们给出了view_node_matrix。第三,采用实验模拟。结果表明,该算法在实际应用中效果较好。我们实现了我们的算法,算法的性能研究表明,所提出的算法提供了一个最优解。最后,我们讨论了算法的观察行为。我们还指出了未来研究的一些重要问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Materialized Views Technology in Data Warehouse
With the needs of decision-support information of enterprise and the fast development of computer technologies data warehouse technology come out. The data warehouse is a repository of information collected from multiple, possibly heterogeneous, autonomous, distributed databases. The information stored at the data warehouse is in form of views referred to as materialized views. The design of data warehouse is one of the core research problems in studying and evolution of data warehouse. One of the most important decisions in design of data warehouse is the data warehouse selection. Selecting views to materialize impacts on the efficiency as well as the total cost of establishing and running a data warehouse. So, we develop algorithms to select a set of views to materialize in data warehouse in order to minimize the total view maintenance cost under the constraint of a given query response time. We call it query cost view selection problem (QC_VSP). In this paper, First, we propose query cost view selection problem model. Second, we give three algorithms for QC_VSP; we give view_node_matrix in order to solve it. Third, experiment simulation is adopted. The results show that our algorithm works better in practical cases. We implemented our algorithms and a performance study of the algorithms shows that the proposed algorithm delivers an optimal solution. Finally, we discuss the observed behavior of the algorithms. We also identify some important issues for future investigations.
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