【作者】 赵秀丽；

【导师】 顾军华；

【作者基本信息】 河北工业大学 ， 计算机应用技术， 2007， 硕士

【摘要】 随着计算机技术在各个行业的普及应用,承载信息的数据随着时间的推移而不断增长,人们已经不再满足于日常操作型的事务处理,而是更加关注能否从纷繁复杂、大量沉淀的数据环境中分析挖掘到有用的决策信息,及时做出正确的分析与决策,使这些历史的业务数据变得有意义,因此数据仓库的概念诞生了。数据仓库是一个面向主题的、集成的、相对稳定的、随时间变化的、用于支持管理决策的数据集合。它维护着海量的数据,支持复杂的查询形式,通常需要访问大量数据,而一个决策支持系统必须对查询做出快速响应,因此,数据仓库要具有较高的性能。物化视图是提高数据仓库性能的一项重要技术,它使得查询效率大大提高,但是物化视图的保存会占用一定的存储空间,而且为了与基表数据保持一致还需要一定的维护开销。这就需要考虑物化视图的选择,要让物化视图尽量少地占用存储空间的情况下尽量大地提高查询效率,这就是本文要解决的重点问题。本文首先对物化视图选择问题进行描述,并建立了问题的数学模型。其次,介绍了几种现有的求解物化视图选择问题的方法,在此基础上提出了物化视图蚁群选择算法ACS-VSP,作为本文的创新点。通过仿真实验,将ACS-VSP的求解性能和已经成功求解过该问题的遗传算法的求解性能进行比较,得出结论:蚁群算法的求解性能优于遗传算法。再次,结合实际应用中查询分布随着时间的推移发生变化的特点,提出了一种物化视图动态调整算法。该算法能够使物化视图集合更好的适应用户的需求,并极大地提高系统对用户查询的响应速度。最后,将理论研究成果应用到学生成绩查询分析系统中,从而证明所提出的物化视图选择算法的实用价值。更多还原

【Abstract】 With the application of computer technology in all areas, the data carrying information grows with the passage of time. People are no longer satisfied with the daily operation of the business, but more concerned about whether they can find useful information for decision-making from the complicated, large data environment, timely make the correct decision, which make these data become meaningful. So the data warehouse concept was born.A data warehouse is a subject-oriented, integrated, relatively stable, time-variant data set to support decision making.It maintains a large amount of data, supports complex queries, and a decision support system should make rapid response to users, therefore, the data warehouse should have high performance. Materialized view is an important technology to improve the performance of data warehouse, it makes the efficiency of queries greatly increased, but the materialized view will take up some storage space and also need some maintenance cost. So, we must consider materialized view selection problem. Materialized views occupy less storage space. At the same time, the efficiency of queries is improved larger, which is the focus of this paper.First, the paper describes materialized view selection problem, establishes the mathematical model of the problem and introduces several existing materialized view selection methods. On this basis, Ant colony system (ACS) method is proposed to solve this problem, as the innovation. Experiments proved that the performance of ant colony algorithm is better than the genetic algorithm. Then, according to the actual applications, the query distribution is changed with the passage of time, a materialized view dynamic adjustment algorithm is proposed. The algorithm can greatly make materialized view set adapt to the needs of users and greatly improve the speed of the system response to users. Finally, the theoretical research results are applied to student score query and analysis system to prove the practical value of the Materialized View selection algorithm.更多还原