Research On Materialized Views Selection In Data Warehouse

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.