Chinese Cognitive Database Query Optimization Method And Its Application

Over the last decade the impact of functional brain imaging on neuroscience has been considerable, advancing scientific understanding of cognitive processes and the neural substrates that underlie them. Neuroimaging techniques have the potential to identify the systems of brain areas responsible for human memory and abstract thinking or to identify elements of the causes for human disorders such as dyslexia and schizophrenia. In recent years, the research potential of functional magnetic resonance imaging (fMRI) has led to a steady and predictable rise in the number of laboratories conducting studies designed to explore the landscape of cognitive function. Still, however, the cost of fMRI experimentation and the infrastructure involved in acquiring the data remains prohibitive for many academic institutions. In the database of Chinese Human Brain, the system needs to execute many query plans on huge datasets. Because a query plan could be executed in a long period which doesn't satisfy the users' demand, we must design an effective query optimization plan to improve the response time of the system. The theory of the query optimization consists of the database statistic profile, multi-join query optimization and distributed group operation etc.Firstly, this paper outlines the structure of the Chinese human brain database and analyses the problem of the data mining. Secondly, this paper deeply studies the query optimization problem. This paper introduces the theory of statistic profile into the application of Chinese human brain database, which effectively solves the difficulty of data collecion. With the incredible increase of query search space, the database system often needs to execute a great amount of JOIN queries in a short time. This paper gives an improved genetic algorithm, analyzing the speed and convergence of the algorithm. Experiment shows that this improved algorithm can solve the problem mentioned above. Another important issue is how to control the group operations. This paper proposes two algorithms based on the structure of the data warehouse, which can reduce the cost and increase the performance of the system.The theory of query optimization proposed by this paper has high research and application value. It can easily be used into other database system projects.