The Design And Implementation Of Distributed Query Optimization In Donation Administration System

With the development of database technology, the application of distributed database becomes more and more wide. The distributed data query becomes more difficult and complex because of distribution and redundancy of data in distributed database systems. Therefore, how to query data more effectively is an important problem in distributed database systems, and it is also the problem which will be studied in this paper.Domestic and international experts and scholars have done a lot of research works on distributed query optimization technology, and some important results have been achieved. A number of classic distributed query optimization algorithms have been obtained, such as the optimization algorithm based on relation algebra equivalent transformation, the optimization algorithm based on the semi-joint, SDD₁ algorithm, mountain climbing algorithm, simulated annealing algorithm and genetic algorithm, etc.This paper is based on the project of donation management software developing and network system integration of Chinese Red Cross. In this paper, we present the relevant concepts of distributed database firstly; then give an introduction to the process of distributed query. We give emphasis to the analysis and research of the optimization algorithm based on relation algebra equivalent transformation and the one based on semi-joint, SDD₁ algorithm, genetic algorithm. Then, by combining the genetic algorithm and semi-joint algorithm together, the semi-joint-genetic algorithm under the condition of multi-link is proposed. The proposed algorithm may be used to construct balance joint tree based on query figure which is thought as a chromosome, and the chromosome chain is obtained by traversing the balance joint tree after the sequence. Then the genetic algorithm is applied into the population constructed by all chromosomes, and an execution scheme is achieved after selection, crossover and mutation operation, then the execution scheme is optimized further by using the semi-joint algorithm. In the execution process of the proposed algorithm, the opportunity of parallel execution is increased greatly, and the query efficiency is improved further.