Distributed Database Query Optimization Techniques

Databases are used widely in many fields. Because Centralized Database has many innate disadvantages when applied to Internet, the application of Distributed Database gets more and more popular. With the development of computer networks and information technology, Distributed Database Systems has become one of the research hotspots of computer science.However, there are still many challenging problems in this field that attract many researchers. It is well known that the performance of a database relies heavily on the efficiency of query execution. To obtain efficient query execution, optimization is the most important step. Many researches have carried on research on this subject by going deep into the bottom of Query Engine. Many mature technologies on this level have been brought out, such as the relational algebra law, the improved logical query plan, the cost estimation of operation, the selective plan based on cost and order of joint, etc. Although many methods have been tried out, no remarkable result or noteworthy technology has come to reality because of complexity of data decomposition and network effects.This article concentrates on how to optimize the global query at an upper level: database-level distribution. Based on statistical methods, the optimizing algorithm try to find a light-loaded server that can process the query with less cost. In fact, it uses the historical records of previous execution. Then, according to some algorithm, the optimizing processor can determine which node among the system is the best to execute this query. The whole system is based on MYSQL, an open source database, which is widely used in Internet application.The balance of this paper is organized as following: the first chapter reviews the progress of the Distributed Database. The second chapter discusses the conventional query optimizing technologies. In third chapter, we introduce the prototype of DP-SQL and its major features. The forth chapter discusses the optimization of Distributed Database in details. Then, in the next chapter, the implementation details are discussed. The last chapter analyzes the algorithm performance, and then draws the conclusion.