Research On Multi-Join Query Optimization Of Distributed Database Based On Genetic Algorithm

In recent years, distributed database applications become wider and wider,but the problem of optimizing a multi-join query is not solved well in distributed database.as the extending of the distributed database,The problem of the multi-join query optimization largely influence the efficiency of the data query,but traditional optimization techniques for multi-join query are inadequate to support some of the database applications.The main content of this thesis is to improve on a genetic algorithm with encoding arbitary tree based on the character of optimization a multi-join query in distributed database.In order to compute the chromosome's fitness ,we give every chromosome's leave node a value.and put forward a new varietal operator,The operator can solve the problem of crossover operator generating new offspring. Results obtained by the author's test show that we get a set of values of genetic algorithm's paramater ,and use the values process the optimization a multi-join query .At last ,in testing experiment,the improve method is more efficient for query optimization.after query optimizationjts query cost is more lower than before.