Research on distributed database query optimization based on genetic algorithm

2012 ◽  
Author(s):  
Yan-qin Li ◽  
Cai-tian Zhang
Keyword(s):  
Genetic Algorithm ◽  
Query Optimization ◽  
Distributed Database ◽  
Database Query

Research on Distributed Database Query Optimization Based on Genetic Algorithm

2013 ◽  
Vol 380-384 ◽  
pp. 2850-2853
Author(s):  
Yan Qin Li ◽  
Cai Tian Zhang
Keyword(s):  
Genetic Algorithm ◽  
Query Optimization ◽  
Optimization Algorithm ◽  
Distributed Storage ◽  
Cost Model ◽  
Distributed Database ◽  
Optimization Method ◽  
Performance Comparison ◽  
Database Query ◽  
Genetic Method

In order to improve the performance of the query optimization for the distribute database, an improved query optimization algorithm was proposed based on the genetic algorithm. The query execution cost model based on the genetic algorithm was proposed in this paper. The distributed database was emerged in the 70's of the last century and developed with the progress of the computer technology and network technology, the distributed database was the database system which is distributed storage dispersedly in physics and with centralized processing in mathematic logic. Because the storage points were not uniform, the structure of the distributed database is much more complicated than the centralized database. Both the genetic algorithm and the dynamic exhaustive planning algorithm were taken in the query simulation for the performance comparison. The result shows that the genetic query optimization method in this paper has better performance in the distributed database query application. The case study and the simulation result show that the algorithm can get a satisfactory optimization result in a few iterations and the query optimization algorithm based on the genetic method has nice performance of the query optimization property, and the consumption and costs of the query is reduced to the minimum. The method which this paper proposed has good application performance and is valuable to put into practice.

Research on Query Optimization Technology in Distributed Database

2012 ◽  
Vol 433-440 ◽  
pp. 3335-3339
Author(s):  
Bo Zhu Wu
Keyword(s):  
Query Processing ◽  
Query Optimization ◽  
Distributed Database ◽  
Query Time ◽  
Processing Technology ◽  
Database Query ◽  
Processing Program ◽  
Depth Study ◽  
Database Query Processing ◽  
Query Efficiency

Through the in-depth study of the existing distributed database query processing technology, this paper proposes a distributed database query processing program. This program optimizes the existing query processing, stores the commonly used query results according to the query frequency, to be directly used by the subsequent queries or used as intermediate query results, thus avoiding possible transmission of a large number of data, thereby reducing the query time and improving query efficiency.

Research of Query Optimization Based on Improved Quantum Particle Swarm Optimization Algorithm in Distributed Database

2012 ◽  
Vol 532-533 ◽  
pp. 1365-1369
Author(s):  
Fu Min Liu ◽  
Jing Yong Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Query Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Quantum Particle ◽  
Particle Swarm ◽  
Distributed Database ◽  
Database Query ◽  
Swarm Optimization ◽  
Quantum Particle Swarm Optimization

Database query optimization is a very complicated issue, also is the key influencing factor in database systems performance. Database query operation efficiency is one of the key factors that affect system response time. Therefore, how to improve the efficiency of database query system becomes particularly important. This paper, on the basis of the advantages of Quantum particle swarm optimization algorithm, proposes distributed database query optimization methods based on Quantum particle swarm optimization algorithm, and improves algorithm. Simulation comparison experiments show that Quantum particle swarm optimization algorithm can improve the efficiency of the distributed database query, and is an effective way to solve the optimization of distributed database query.

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