Query optimization strategies and implementation based on distributed database

Author(s):  
Lin Xue
2012 ◽  
Vol 433-440 ◽  
pp. 3335-3339
Author(s):  
Bo Zhu Wu

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.


2018 ◽  
Vol 14 (4) ◽  
pp. 466-476
Author(s):  
Slamet Sudaryanto Nurhendratno ◽  
Sudaryanto ◽  
Fikri Budiman ◽  
Maryani Setyowati

2011 ◽  
Vol 4 ◽  
pp. 156-165 ◽  
Author(s):  
Peter Paul Beran ◽  
Werner Mach ◽  
Erich Schikuta ◽  
Ralph Vigne

2012 ◽  
Vol 532-533 ◽  
pp. 1365-1369
Author(s):  
Fu Min Liu ◽  
Jing Yong Wang

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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