Multi-dimensional query optimization algorithm for bitmap index with binning

2010 ◽  
Vol 30 (8) ◽  
pp. 2013-2016 ◽  
Author(s):  
Li-ming WANG ◽  
Xiao CHENG ◽  
Yu-mei CHAI
Keyword(s):  
Query Optimization ◽  
Optimization Algorithm ◽  
Bitmap Index

A PSO-Based Web Document Query Optimization Algorithm

2006 ◽  
pp. 609-615 ◽  
Author(s):  
Ziqiang Wang ◽  
Xin Li ◽  
Dexian Zhang ◽  
Feng Wu
Keyword(s):  
Query Optimization ◽  
Optimization Algorithm ◽  
Web Document

ADAPTIVE QUERY OPTIMIZATION IN DYNAMIC DATABASES

1998 ◽  
Vol 07 (01) ◽  
pp. 1-30
Author(s):  
MIN J. YU ◽  
P. C-Y. SHEU
Keyword(s):  
Query Optimization ◽  
Optimization Algorithm ◽  
Optimal Solution ◽  
Complex Objects ◽  
Access Path ◽  
Dynamic Databases ◽  
Partial Plan ◽  
Data Modifications

This paper addresses the problem of query optimization for databases in which objects frequently change their values. A greedy, adaptive query optimization algorithm is proposed to evaluate relational queries and queries containing complex objects. Rather than contructing a full plan for an access path and executing it, the algorithm constructs a partial plan, executes it, updates the statistics, and constructs a new partial plan. Since a partial plan is constructed based on the latest statistics, the algorithm is adaptive to data modifications and errors from the statistics. It is proved that the algorithm can produce an optimal solution for a class of queries. Furthermore, experiments show that the overhead associated with the algorithm is negligible and the algorithm is efficient for other cases.

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.

Sign in / Sign up

Export Citation Format

Share Document