Title :
Adaptive techniques for distributed query optimization
Author :
C. Yu;L. Lilien;K. Guh;H. Templeton;D. Brill;A. Chen
Author_Institution :
Deportment of Electrical Engineering and Computer Science, University of Illinois at Chicago, Chicago, Illinois 60680
Abstract :
We propose new adaptive techniques for distributed query optimization. These techniques are divided into two groups: the ones that improve efficiency of query execution (directly) and the ones that improve cost estimations for query execution strategies. Some of the proposed techniques utilize semantic information and knowledge acquisition to adapt to the environment. The latter, in contrast to the former, is not a well-established idea. This is a disturbing fact since knowledge acquisition can give significant improvements in performance of a query optimization algorithm. Performing analysis manually is extrernely time consuming and tedious. Therefore, some learning capacity should be added to the system. Some knowledge acquisition techniques that result in adaptive (dynamic) adjustment to run-time changes are proposed.
Keywords :
"Estimation","Query processing","Data transfer","Heuristic algorithms","Qualifications","Knowledge acquisition","Algorithm design and analysis"
Conference_Titel :
Data Engineering, 1986 IEEE Second International Conference on
Print_ISBN :
978-0-8186-0655-7
DOI :
10.1109/ICDE.1986.7266209