Paper Information

Journal:   TABRIZ JOURNAL OF ELECTRICAL ENGINEERING   SUMMER 2016 , Volume 46 , Number 2 (76); Page(s) 97 To 108.
 
Paper: 

MATERIALIZED VIEW SELECTION USING HYBRID CULTURAL SEARCH ALGORITHM

 
 
Author(s):  SHAYEGH BOROUJENI P., DANESHPOUR N.
 
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Abstract: 

A data warehouse stores a large amount of data, which are usually used in decision support systems. Response time of these systems is too high because of their huge data. Since these systems are generally used by organization’s supervisors, reducing this response time is important. One of the major solutions for this problem is view materialization. Materialization of all views is impossible according to the constraint on memory space and the cost of maintenance these views. So, it is needed to select proper views to be materialized. Selection of these views is a kind of searching in a huge space that is considered as NP hard problem. Several methods are proposed to address this problem until now. Evolutionary algorithms are mostly used in solving MV problems. In this paper, Hybrid Cultural algorithm is used to select N top views among all views. Experiments show that this proposed algorithm has lower cost and higher speed than genetic algorithm, cuckoo search algorithm and Differential algorithm.

 
Keyword(s): DATA WAREHOUSE, MATERIALIZED VIEW, HYBRID CULTURAL ALGORITHM
 
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