A novel coral reefs optimization algorithm for materialized view selection in data warehouse environments

2019 ◽  
Vol 49 (11) ◽  
pp. 3965-3989
Author(s):  
Hossein Azgomi ◽  
Mohammad Karim Sohrabi
2010 ◽  
Vol 29-32 ◽  
pp. 1133-1138 ◽  
Author(s):  
Li Juan Zhou ◽  
Hai Jun Geng ◽  
Ming Sheng Xu

A data warehouse stores materialized views of data from one or more sources, with the purpose of efficiently implementing decision-support or OLAP queries. Materialized view selection is one of the crucial decisions in designing a data warehouse for optimal efficiency. The goal is to select an appropriate set of views that minimizes sum of the query response time and the cost of maintaining the selected views, given a limited amount of resource, e.g., materialization time, storage space, etc. In this article, we present an improved PGA algorithm to accomplish the view selection problem; the experiments show that our proposed algorithm shows it’s superior.


2014 ◽  
Vol 989-994 ◽  
pp. 1955-1958
Author(s):  
Lei Ma

Materialized view is an important topic in data warehouse research, and also affects the query efficiency and maintenance cost. The disk-space view-selection problem is to select a set of materialized views for the purpose of minimizing the total query processing cost and the total maintenance cost. In this paper we introduce evolutionary algorithm using stochastic ranking algorithm, which can enable materialized view selection under disk-space constraint. The algorithm improve the stochastic ranking algorithm, which can find a near-optimal feasible solution. This paper use the algorithm in Police data warehouse.


2011 ◽  
Vol 52-54 ◽  
pp. 978-983
Author(s):  
Li Juan Zhou ◽  
Xiao Xu He ◽  
Kang Li

This paper designed a data warehouse model of agricultural production. And it built an effective and viable agricultural production data warehouse, by using some key technologies: multidimensional data analysis, cube, materialized view selection, materialized view maintenance. Finally, it provided a solution for the effective management and maintenance problems about high-capacity heterogeneous data.


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