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Karimi Mosadegh A, Daneshpour N. Increasing the Speed of Incremental View Maintenance Using the Cuckoo Algorithm. JSDP. 2017; 14 (3) :113-126
URL: http://jsdp.rcisp.ac.ir/article-1-460-en.html
Shahid Rajaee Teacher Training University
Abstract:   (913 Views)

Data warehouse is a repository of integrated data that is collected from various sources. Data warehouse has a capability of maintaining data from various sources in its view form. So, the view should be maintained and updated during changes of sources. Since the increase in updates may cause costly overhead, it is necessary to update views with high accuracy. Optimal Delta Evaluation method is one of the incremental view maintenance method that can maintain materialized views efficiently in the data warehouse environment. This method is one of the incremental view maintenance grouping methods. In this method incremental maintenance expression is divided into groups, as a result access to some repeated relations is minimized. As a final result, Optimal Delta Evaluation method can minimize the total accesses to relations. The algorithm proposed in this paper, is the combination of optimal Delta Evaluation with Cuckoo heuristic Algorithm that reduces maintenance time of views and thus speeds up this process. Cuckoo optimization algorithm begins with an initial population. Trying to survive the Cuckoo makes the base to optimize the algorithm. The results show that the Cuckoo algorithm is faster in order to update its incremental views compared with previous methods.
 

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Type of Study: Research | Subject: Paper
Received: 2015/11/20 | Accepted: 2016/10/29 | Published: 2018/01/29 | ePublished: 2018/01/29

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