DocumentCode :
3292397
Title :
Clustering-Based Dynamic Materialized View Selection Algorithm
Author :
Gong, An ; Zhao, Weijing
Author_Institution :
Coll. of Comput. & Commun. Eng., China Univ. of Pet., Beijing
Volume :
5
fYear :
2008
fDate :
18-20 Oct. 2008
Firstpage :
391
Lastpage :
395
Abstract :
With the base of proposing materialized view similarity function, the paper proposes clustering-based dynamic materialized view selection algorithm. It firstly clusters materialized views, and then dynamically adjusts materialized view set. So, it eliminates the "jitter", which dynamic materialized view selection algorithm generally has. The experimental results show that the algorithm not only improves the overall query response performance, but also reduces the computational cost which will bespent during updating materialized view.
Keywords :
data warehouses; pattern clustering; clustering-based dynamic materialized view selection algorithm; computational cost reduction; data warehouse; similarity function; Clustering algorithms; Computational efficiency; Data warehouses; Educational institutions; Frequency; Fuzzy systems; Heuristic algorithms; Jitter; Knowledge engineering; Petroleum; clustering; data warehouse; dynamic selection algorithm; materialized view;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on
Conference_Location :
Jinan Shandong
Print_ISBN :
978-0-7695-3305-6
Type :
conf
DOI :
10.1109/FSKD.2008.96
Filename :
4666556
Link To Document :
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