Denormalization strategies for data retrieval from data warehouses

被引：27
|
作者：
Shin, Seung Kyoon
Sanders, G. Lawrence
机构：
[1] Univ Rhode Isl, Coll Business Adm, Kingston, RI 02881 USA
[2] SUNY Buffalo, Sch Management, Dept Management Syst & Sci, Buffalo, NY 14260 USA
来源：
DECISION SUPPORT SYSTEMS | 2006年 / 42卷 / 01期
关键词：
database design; denormalization; decision support systems; data warehouse; data mining;
D O I：
10.1016/j.dss.2004.12.004
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this study, the effects of denormalization on relational database system performance are discussed in the context of using denormalization strategies as a database design methodology for data warehouses. Four prevalent denormalization strategies have been identified and examined under various scenarios to illustrate the conditions where they are most effective. The relational algebra, query trees, and join cost function are used to examine the effect on the performance of relational systems. The guidelines and analysis provided are sufficiently general and they can be applicable to a variety of databases, in particular to data warehouse implementations, for decision support systems. (c) 2004 Elsevier B.V All rights reserved.
引用
收藏
页码：267 / 282
页数：16
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