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Referential Horizontal Partitioning Selection Problem in Data Warehouses: Hardness Study and Selection Algorithms
by Bellatreche, Ladjel; Boukhalfa, Kamel; Richard, Pascal; Woameno, Komla Yamavo
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Article #:    ITJ5289
Pages: 1-23
Source: International Journal of Data Warehousing and Mining, Vol. 5, Issue 4
Copyright: 2009; IGI Publishing
Author Affiliations: University of Poitiers, France; University of Poitiers, France; University of Poitiers, France; University of Poitiers, France
Editor: D. Taniar
Keywords: Data Definition Language, Fragmentation Schema Selection Algorithm, partitioning, Primary Star Join Query Optimization, Referential Horizontal Partitioning

Abstract
Horizontal Partitioning has been largely adopted by the database community, where it took a significant part in the physical design process. Actually, it is supported by most commercial database systems (DBMS), where a native Data Definition Language for decomposing tables/materialized views using various modes is proposed. In traditional databases, horizontal partitioning has been largely studied, where several fragmentation algorithms were proposed to partition tables in isolation. In the relational data warehouse environment, horizontal partitioning consists in decomposing the whole warehouse schema into sub schemas, where each schema contains fragments of dimension and fact tables. Dimension tables are fragmented using the primary partitioning mode, whereas the fact table is divided using referential mode. In this article, the authors first focus on the evolution of horizontal partitioning in commercial DBMS motivated by decision support applications. Secondly, they give a formalization of the referential fragmentation schema selection problem in the data warehouse and they study its hardness to select an optimal solution. Due to its high complexity, they develop two algorithms: hill climbing and simulated annealing with several variants to select a near optimal partitioning schema. Finally, extensive experimental studies are conducted using the data set of APB1 benchmark to compare the quality the proposed algorithms using a mathematical cost model. Based on these experiments, some recommendations are given to advise database administrator for well using horizontal partitioning.

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