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Vertical Fragmentation in Databases Using Data-Mining Technique

Vertical Fragmentation in Databases Using Data-Mining Technique

Narasimhaiah Gorla, Pang W.Y. Betty
Copyright: © 2010 |Pages: 21
ISBN13: 9781615209699|ISBN10: 1615209697|EISBN13: 9781615209705
DOI: 10.4018/978-1-61520-969-9.ch136
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MLA

Gorla, Narasimhaiah, and Pang W.Y. Betty. "Vertical Fragmentation in Databases Using Data-Mining Technique." Business Information Systems: Concepts, Methodologies, Tools and Applications, edited by Information Resources Management Association, IGI Global, 2010, pp. 2248-2268. https://doi.org/10.4018/978-1-61520-969-9.ch136

APA

Gorla, N. & Betty, P. W. (2010). Vertical Fragmentation in Databases Using Data-Mining Technique. In I. Management Association (Ed.), Business Information Systems: Concepts, Methodologies, Tools and Applications (pp. 2248-2268). IGI Global. https://doi.org/10.4018/978-1-61520-969-9.ch136

Chicago

Gorla, Narasimhaiah, and Pang W.Y. Betty. "Vertical Fragmentation in Databases Using Data-Mining Technique." In Business Information Systems: Concepts, Methodologies, Tools and Applications, edited by Information Resources Management Association, 2248-2268. Hershey, PA: IGI Global, 2010. https://doi.org/10.4018/978-1-61520-969-9.ch136

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Abstract

A new approach to vertical fragmentation in relational databases is proposed using association rules, a data-mining technique. Vertical fragmentation can enhance the performance of database systems by reducing the number of disk accesses needed by transactions. By adapting Apriori algorithm, a design methodology for vertical partitioning is proposed. The heuristic methodology is tested using two real-life databases for various minimum support levels and minimum confidence levels. In the smaller database, the partitioning solution obtained matched the optimal solution using exhaustive enumeration. The application of our method on the larger database resulted in the partitioning solution that has an improvement of 41.05% over unpartitioned solution and took less than a second to produce the solution. We provide future research directions on extending the procedure to distributed and object-oriented database designs.

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