By Topic

Improving Star Join Queries Performance: A Maximal Frequent Pattern Based Approach for Automatic Selection of Indexes in Relational Data Warehouses

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Ziani, B. ; Dept. of Comput. Sci., Univ. of Laghouat, Algeria ; Ouinten, Y.

Indexing is a fundamental technique used by the administrator to reduce the cost of processing complex queries defined on a data warehouse. However, selecting a suitable configuration of indexes is a difficult problem to solve. The problem is classified as NP-hard. Automatic index selection has received significant attention in the databases field. Most works have focused on providing tools and algorithms to help data bases administrators in the choice of a configuration of indexes. Some of these works have been adapted for the data warehouse context. The idea, recently introduced, of using data mining techniques to resolve this problem remains a promising approach. In this paper, we propose a maximal frequent pattern based approach to generate a configuration of indexes from a given workload. The proposed approach was tested on APB-1 benchmark under Oracle. The results obtained show that the proposed approach generates indexes that improve the performance of the workload.

Published in:

Internet Computing & Information Services (ICICIS), 2011 International Conference on

Date of Conference:

17-18 Sept. 2011