Volume 11 Number 2 (Mar. 2016)
Home > Archive > 2016 > Volume 11 Number 2 (Mar. 2016) >
JCP 2016 Vol.11(2): 140-148 ISSN: 1796-203X
doi: 10.17706/jcp.11.2.140-148

Materialized View Selection for a Data Warehouse Using Frequent Itemset Mining

Mohammad Karim Sohrabi, Vahid Ghods
Department of Electrical and Computer Engineering, Semnan Branch, Islamic Azad University, Semnan, Iran.
Abstract—Data warehouses are subject oriented, consolidated, integrated, and time variant repository of possibly heterogeneous data. A data warehouse is used to response to on-line analytical queries over the millions records of data in an acceptable time. Since a data warehouse often has millions of records of data, it is an important challenge how we can reduce the time of on-line analytical processing. One of the most important issues which address this problem is the view materialization. Each sub-query results an intermediate table, called virtual view, which is used to find final result of the analytical query. These virtual views often are commonly used to response to several analytical queries. We can materialize such views to prevent multiple redundant computations and thus lead to reduction in response time of queries. The constraint of storage memory on one hand, and the maintenance cost of materialized views when the source data are updated on the other hand, cause that it is impossible to materialize all or even large part of views. Therefore, selection of a proper set of views to materialization plays a major role in performance. There are many methods of view selection to materialization which uses different techniques and frameworks to select optimal set of views to materialization. In this paper, we present a new efficient method to conduct selecting proper set of views to materialization using a frequent itemset mining approach. In our algorithm, the set of given queries is transformed to a transaction database where a transaction corresponds to a query and items of a transaction are the original query’s predicates. Our performance study showed that this algorithm outperformed substantially the best former algorithms.

Index Terms—Data warehouse, on-line analytical processing (OLAP), view selection, view materialization, frequent itemset mining.

[PDF]

Cite: Mohammad Karim Sohrabi, Vahid Ghods, "Materialized View Selection for a Data Warehouse Using Frequent Itemset Mining," Journal of Computers vol. 11, no. 2, pp. 140-148, 2016.

General Information

ISSN: 1796-203X
Frequency: Monthly (2006-2014); Bimonthly (Since 2015)
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Cherry L. Chen
Abstracting/ Indexing: DBLP, EBSCO, DOAJ, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
  • Jan 20, 2017 News!

    Vol.12, No.6 has been published with online version.   [Click]

  • Jan 16, 2017 News!

    Vol.12, No.5 has been published with online version.   [Click]

  • Oct 09, 2016 News!

    Vol.12, No.4 has been published with online version.   [Click]

  • Sep 02, 2016 News!

    Vol.11, No.3 has been indexed by EI (Inspec).   [Click]

  • Aug 18, 2016 News!

    Vol.11, No.2 has been indexed by EI (Inspec).   [Click]

  • Read more>>