JSW 2011 Vol.6(5): 857-865 ISSN: 1796-217X
doi: 10.4304/jsw.6.5.857-865
doi: 10.4304/jsw.6.5.857-865
An Efficient Method for Improving Query Efficiency in Data Warehouse
Zhiwei Ni, Junfeng Guo, Li Wang, Yazhuo Gao
School of Management, Hefei University of Technology, Hefei , Anhui, China; Key Lab. of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei , Anhui, China
Abstract—There are lots of performance bottlenecks for real-time queries in mass data. Many methods can only improve the efficiency for frequently used queries, but it is not advisable to neglect the non-frequently used queries. This paper proposes a new integrated index model called BBI and illustrates the application of this model. Based on the feature of data warehouse and OLAP queries, this index model is built with inverted index, aggregation table, bitmap index and b-tree. It greatly promotes not only the efficiency of frequently used queries, but also the performance of other queries. The analytical and experimental results demonstrate the utility of BBI.
Index Terms—Aggregation Table, Inverted Index, Bitmap Index, B-Tree Index
Abstract—There are lots of performance bottlenecks for real-time queries in mass data. Many methods can only improve the efficiency for frequently used queries, but it is not advisable to neglect the non-frequently used queries. This paper proposes a new integrated index model called BBI and illustrates the application of this model. Based on the feature of data warehouse and OLAP queries, this index model is built with inverted index, aggregation table, bitmap index and b-tree. It greatly promotes not only the efficiency of frequently used queries, but also the performance of other queries. The analytical and experimental results demonstrate the utility of BBI.
Index Terms—Aggregation Table, Inverted Index, Bitmap Index, B-Tree Index
Cite: Zhiwei Ni, Junfeng Guo, Li Wang, Yazhuo Gao, "An Efficient Method for Improving Query Efficiency in Data Warehouse," Journal of Software vol. 6, no. 5, pp. 857-865, 2011.
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General Information
ISSN: 1796-217X (Online)
Frequency: Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKI, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsweditorialoffice@gmail.com
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