An Improved OLAP Join and Aggregate Algorithm Based on Dimension Hierarchy

Author

He, Haitao ; Zhang, Yanpeng ; Ren, Jiadong ; Hu, Changzhen

Author_Institution

Coll. of Inf. Sci. & Eng., Yanshan Univ., Qinhuangdao, China

Volume

5

fYear

2009

fDate

14-16 Aug. 2009

Firstpage

169

Lastpage

172

Abstract

The OLAP (online analytical processing) queries are always involved with queries on the massive dataset. As a result, how to perform multi-table join and aggregate operations becomes the key issue. A join and aggregate algorithm based on dimension hierarchy (JABDH) is proposed in this paper. Considering the semantic characteristic which is not in all the dimension hierarchies, dimension hierarchical encoding is used to retrieve the matching dimension hierarchies and evaluate the set of query ranges for semantic dimension hierarchies. To improve the efficiency of multi-table join and aggregate operations for non-semantic dimensional hierarchies, join and aggregate operations are translated into bitmapped join index of fact table. The performance analysis and experimental results show that JABDH has improved the speed of queries and the efficiency of the OLAP queries.

Keywords

data mining; query processing; OLAP aggregate algorithm; OLAP join algorithm; dimension hierarchical encoding; dimension hierarchy; online analytical processing queries; Aggregates; Computer science; Data engineering; Educational institutions; Encoding; Fuzzy systems; Helium; Information analysis; Information science; Knowledge engineering; aggregation queries; bitmapped join index; dimension hierarchical encoding; multi-table join;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on

Conference_Location

Tianjin

Print_ISBN

978-0-7695-3735-1

Type

conf

DOI

10.1109/FSKD.2009.549

Filename

5360636