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Author Morfonios, Konstantinos ♦ Konakas, Stratis ♦ Ioannidis, Yannis ♦ Kotsis, Nikolaos
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2007
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Data cube ♦ OLAP ♦ Data warehouse
Abstract Implementation of the data cube is an important and scientifically interesting issue in On-Line Analytical Processing (OLAP) and has been the subject of a plethora of related publications. Naive implementation methods that compute each node separately and store the result are impractical, since they have exponential time and space complexity with respect to the cube dimensionality. To overcome this drawback, a wide range of methods that provide efficient cube implementation (with respect to both computation and storage) have been proposed, which make use of relational, multidimensional, or graph-based data structures. Furthermore, there are several other methods that compute and store approximate descriptions of data cubes, sacrificing accuracy for condensation. In this article, we focus on Relational-OLAP (ROLAP), following the majority of the efforts so far. We review existing ROLAP methods that implement the data cube and identify six orthogonal parameters/dimensions that characterize them. We place the existing techniques at the appropriate points within the problem space defined by these parameters and identify several clusters that the techniques form with various interesting properties. A careful study of these properties leads to the identification of particularly effective values for the space parameters and indicates the potential for devising new algorithms with better overall performance.
ISSN 03600300
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2007-11-02
Publisher Place New York
e-ISSN 15577341
Journal ACM Computing Surveys (CSUR)
Volume Number 39
Issue Number 4


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Source: ACM Digital Library