Optimized Data Indexing Algorithms for OLAP Systems

The need to process and analyze large data volumes, as well as to convey the information contained therein to decision makers naturally led to the development of OLAP systems. Similarly to SGBDs, OLAP systems must ensure optimum access to the storage environment. Although there are several ways to o...

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Bibliographic Details
Published inDatabase systems journal Vol. I; no. 2; pp. 17 - 26
Main Author Lucian BORNAZ
Format Journal Article
LanguageEnglish
Published Bucharest University of Economic Studies 01.12.2010
Subjects
data warehouse
indexing algorithm
n-Tree
OLAP
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ISSN2069-3230
2069-3230

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Summary:The need to process and analyze large data volumes, as well as to convey the information contained therein to decision makers naturally led to the development of OLAP systems. Similarly to SGBDs, OLAP systems must ensure optimum access to the storage environment. Although there are several ways to optimize database systems, implementing a correct data indexing solution is the most effective and less costly. Thus, OLAP uses indexing algorithms for relational data and n-dimensional summarized data stored in cubes. Today database systems implement derived indexing algorithms based on well-known Tree, Bitmap and Hash indexing algorithms. This is because no indexing algorithm provides the best performance for any particular situation (type, structure, data volume, application). This paper presents a new n-dimensional cube indexing algorithm, derived from the well known B-Tree index, which indexes data stored in data warehouses taking in consideration their multi-dimensional nature and provides better performance in comparison to the already implemented Tree-like index types.
ISSN:2069-3230
2069-3230