Journal article
A tunable class hierarchy index for object-oriented databases using a multidimensional index structure
Information and software technology, v 43(5), pp 309-323
01 Apr 2001
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
This paper presents a tunable 2-dimensional class hierarchy indexing (2D-CHI)technique for object-oriented databases. A 2-dimensional file organization is used as the index structure. 2D-CHI deals with the problem of clustering objects in a 2-dimensional domain space consisting of th ekey attribute comain and the class identifier domain. In conventional class indexing techniques using one-dimensional index structures sucha s the B+ -tree, the clustering property is owned exclusively by one attribute. These indexing techniques do not handle the queries that address both the attribute keys and the class identifiers efficiently. 2D-CHI enhances query performance by adjussting the degree of clustering between the key value domain and the class identifier domain based on the precollected usage pattern. For performance evaluation, the authors first compare 2D-CHI with the conventianl class indexigintechniques using an analytic costs model based on the assumption of uniform object distribution, and then, verify the cost model through experiments using the multilevel grid file as the 2-cimensional index. The authors further perform experiments with nonuniform object distributions. The experiments show that the proposed method builds optimal class index structures in terms of the total number of page accesses for given the precollected usage pattern regardless of query types and object distributions.
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Details
- Title
- A tunable class hierarchy index for object-oriented databases using a multidimensional index structure
- Creators
- Lee J-HK-Y Whang - Computer Engineering Department, Catholic University of Taegu-Hyosung, South KoreaHan W-SCho W-SIl-Y Song - Drexel University
- Publication Details
- Information and software technology, v 43(5), pp 309-323
- Publisher
- Elsevier Science Ltd
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000167909700003
- Scopus ID
- 2-s2.0-0035311273
- Other Identifier
- 991019183947004721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Information Systems
- Computer Science, Software Engineering