An evaluation of vertical class partitioning for query processing in object-oriented databases
| Autor: | Kamalakar Karlapalem, Qing Li, Chi-Wai Fung |
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| Rok vydání: | 2002 |
| Předmět: |
Class (computer programming)
Hierarchy Theoretical computer science Hierarchy (mathematics) Computer science computer.software_genre Computer Science Applications Set (abstract data type) Computational Theory and Mathematics Database theory Data mining Representation (mathematics) Projection (set theory) computer Computer Science::Databases Information Systems Instance variable Database model |
| Zdroj: | IEEE Transactions on Knowledge and Data Engineering. 14:1095-1118 |
| ISSN: | 1041-4347 |
| DOI: | 10.1109/tkde.2002.1033777 |
| Popis: | Vertical partitioning is a design technique for reducing the number of disk accesses to execute a given set of queries by minimizing the number of irrelevant instance variables accessed. This is accomplished by grouping the frequently accessed instance variables as vertical class fragments. The complexity of object-oriented database models due to subclass hierarchy and class composition hierarchy complicates the definition and representation of vertical partitioning of the classes, which makes the problem of vertical partitioning in OODBs very challenging. In this paper, we develop a comprehensive analytical cost model for processing of queries on vertically partitioned OODB classes. A set of analytical evaluation results is presented to show the effect of vertical partitioning, and to study the trade-off between the projection ratio versus selectivity factor vis-a-vis sequential versus index access. Furthermore, an empirical experimental prototype supporting vertical class partitioning has been implemented on a commercial OODB tool kit to validate our analytical cost model. |
| Databáze: | OpenAIRE |
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