Online index selection in RDBMS by evolutionary approach

Piotr Kołaczkowski , Henryk Rybiński

Abstract

In recent years, many algorithms for automatic physical database tuning have been proposed and successfully used in tools for administration of relational database management systems. The novel method described in this paper uses a steady-state evolutionary approach to continuously give index recommendations so that the database management system can adapt to changing workload and data distribution. Contrary to online algorithms offering recommendations on a per-query basis, our solution takes into account index reuse accross different queries. The experiments show that the quality of the recommendations obtained by the proposed method matches the quality of recommendations given by the best offline index selection algorithms. Moreover, high performance and low memory footprint of the method make it suitable for autonomic database tuning systems. © 2011 Springer-Verlag Berlin Heidelberg.

Author Piotr Kołaczkowski (FEIT / IN)
Piotr Kołaczkowski,,
- The Institute of Computer Science
, Henryk Rybiński (FEIT / IN)
Henryk Rybiński,,
- The Institute of Computer Science
Pages475-484
Publication size in sheets0.5
Book Hameurlain Abdelkader, Liddle Stephen W., Schewe Klaus-Dieter, Zhou Xiaofang (eds.): Database and Expert Systems Applications, Lecture Notes In Computer Science, vol. 6861, 2011, Springer, ISBN 978-3-642-23090-5, 608 p., DOI:10.1007/978-3-642-23091-2
ASJC Classification1702 Artificial Intelligence; 1706 Computer Science Applications; 1707 Computer Vision and Pattern Recognition; 2210 Mechanical Engineering; 2204 Biomedical Engineering; 1711 Signal Processing; 1700 General Computer Science; 2614 Theoretical Computer Science
DOIDOI:10.1007/978-3-642-23091-2_41
Languageen angielski
Score (nominal)13
Score sourcejournalList
Publication indicators Scopus Citations = 0; GS Citations = 1.0
Citation count*1 (2019-12-31)
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