Online Index Selection in RDBMS by Evolutionary Approach
Piotr Kołaczkowski , Henryk Rybiński
AbstractIn 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.
|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|
|project||Autonomic index selection in relational database management systems by evolutionary transformation of query execution plans. Project leader: Rybiński Henryk,
, Phone: +48 22 234 7731, start date 15-04-2009, planned end date 08-09-2010, end date 30-09-2011, II/2009/M/1, Completed
|Citation count*||1 (2018-02-19)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.