Resource selection for autonomic database tuning

초록

Database administrators should be aware of resource usages to maintain database system performance. As database applications become more complex and diverse, managing database systems becomes too costly and prone to error. Autonomic database tuning becomes more important than ever. This paper starts with an analysis on how resource usages respond by changing resource sizes in database systems. Then, we present a simple method that automatically selects resources that affect the system performance. An experiment using the TPC-C and TPC-W workloads has been carried out with a commercial database system. A preliminary analysis shows that our method works. © 2005 IEEE.