An Experiment-driven Approach to Tune Database Configuration Parameters and SQL
Event details
| Date | 14.05.2009 |
| Hour | 13:30 |
| Speaker | Prof. Shivnath BABU, Duke University |
| Location | |
| Category | Conferences - Seminars |
Abstract
Database systems have a large number of configuration parameters that control memory distribution, I/O optimization, costing of query plans, and other behavior. Regular users and even expert database administrators struggle to tune these parameters for good performance. In the first part of the talk, I will present iTuned, a tool that automates the task of identifying good settings for database configuration parameters. iTuned has three novel features: (i) a technique called Adaptive Sampling that collects monitoring data through planned experiments to find high-impact parameters and high-performance parameter settings, (ii) support for live experiments in production database environments with little overhead on the user-facing workload; and (iii) portability across different database systems.
The second part of the talk will consider SQL tuning, the attempt to improve a poorly-performing execution plan selected by the query optimizer for a SQL query. Like parameter tuning, SQL tuning requires considerable expertise in database internals; forcing database administrators to rely on intuition or trial-and-error. I will show how SQL tuning can be automated using the same experiment-driven paradigm as iTuned, but with a different instantiation. Finally, I will present evidence from empirical evaluations and recent computing trends to argue why the experiment-driven paradigm is an idea whose time has come.
Speaker's bio
Shivnath Babu is an Assistant Professor of Computer Science at Duke University. He got his Ph.D. from Stanford University in 2005. He has received a U.S. National Science Foundation CAREER Award and three IBM Faculty Awards. His current research focuses on making large-scale databases and systems easier to manage.
Practical information
- General public
- Free