Nicolas Bruno, Surajit Chaudhuri, Arnd Christian König, Vivek Narasayya, Ravi Ramamurthy, and Manoj Syamala
The AutoAdmin project was started at Microsoft Research in 1996. The goal of AutoAdmin is to develop technology that makes database systems more self-tuning and self-managing. Initially, we focused mainly on the physical database design problem. In subsequent years we broadened our focus and studied a number of other problems: database monitoring, execution feedback for query optimization, flexible hinting mechanisms for query optimizers, query progress estimation and index defragmentation. One discipline we consistently followed in this project was that of implementing our techniques in the database server (in our case this was Microsoft SQL Server). This helped us better understand the applicability and limitations of our ideas and made it possible for our work to have impact on the Microsoft SQL Server product. In this article, we summarize some of the key technical lessons we have learned in the AutoAdmin project. Thus our discussions center around work done in AutoAdmin and does not cover the extensive related work done in other related projects in the database community (see  for an overview of work on self-tuning database systems). We focus our discussion on three problems: (1) physical database design, (2) exploiting feedback from execution for query optimization, and (3) query progress estimation. More details of AutoAdmin can be found on the project website .
|Published in||Bulletin of the IEEE Computer Society Technical Committee on Data Engineering|
|Publisher||IEEE Computer Society|