au·to·nom·ic
Pronunciation: "o-t&-'nä-mik
Function: adjective
Date: 1898
1 : acting or occurring involuntarily <autonomic reflexes>
2 : relating to, affecting, or controlled by the autonomic nervous system or its effects or activity <autonomic drugs>

                               -- Merriam Webster Dictionary

 Query optimization automatically determines the best way to execute a given non-procedural query to a database, using a mathematical model of the performance of each possible execution plan.  Relational query optimization, which dates from Pat Selinger’s pioneering work in System R in the 1970s, was actually one of the earliest examples of autonomic computing!  More recently, we have extended relational query optimization in DB2 in a number of ways to make it fulfill its true autonomic promise, to exploit the optimizer’s model to evaluate alternative physical database designs, and to support the emerging XQuery standard.  Much of this work is part of the DB2 Autonomic Computing project (formerly known as the Self-Managing And Resource Tuning (SMART) project) that predated the IBM-wide Autonomic Computing initiative. Guy’s talk will give an overview of some of these extensions, including efficient sampling in SQL queries, the Design Advisor, the meta-optimizer, and the self-validating LEarning Optimizer (LEO). 

Dr. Guy M. Lohman is Manager of Advanced Optimization in the Advanced Database Solutions Department at IBM Research Division's Almaden Research Center in San Jose, California, and has 21 years of experience in relational query optimization.  He is the architect of the Optimizer of the DB2 Universal Data Base (UDB) for Linux, Unix, and Windows, and was responsible for its development in Versions 2 and 5, as well as the invention and prototyping of Visual Explain.  During that period, Dr. Lohman also managed the overall effort to incorporate into the DB2 UDB product the Starburst compiler technology that was prototyped at the Almaden Research Center.  More recently, he was a co-inventor and designer of the DB2 Index Wizard (DB2 Advisor), and co-founder of the DB2 SMART (Self-Managing And Resource Tuning) project, part of IBM's Autonomic Computing initiative.  In 2002, Dr. Lohman was elected to the IBM Academy of Technology.  His current research interests involve query optimization and self-managing database systems.