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The Computer Journal 2004 47(6):673-693; doi:10.1093/comjnl/47.6.673
© 2004 by British Computer Society
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Regression-Based Self-Tuning Modeling of Smooth User-Defined Function Costs for an Object-Relational Database Management System Query Optimizer

Byung Suk Lee1,*, Li Chen2,§,++, Jeff Buzas3,¶ and Vinod Kannoth4,{ddagger}

1 Department of Computer Science, University of Vermont, Burlington, VT 05405, USA 2 Department of Computer Science, Texas A&M University, College Station, TX 77843, USA 3 Department of Mathematics and Statistics, University of Vermont, Burlington, VT 05405, USA 4 Federal Reserve Information Technology, 701 East Byrd Street, Richmond, VA 23219, USA

We present a new approach to modeling the execution costs of user-defined functions (UDFs) for the query optimizer of an object-relational DBMS (ORDBMS). Our approach self-tunes a cost model incrementally based on the costs of the recent executions of a UDF. The approach is centered on a feedback loop in which the feedback information comprises individual UDF execution records. Each execution record contains the cost variable values used in the execution and the resulting CPU and disk I/O costs. This feedback information is saved in the execution log and used in a batch to update the cost model. Furthermore, our approach handles nominal cost variables by maintaining separate cost models for recently used values of the variables. We have built a framework that implements the feedback loop in a commercial ORDBMS. Then, we have performed experiments using common database UDFs with smooth cost variations and incrementally modeling the data using multiple regression. The experimental results demonstrate the adaptive accuracy that makes the cost model stabilize quickly while incurring small errors in cost estimations. Our approach has the advantages of incurring little overhead while tuning the cost model continuously throughout the UDF executions.

Received 10 May 2003. Revised 27 March 2004.

* Email: bslee{at}emba.uvm.edu

§ Email: lchen{at}emba.uvm.edu

Email: buzas{at}emba.uvm.edu

{ddagger} Email: vinod.kannoth{at}frit.frb.org

++ Work done while at the Department of Computer Science, University of Vermont.


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