A Note On Operator-Level Query Execution Cost Modeling

TL;DR

This paper investigates operator-level query execution cost modeling, addressing practical challenges with limited feedback and mixed estimates, and demonstrates its effectiveness in index tuning applications.

Contribution

It introduces a robust framework for operator-level cost modeling that handles limited feedback and mixed estimates, with a case study on index tuning.

Findings

Framework improves robustness of cost estimates

Effective in index tuning scenarios

Addresses feedback limitations and estimate inconsistencies

Abstract

External query execution cost modeling using query execution feedback has found its way in various database applications such as admission control and query scheduling. Existing techniques in general fall into two categories, plan-level cost modeling and operator-level cost modeling. It has been shown in the literature that operator-level cost modeling can often significantly outperform plan-level cost modeling. In this paper, we study operator-level cost modeling from a robustness perspective. We address two main challenges in practice regarding limited execution feedback (for certain operators) and mixed cost estimates due to the use of multiple cost modeling techniques. We propose a framework that deals with these issues and present a comprehensive analysis of this framework. We further provide a case study to demonstrate the efficacy of our framework in the context of index tuning, which is itself a new application of external cost modeling techniques.