Adversarial Query Synthesis via Bayesian Optimization

2026-03-02

AI Summary

This work proposes a novel automated approach to adversarial query synthesis for database benchmarking by introducing Bayesian optimization—a technique previously unexplored in this context. Traditional database benchmarks rely heavily on manually crafted queries, which struggle to uncover high-difficulty test cases that stress system performance. The proposed method integrates automatic query generation with performance evaluation, substantially reducing the need for human intervention while efficiently producing queries that pose greater challenges to database systems. Experimental results demonstrate that the synthesized queries exhibit more than twice the optimization potential compared to those from existing benchmarks, significantly enhancing both the coverage and efficiency of database testing.

Technology Category

• Search and Optimization: Adversarial Search
• Data Mining & Knowledge Management: Intelligent Query Processing
• Game Theory and Economic Paradigms: Adversarial Learning

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Graph Algorithms and Modeling for the Web: Querying, indexing, and retrieval in Web-related graphs
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems

Abstract

Benchmark workloads are extremely important to the database management research community, especially as more machine learning components are integrated into database systems. Here, we propose a Bayesian optimization technique to automatically search for difficult benchmark queries, significantly reducing the amount of manual effort usually required. In preliminary experiments, we show that our approach can generate queries with more than double the optimization headroom compared to existing benchmarks.

Problem

• adversarial query
• benchmark
• database
• query synthesis
• optimization headroom

Innovation

• Adversarial Query Synthesis
• Bayesian Optimization
• Benchmark Workloads
• Query Optimization
• Database Systems