QueryBooster: Improving SQL Performance Using Middleware Services for Human-Centered Query Rewriting

TL;DR

QueryBooster is a middleware system that enables users to express and generate SQL query rewriting rules using an intuitive language, significantly enhancing query performance through human-centered customization.

Contribution

It introduces a middleware architecture with VarSQL, a rule language, and an automatic rule generalization method, allowing flexible, user-driven SQL query rewriting.

Findings

User study confirms VarSQL's expressiveness.

Experiments show improved query performance.

Rule suggestion framework is effective.

Abstract

SQL query performance is critical in database applications, and query rewriting is a technique that transforms an original query into an equivalent query with a better performance. In a wide range of database-supported systems, there is a unique problem where both the application and database layer are black boxes, and the developers need to use their knowledge about the data and domain to rewrite queries sent from the application to the database for better performance. Unfortunately, existing solutions do not give the users enough freedom to express their rewriting needs. To address this problem, we propose QueryBooster, a novel middleware-based service architecture for human-centered query rewriting, where users can use its expressive and easy-to-use rule language (called VarSQL) to formulate rewriting rules based on their needs. It also allows users to express rewriting intentions by providing examples of the original query and its rewritten query. QueryBooster automatically generalizes them to rewriting rules and suggests high-quality ones. We conduct a user study to show the benefits of VarSQL to formulate rewriting rules. Our experiments on real and synthetic workloads show the effectiveness of the rule-suggesting framework and the significant advantages of using QueryBooster for human-centered query rewriting to improve the end-to-end query performance.