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

Author:

Bai Qiushi1,Alsudais Sadeem1,Li Chen1

Affiliation:

1. University of California, Irvine

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.

Publisher

Association for Computing Machinery (ACM)

Subject

General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development

Reference56 articles.

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5. Qiushi Bai , Sadeem Alsudais , and Chen Li . 2022 . Demo of VisBooster: Accelerating Tableau Live Mode Queries Up to 100 Times Faster . In Proceedings of the Workshops of the EDBT/ICDT 2022 Joint Conference, Edinburgh, UK, March 29, 2022 (CEUR Workshop Proceedings), Maya Ramanath and Themis Palpanas (Eds.) , Vol. 3135 . CEUR-WS.org. http://ceur-ws.org/Vol-3135/bigvis_short5.pdf Qiushi Bai, Sadeem Alsudais, and Chen Li. 2022. Demo of VisBooster: Accelerating Tableau Live Mode Queries Up to 100 Times Faster. In Proceedings of the Workshops of the EDBT/ICDT 2022 Joint Conference, Edinburgh, UK, March 29, 2022 (CEUR Workshop Proceedings), Maya Ramanath and Themis Palpanas (Eds.), Vol. 3135. CEUR-WS.org. http://ceur-ws.org/Vol-3135/bigvis_short5.pdf

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