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PilotDB: Database-Agnostic Online Approximate Query Processing with A Priori Error Guarantees

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Bibliographic Details
Title: PilotDB: Database-Agnostic Online Approximate Query Processing with A Priori Error Guarantees
Authors: Yuxuan Zhu, Tengjun Jin, Stefanos Baziotis, Chengsong Zhang, Charith Mendis, Daniel Kang
Source: Proceedings of the ACM on Management of Data. 3:1-28
Publisher Information: Association for Computing Machinery (ACM), 2025.
Publication Year: 2025
Description: After decades of research in approximate query processing (AQP), its adoption in the industry remains limited. Existing methods struggle to simultaneously provide user-specified error guarantees, eliminate maintenance overheads, and avoid modifications to database management systems. To address these challenges, we introduce two novel techniques, TAQA and BSAP. TAQA is a two-stage online AQP algorithm that achieves all three properties for arbitrary queries. However, it can be slower than exact queries if we use standard row-level sampling. BSAP resolves this by enabling block-level sampling with statistical guarantees in TAQA. We implement TAQA and BSAP in a prototype middleware system, PilotDB, that is compatible with all DBMSs supporting efficient block-level sampling. We evaluate PilotDB on PostgreSQL, SQL Server, and DuckDB over real-world benchmarks, demonstrating up to 126X speedups when running with a 5% guaranteed error.
Document Type: Article
Language: English
ISSN: 2836-6573
DOI: 10.1145/3725335
Accession Number: edsair.doi...........3ffa3bb1ace10cd50116dc8dfd3b8797
Database: OpenAIRE
Description
Abstract:After decades of research in approximate query processing (AQP), its adoption in the industry remains limited. Existing methods struggle to simultaneously provide user-specified error guarantees, eliminate maintenance overheads, and avoid modifications to database management systems. To address these challenges, we introduce two novel techniques, TAQA and BSAP. TAQA is a two-stage online AQP algorithm that achieves all three properties for arbitrary queries. However, it can be slower than exact queries if we use standard row-level sampling. BSAP resolves this by enabling block-level sampling with statistical guarantees in TAQA. We implement TAQA and BSAP in a prototype middleware system, PilotDB, that is compatible with all DBMSs supporting efficient block-level sampling. We evaluate PilotDB on PostgreSQL, SQL Server, and DuckDB over real-world benchmarks, demonstrating up to 126X speedups when running with a 5% guaranteed error.
ISSN:28366573
DOI:10.1145/3725335