PilotDB: Database-Agnostic Online Approximate Query Processing with A Priori Error Guarantees (Technical Report)
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arXiv
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| Autores principales: | , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866916663573610496 |
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| author | Zhu, Yuxuan Jin, Tengjun Baziotis, Stefanos Zhang, Chengsong Mendis, Charith Kang, Daniel |
| author_facet | Zhu, Yuxuan Jin, Tengjun Baziotis, Stefanos Zhang, Chengsong Mendis, Charith Kang, Daniel |
| contents | 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 simple ment 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_21087 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | PilotDB: Database-Agnostic Online Approximate Query Processing with A Priori Error Guarantees (Technical Report) Zhu, Yuxuan Jin, Tengjun Baziotis, Stefanos Zhang, Chengsong Mendis, Charith Kang, Daniel Databases H.2.4; G.3 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 simple ment 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. |
| title | PilotDB: Database-Agnostic Online Approximate Query Processing with A Priori Error Guarantees (Technical Report) |
| topic | Databases H.2.4; G.3 |
| url | https://arxiv.org/abs/2503.21087 |