AQUA: Automatic Collaborative Query Processing in Analytical Database
Summary: AQUA compiles collaborative queries (relational + DL inference) into SQL so the optimizer can plan them end-to-end instead of delegating to black-box UDFs. Adds a declarative DL data-management interface and DL-aware physical optimizations to remove manual model-data handling and tuning. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Yuchen Peng
- 2. Ke Chen
- 3. Lidan Shou
- 4. Dawei Jiang
- 5. Gang Chen
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 139 | The MADlib Analytics Library or MAD Skills, the SQL | 2012 | VLDB | 0.00042320525 |
| 2,660 | Vertica-ML: Distributed Machine Learning in Vertica Database | 2020 | SIGMOD | 8.3614044e-05 |
| 3,122 | DB4ML – An In-Memory Database Kernel with Machine Learning Support | 2020 | SIGMOD | 7.5284233e-05 |
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