GooseDB: A Database Engine that Optimally Refines Top-k Queries to Satisfy Representation Constraints
Summary: GooseDB combines DuckDB with an MILP solver to synthesize minimally modified SQL queries that enforce representation (group-count) constraints on top-k outputs given constraints and user modification preferences. Novelty: supports broad edits to selection predicates and scoring functions and is the first system to jointly optimize both (and across multiple k) for minimal-change refinements, substantially generalizing prior work. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Zixuan Chen (Northeastern University)
- 2. Jinyang Li (University of Michigan)
- 3. H. V. Jagadish (University of Michigan)
- 4. Mirek Riedewald (Northeastern University)
BibTeX Citation
@article{chen_vldb25,
title = {{GooseDB: A Database Engine that Optimally Refines Top-k Queries to Satisfy Representation Constraints}},
author = {Chen, Zixuan and Li, Jinyang and Jagadish, H. V. and Riedewald, Mirek},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {12},
pages = {5351--5354},
doi = {10.14778/3750601.3750669},
url = {https://doi.org/10.14778/3750601.3750669},
year = {2025}
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Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 71 | DuckDB: an Embeddable Analytical Database | 2019 | SIGMOD | 0.00037724477 |
| 1,379 | Designing Fair Ranking Schemes | 2019 | SIGMOD | 0.00010859038 |
| 4,327 | Query Refinement for Diversity Constraint Satisfaction | 2024 | VLDB | 6.6600895e-05 |
| 5,359 | Why Not Yet: Fixing a Top-k Ranking that Is Not Fair to Individuals | 2023 | VLDB | 6.1608586e-05 |
| 6,522 | Query Refinement for Diverse Top-k Selection | 2024 | SIGMOD | 5.7546462e-05 |
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| 2 | 6,030 | Answering Top-k Representative Queries on Graph Databases | 2014 | SIGMOD |
| 3 | 13,598 | Dominance-Based Data Reduction for Package Queries | 2026 | VLDB |
| 4 | 5,053 | Beyond Quacking: Deep Integration of Language Models and RAG into DuckDB | 2025 | VLDB |
| 5 | 9,035 | Generating Flexible Workloads for Graph Databases | 2016 | VLDB |
| 6 | 9,741 | Rodeo: Making Refinements for Diverse Top-k Queries | 2024 | VLDB |
| 7 | 7,080 | DuckPGQ: Efficient Property Graph Queries in an analytical RDBMS | 2023 | CIDR |
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