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
- 2. Jinyang Li
- 3. H. V. Jagadish
- 4. Mirek Riedewald
Incoming Citations (Sorted by Pagerank)
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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 |
|---|---|---|---|---|
| 185 | DuckDB: an Embeddable Analytical Database | 2019 | SIGMOD | 0.00036529607 |
| 1,577 | Designing Fair Ranking Schemes | 2019 | SIGMOD | 0.00011276814 |
| 5,660 | Query Refinement for Diverse Top-k Selection | 2024 | SIGMOD | 5.3859487e-05 |
| 5,839 | Why Not Yet: Fixing a Top-k Ranking that Is Not Fair to Individuals | 2023 | VLDB | 5.3073497e-05 |
| 6,644 | Query Refinement for Diversity Constraint Satisfaction | 2024 | VLDB | 4.973836e-05 |
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| 6,085 | Answering Top-k Representative Queries on Graph Databases | 2014 | SIGMOD | 5.2165029e-05 |
| 185 | DuckDB: an Embeddable Analytical Database | 2019 | SIGMOD | 0.00036529607 |
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| 8,257 | DuckPGQ: Efficient Property Graph Queries in an analytical RDBMS | 2023 | CIDR | 4.5437589e-05 |
| 10,289 | Efficient Query Repair for Aggregate Constraints | 2026 | VLDB | 4.1905499e-05 |
| 12,150 | Demonstration of the FDB Query Engine for Factorised Databases | 2012 | VLDB | 4.1905499e-05 |
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