Persona-Conditioned Query Generation for Selectivity-Controlled Workloads
Summary: PCOQ uses LLM-embodied user personas to generate behaviorally diverse, realistic query workloads. It uniquely supports user-specified selectivity despite infeasible LLM counting and costly query execution, via an interactive workload-generation platform. (summarized by gpt-5.6-luna on Aug 28 2026)
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Authors
- 1. Angjela Davitkova (Rheinland-Palatinate Technical University Kaiserslautern-Landau)
- 2. Sebastian Michel (Rheinland-Palatinate Technical University Kaiserslautern-Landau)
BibTeX Citation
@article{davitkova_vldb26,
title = {{Persona-Conditioned Query Generation for Selectivity-Controlled Workloads}},
author = {Davitkova, Angjela and Michel, Sebastian},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {12},
pages = {4714--4717},
doi = {10.14778/3827998.3828104},
url = {https://doi.org/10.14778/3827998.3828104},
year = {2026}
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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 |
|---|---|---|---|---|
| 174 | Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation | 2024 | VLDB | 0.00026790979 |
| 1,890 | Generating Targeted Queries for Database Testing | 2008 | SIGMOD | 9.4193315e-05 |
| 2,467 | Few-shot Text-to-SQL Translation using Structure and Content Prompt Learning | 2023 | SIGMOD | 8.4211526e-05 |
| 4,132 | SQLStorm: Taking Database Benchmarking into the LLM Era | 2025 | VLDB | 6.7885553e-05 |
| 4,482 | LearnedSQLGen: Constraint-aware SQL Generation using Reinforcement Learning | 2022 | SIGMOD | 6.5802486e-05 |
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