Relational Query Synthesis ⋈ Decision Tree Learning
Summary: LIBRA synthesizes SPJ queries with categorical/numerical predicates by interleaving schema-guided relational search and decision-tree learning. It guarantees completeness, favors minimal queries, and outperforms Scythe/PATSQL on 1,475 multi-table instances. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Aaditya Naik (University of Pennsylvania)
- 2. Aalok Thakkar (University of Pennsylvania)
- 3. Adam Stein (University of Pennsylvania)
- 4. Rajeev Alur (University of Pennsylvania)
- 5. Mayur Naik (University of Pennsylvania)
BibTeX Citation
@article{naik_vldb24,
title = {{Relational Query Synthesis ⋈ Decision Tree Learning}},
author = {Naik, Aaditya and Thakkar, Aalok and Stein, Adam and Alur, Rajeev and Naik, Mayur},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {2},
pages = {250--263},
doi = {10.14778/3626292.3626306},
url = {https://doi.org/10.14778/3626292.3626306},
year = {2024}
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Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 764 | To Join or Not to Join? Thinking Twice about Joins before Feature Selection | 2016 | SIGMOD | 0.00014226652 |
| 865 | Natural language to SQL: Where are we today? | 2020 | VLDB | 0.00013521464 |
| 1,121 | ARDA: Automatic Relational Data Augmentation for Machine Learning | 2020 | VLDB | 0.00012093059 |
| 2,048 | Duoquest: A Dual-Specification System for Expressive SQL Queries | 2020 | SIGMOD | 9.2560185e-05 |
| 4,190 | QuickFOIL: Scalable Inductive Logic Programming | 2015 | VLDB | 6.8431849e-05 |
| 4,662 | The Relational Model Of Data And Cylindrical Algebras | 1982 | PODS | 6.5787742e-05 |
| 4,733 | Interactive Query Synthesis from Input-Output Examples | 2017 | SIGMOD | 6.5335361e-05 |
| 5,438 | PATSQL: Efficient Synthesis of SQL Queries from Example Tables with Quick Inference of Projected Columns | 2021 | VLDB | 6.2195845e-05 |
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