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This is Going to Sound Crazy, But What If We Used Large Language Models to Boost Automatic Database Tuning Algorithms By Leveraging Prior History? We Will Find Better Configurations More Quickly Than Retraining From Scratch!
Summary: Booster augments existing DBMS autotuners with LLMs and query-level historical artifacts, turning prior tuning runs into per-query config contexts that can be reused under workload drift/schema transfer. Beam-search composition of query suggestions yields much faster re-optimization, up to 74% better configs than retraining/continuing from scratch.
(summarized by gpt-5-mini on Apr 11 2026)
- Paper ID
- 7529
- Venue
- SIGMOD
- Year
- 2026
- Pagerank
- 4.1945683e-05
- Overall Rank
- 10,217 | 28.93%
- DOI
-
10.1145/3786704
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Incoming Citations (Sorted by Pagerank)
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| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
Outgoing Citations (Sorted by Pagerank)
Showing 19 of 69 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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Year |
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| 7,854 |
dbET: Execution Time Distribution-based Plan Selection |
2023 |
SIGMOD |
4.6350172e-05 |
| 7,879 |
PDX: A Data Layout for Vector Similarity Search |
2025 |
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4.6292417e-05 |
| 7,989 |
RCRank: Multimodal Ranking of Root Causes of Slow Queries in Cloud Database Systems |
2025 |
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4.6124681e-05 |
| 8,020 |
The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions |
2024 |
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4.6040862e-05 |
| 8,041 |
DISTILL: Low-Overhead Data-Driven Techniques for Filtering and Costing Indexes for Scalable Index Tuning |
2022 |
VLDB |
4.5998045e-05 |
| 8,103 |
Grep: A Graph Learning Based Database Partitioning System |
2023 |
SIGMOD |
4.5852201e-05 |
| 8,131 |
Sibyl: Forecasting Time-Evolving Query Workloads |
2024 |
SIGMOD |
4.5784634e-05 |
| 8,186 |
E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model |
2025 |
VLDB |
4.5651684e-05 |
| 8,220 |
PerfGuard: Deploying ML-for-Systems without Performance Regressions, Almost! |
2021 |
VLDB |
4.5557328e-05 |
| 8,417 |
The Case for Learned In-Memory Joins |
2023 |
VLDB |
4.5194164e-05 |
| 8,659 |
Learned Offline Query Planning via Bayesian Optimization |
2025 |
SIGMOD |
4.4722928e-05 |
| 8,994 |
Automatic Index Selection for Large-Scale Datalog Computation |
2019 |
VLDB |
4.4129398e-05 |
| 9,006 |
Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems |
2024 |
VLDB |
4.4101482e-05 |
| 9,032 |
Sphinteract: Resolving Ambiguities in NL2SQL Through User Interaction |
2025 |
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4.4039656e-05 |
| 9,348 |
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4.3526427e-05 |
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4.3522361e-05 |
| 9,467 |
Database Gyms |
2023 |
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4.3346412e-05 |
| 9,960 |
An Elephant Under The Microscope: Analyzing The Interaction Of Optimizer Components In PostgreSQL |
2025 |
SIGMOD |
4.2294678e-05 |
| 9,961 |
QueryArtisan: Generating Data Manipulation Codes for Ad-hoc Analysis in Data Lakes |
2025 |
VLDB |
4.2294678e-05 |
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