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Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems

Summary: Boot speeds collection of runtime-behavior training data for self-driving DBMSs via macro- and micro-acceleration that alters query execution to emit approximate telemetry and skip repetitive execution. Integrated with a PostgreSQL gym, yields up to 268x speedup with modest accuracy loss. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13575
Venue
VLDB
Year
2024
Pagerank
4.4059413e-05
Overall Rank
9,012 | 37.37%
DOI
10.14778/3681954.3682030

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 6 of 6 citing papers.

Rank Citing Paper Year Venue Pagerank
8,660 Learned Offline Query Planning via Bayesian Optimization 2025 SIGMOD 4.4680058e-05
9,581 Low Rank Learning for Offline Query Optimization 2025 SIGMOD 4.3186744e-05
9,955 SCompression: Enhancing Database Knob Tuning Efficiency Through Slice-Based OLTP Workload Compression 2025 VLDB 4.2332427e-05
10,050 APQO: An Adaptive Framework for Parametric Query Optimization 2026 SIGMOD 4.1905499e-05
10,217 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! 2026 SIGMOD 4.1905499e-05
10,435 Automated Database Tuning vs. Human-Based Tuning in a Simulated Stressful Work Environment: A Demonstration of the Database Gym 2025 SIGMOD 4.1905499e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 48 of 48 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
183 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00036859633
237 An Efficient, Cost-Driven Index Selection Tool for Microsoft SQL Server 1997 VLDB 0.00031727601
329 Neo: A Learned Query Optimizer 2019 VLDB 0.00027301488
371 Self-Driving Database Management Systems 2017 CIDR 0.00025382677
606 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00019251186
634 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00018844568
704 Query-based Workload Forecasting for Self-Driving Database Management Systems 2018 SIGMOD 0.00017785557
779 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00016719473
870 Parametric Query Optimization 1992 VLDB 0.00015709369
876 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.00015660534
905 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00015423174
1,229 Toward a Progress Indicator for Database Queries 2004 SIGMOD 0.00013153898
1,268 Proactive Re-Optimization 2005 SIGMOD 0.00012914584
1,509 Estimating Progress of Execution for SQL Queries 2004 SIGMOD 0.0001158945
1,574 Approximate Query Processing: No Silver Bullet 2017 SIGMOD 0.00011289028
2,050 Automatically Indexing Millions of Databases in Microsoft Azure SQL Database 2019 SIGMOD 9.6883066e-05
2,090 Balsa: Learning a Query Optimizer Without Expert Demonstrations 2022 SIGMOD 9.5668285e-05
2,113 When Can We Trust Progress Estimators for SQL Queries? 2005 SIGMOD 9.5207583e-05
2,423 Data Synthesis based on Generative Adversarial Networks 2018 VLDB 8.8447357e-05
2,937 DSB: A Decision Support Benchmark for Workload-Driven and Traditional Database Systems 2021 VLDB 7.8552033e-05
2,995 A Sampling Algebra for Aggregate Estimation 2013 VLDB 7.7606324e-05
3,066 Learning a Partitioning Advisor for Cloud Databases 2020 SIGMOD 7.6255556e-05
3,102 Oracle Database Replay 2008 SIGMOD 7.5604346e-05
3,144 Active Learning for ML Enhanced Database Systems 2020 SIGMOD 7.4844943e-05
3,241 A Learned Query Rewrite System using Monte Carlo Tree Search 2022 VLDB 7.32744e-05
3,580 Query Performance Prediction for Concurrent Queries using Graph Embedding 2020 VLDB 6.9460425e-05
3,955 Efficiently Approximating Selectivity Functions using Low Overhead Regression Models 2020 VLDB 6.5895015e-05
4,216 Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation 2021 VLDB 6.3448176e-05
4,587 MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems 2021 SIGMOD 6.0594195e-05
4,730 UDO: Universal Database Optimization using Reinforcement Learning 2021 VLDB 5.9604983e-05
5,673 Budget-aware Index Tuning with Reinforcement Learning 2022 SIGMOD 5.3789277e-05
5,834 An Efficient Transfer Learning Based Configuration Adviser for Database Tuning 2024 VLDB 5.3082111e-05
5,844 Stage: Query Execution Time Prediction in Amazon Redshift 2024 SIGMOD 5.3060581e-05
5,994 Steering Query Optimizers: A Practical Take on Big Data Workloads 2021 SIGMOD 5.2367998e-05
6,328 A Comparative Study and Component Analysis of Query Plan Representation Techniques in ML4DB Studies 2024 VLDB 5.1034426e-05
6,341 Operator and Query Progress Estimation in Microsoft SQL Server Live Query Statistics 2016 SIGMOD 5.0980049e-05
6,364 ISUM: Efficiently Compressing Large and Complex Workloads for Scalable Index Tuning 2022 SIGMOD 5.0895007e-05
6,402 Approximate Query Engines: Commercial Challenges and Research Opportunities 2017 SIGMOD 5.0725227e-05
6,478 A Statistical Approach Towards Robust Progress Estimation 2012 VLDB 5.040535e-05
6,507 Expand your Training Limits! Generating Training Data for ML-based Data Management 2021 SIGMOD 5.0273414e-05
6,774 A Unified Transferable Model for ML-Enhanced DBMS 2022 CIDR 4.9253635e-05
8,003 The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions 2024 VLDB 4.6049527e-05
8,036 Tastes Great! Less Filling! High Performance and Accurate Training Data Collection for Self-Driving Database Management Systems 2022 SIGMOD 4.5965825e-05
8,043 DISTILL: Low-Overhead Data-Driven Techniques for Filtering and Costing Indexes for Scalable Index Tuning 2022 VLDB 4.5954398e-05
8,378 Towards Building Autonomous Data Services on Azure 2023 SIGMOD 4.5275731e-05
9,469 Database Gyms 2023 CIDR 4.3304872e-05
9,930 Wred: Workload Reduction for Scalable Index Tuning 2024 SIGMOD 4.2469394e-05
9,931 Wii: Dynamic Budget Reallocation In Index Tuning 2024 SIGMOD 4.2469394e-05
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Semantically Similar Papers

Overall Rank Paper Year Venue Pagerank
183 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00036859633
4,216 Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation 2021 VLDB 6.3448176e-05
10,217 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! 2026 SIGMOD 4.1905499e-05
8,003 The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions 2024 VLDB 4.6049527e-05
704 Query-based Workload Forecasting for Self-Driving Database Management Systems 2018 SIGMOD 0.00017785557
371 Self-Driving Database Management Systems 2017 CIDR 0.00025382677
4,587 MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems 2021 SIGMOD 6.0594195e-05
8,036 Tastes Great! Less Filling! High Performance and Accurate Training Data Collection for Self-Driving Database Management Systems 2022 SIGMOD 4.5965825e-05
10,435 Automated Database Tuning vs. Human-Based Tuning in a Simulated Stressful Work Environment: A Demonstration of the Database Gym 2025 SIGMOD 4.1905499e-05
9,469 Database Gyms 2023 CIDR 4.3304872e-05