DBScholar

Back to papers

The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions

Summary: Proto-X holistically tunes multiple DBMS configuration spaces, learning cross-space similarities and synthesizing proto-actions to coordinate search rather than sequentially tuning knobs, hints, and indexes. On PostgreSQL, it handles orders-of-magnitude larger spaces and improves performance up to 53% over prior methods. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
h0d2ec23d398ffd06
Venue
VLDB
Year
2024
Pagerank
5.4142519e-05
Overall Rank
7,977 | 46.37%
DOI
10.14778/3681954.3682007

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{zhang_vldb24,
        title = {{The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions}},
        author = {Zhang, William and Lim, Wan Shen and Butrovich, Matthew and Pavlo, Andrew},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {11},
        pages = {3373--3387},
        doi = {10.14778/3681954.3682007},
        url = {https://doi.org/10.14778/3681954.3682007},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 6 of 6 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 50 of 67 cited papers.

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

Rank Cited Paper Year Venue Pagerank
15 How Good Are Query Optimizers, Really? 2016 VLDB 0.00061066921
78 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00036684414
145 Neo: A Learned Query Optimizer 2019 VLDB 0.0002908188
224 Self-Driving Database Management Systems 2017 CIDR 0.00024013745
235 OLTP-Bench: An Extensible Testbed for Benchmarking Relational Databases 2014 VLDB 0.00023697028
314 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.00021282642
318 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021167555
362 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00019989474
378 AutoAdmin "What-if" Index Analysis Utility 1998 SIGMOD 0.00019549382
379 Apache Calcite: A Foundational Framework for Optimized Query Processing Over Heterogeneous Data Sources 2018 SIGMOD 0.00019514689
437 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00018315867
460 Query-based Workload Forecasting for Self-Driving Database Management Systems 2018 SIGMOD 0.00017842695
491 Database Tuning Advisor for Microsoft SQL Server 2005 2004 VLDB 0.00017413042
560 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.00016403151
751 Automatic Physical Database Tuning: A Relaxation-based Approach 2005 SIGMOD 0.0001425375
1,199 Balsa: Learning a Query Optimizer Without Expert Demonstrations 2022 SIGMOD 0.00011563985
1,279 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00011226878
1,289 An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems 2021 VLDB 0.00011162479
1,397 Magic mirror in my hand, which is the best in the land? An Experimental Evaluation of Index Selection Algorithms 2020 VLDB 0.00010789242
1,515 DSB: A Decision Support Benchmark for Workload-Driven and Traditional Database Systems 2021 VLDB 0.00010417728
1,516 Automatically Indexing Millions of Databases in Microsoft Azure SQL Database 2019 SIGMOD 0.00010402594
2,210 Lero: A Learning-to-Rank Query Optimizer 2023 VLDB 8.8257742e-05
2,250 QueryFormer: A Tree Transformer Model for Query Plan Representation 2022 VLDB 8.7533306e-05
2,275 Active Learning for ML Enhanced Database Systems 2020 SIGMOD 8.7090584e-05
2,395 A Learned Query Rewrite System using Monte Carlo Tree Search 2022 VLDB 8.5281914e-05
2,522 Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation 2022 VLDB 8.3477168e-05
2,765 Instance-Optimized Data Layouts for Cloud Analytics Workloads 2021 SIGMOD 8.0439015e-05
2,772 Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation 2022 VLDB 8.035288e-05
2,842 Query Performance Prediction for Concurrent Queries using Graph Embedding 2020 VLDB 7.949193e-05
3,051 LlamaTune: Sample-Efficient DBMS Configuration Tuning 2022 VLDB 7.7055931e-05
3,158 CGPTuner: a Contextual Gaussian Process Bandit Approach for the Automatic Tuning of IT Configurations Under Varying Workload Conditions 2021 VLDB 7.5811757e-05
3,327 Robust Query Driven Cardinality Estimation under Changing Workloads 2023 VLDB 7.4207879e-05
3,590 Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation 2021 VLDB 7.1865343e-05
3,645 UDO: Universal Database Optimization using Reinforcement Learning 2021 VLDB 7.1397796e-05
3,714 The Case for a Learned Sorting Algorithm 2020 SIGMOD 7.0769061e-05
3,965 MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems 2021 SIGMOD 6.8918628e-05
4,007 Automated Generation of Materialized Views in Oracle 2020 VLDB 6.8592987e-05
4,197 Proteus: A Self-Designing Range Filter 2022 SIGMOD 6.7417716e-05
4,202 Kepler: Robust Learning for Faster Parametric Query Optimization 2023 SIGMOD 6.7374091e-05
4,468 Real-time Workload Pattern Analysis for Large-scale Cloud Databases 2023 VLDB 6.5863349e-05
4,683 AutoSteer: Learned Query Optimization for Any SQL Database 2023 VLDB 6.4716143e-05
4,711 Learned Index Benefits: Machine Learning Based Index Performance Estimation 2022 VLDB 6.4573842e-05
4,850 The RLR-Tree: A Reinforcement Learning Based R-Tree for Spatial Data 2023 SIGMOD 6.3808017e-05
4,968 Budget-aware Index Tuning with Reinforcement Learning 2022 SIGMOD 6.3348803e-05
5,022 Analyzing the Impact of Cardinality Estimation on Execution Plans in Microsoft SQL Server 2023 VLDB 6.3100988e-05
5,039 Leveraging Query Logs and Machine Learning for Parametric Query Optimization 2022 VLDB 6.3023214e-05
5,058 Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing 2022 VLDB 6.2926774e-05
5,194 Database Workload Characterization with Query Plan Encoders 2022 VLDB 6.2353557e-05
5,214 Stage: Query Execution Time Prediction in Amazon Redshift 2024 SIGMOD 6.2248104e-05
5,241 FASTgres: Making Learned Query Optimizer Hinting Effective 2023 VLDB 6.2154384e-05
Previous Page 1 / 2 Next

Semantically Similar Papers