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Black or White? How to Develop an AutoTuner for Memory-based Analytics

Summary: RelM, a white-box memory autotuner, exploits interactions from containers to JVM for near-optimal tuning with low overhead. Guided-BO speeds Bayesian optimization with RelM; Spark tests show near-brute-force quality at reduced cost. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hababcaad858a783c
Venue
SIGMOD
Year
2020
Pagerank
9.8403606e-05
Overall Rank
1,699 | 88.59%
DOI
10.1145/3318464.3380591

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{kunjir_sigmod20,
        title = {{Black or White? How to Develop an AutoTuner for Memory-based Analytics}},
        author = {Kunjir, Mayuresh and Babu, Shivnath},
        series = {{SIGMOD} '20},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3318464.3380591},
        url = {https://dl.acm.org/doi/10.1145/3318464.3380591},
        year = {2020}
}

Incoming Citations (Sorted by Pagerank)

Showing 27 of 27 citing papers.

Rank Citing Paper Year Venue Pagerank
1,289 An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems 2021 VLDB 0.00011159167
2,227 GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization 2024 VLDB 8.8007923e-05
2,721 ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases 2021 SIGMOD 8.0931221e-05
2,770 Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation 2022 VLDB 8.0343719e-05
2,908 AI Meets Database: AI4DB and DB4AI 2021 SIGMOD 7.8716173e-05
3,964 MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems 2021 SIGMOD 6.889374e-05
4,080 Towards Dynamic and Safe Configuration Tuning for Cloud Databases 2022 SIGMOD 6.8151596e-05
4,459 Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process 2022 SIGMOD 6.5883555e-05
4,686 LOCAT: Low-Overhead Online Configuration Auto-Tuning of Spark SQL Applications 2022 SIGMOD 6.4690725e-05
4,743 Machine Learning for Databases 2021 VLDB 6.4379536e-05
5,080 DBPA: A Benchmark for Transactional Database Performance Anomalies 2023 SIGMOD 6.2830313e-05
5,284 An Efficient Transfer Learning Based Configuration Adviser for Database Tuning 2024 VLDB 6.1963031e-05
5,438 Eraser: Eliminating Performance Regression on Learned Query Optimizer 2024 VLDB 6.1278045e-05
5,973 Towards instance-optimized data systems 2021 VLDB 5.9281867e-05
6,453 Towards General and Efficient Online Tuning for Spark 2023 VLDB 5.7790502e-05
6,732 A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning 2023 SIGMOD 5.6921776e-05
7,072 E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model 2025 VLDB 5.6053987e-05
8,009 A Spark Optimizer for Adaptive, Fine-Grained Parameter Tuning 2024 VLDB 5.4063491e-05
8,210 Grep: A Graph Learning Based Database Partitioning System 2023 SIGMOD 5.3761621e-05
10,089 ContTune: Continuous Tuning by Conservative Bayesian Optimization for Distributed Stream Data Processing Systems 2023 VLDB 5.0806786e-05
10,477 HAMMER: An Automatic RAG Tuning System via Hierarchical Memory-Guided Monte Carlo Tree Search 2026 SIGMOD 4.9769913e-05
10,591 MCTuner: Spatial Decomposition-Enhanced Database Tuning via LLM-Guided Exploration 2026 SIGMOD 4.9769913e-05
11,112 Centrum: Model-based Database Auto-tuning with Minimal Distributional Assumptions 2025 SIGMOD 4.9769913e-05
11,295 AQETuner: Reliable Query-level Configuration Tuning for Analytical Query Engines 2025 VLDB 4.9769913e-05
11,598 Agile-Ant: Self-managing Distributed Cache Management for Cost Optimization of Big Data Applications 2024 VLDB 4.9769913e-05
11,854 Juggler: Autonomous Cost Optimization and Performance Prediction of Big Data Applications 2022 SIGMOD 4.9769913e-05
11,917 SparkCAD: Caching Anomalies Detector for Spark Applications 2022 VLDB 4.9769913e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 16 of 16 cited papers.

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

Rank Cited Paper Year Venue Pagerank
78 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00036675568
88 Automated Selection of Materialized Views and Indexes for SQL Databases 2000 VLDB 0.00035340164
144 Neo: A Learned Query Optimizer 2019 VLDB 0.00029090793
151 An Efficient, Cost-Driven Index Selection Tool for Microsoft SQL Server 1997 VLDB 0.00028664776
243 Automating Physical Database Design in a Parallel Database 2002 SIGMOD 0.00023349603
314 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.00021276452
322 Tuning Database Configuration Parameters with iTuned 2009 VLDB 0.00021034201
437 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00018310278
508 Adaptive Self-Tuning Memory in DB2 2006 VLDB 0.00017083245
598 Automatic Performance Diagnosis and Tuning in Oracle 2005 CIDR 0.0001575517
781 Self-tuning Database Technology and Information Services: from Wishful Thinking to Viable Engineering 2002 VLDB 0.00014019939
940 Starfish: A Self-tuning System for Big Data Analytics 2011 CIDR 0.00012959992
5,091 ROBUS: Fair Cache Allocation for Data-parallel Workloads 2017 SIGMOD 6.2775613e-05
7,638 MRTuner: A Toolkit to Enable Holistic Optimization for MapReduce Jobs 2014 VLDB 5.4767699e-05
9,199 Tempo: Robust and Self-Tuning Resource Management in Multi-tenant Parallel Databases 2016 VLDB 5.2088173e-05
10,164 Thoth in Action: Memory Management in Modern Data Analytics 2017 VLDB 5.0664415e-05
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