Speedup Your Analytics: Automatic Parameter Tuning for Databases and Big Data Systems

Summary: Survey of parameter tuning for databases, Hadoop, and Spark, with six approaches: rule-based, cost modeling, simulation, experiment-driven, ML, adaptive tuning. Outlines foundations, pros/cons, cloud, and challenges in heterogeneity and real-time analytics. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 12102
Venue: VLDB
Year: 2019
Pagerank: 6.0619534e-05
Overall Rank: 5,865 | 59.77%
DOI: 10.14778/3352063.3352112

Incoming Non-self Citations Over Time

Authors

1. Jiaheng Lu (University of Helsinki)
2. Yuxing Chen (University of Helsinki)
3. Herodotos Herodotou (Cyprus University of Technology)
4. Shivnath Babu (Duke University)

BibTeX Citation

@article{lu_vldb19,
        title = {{Speedup Your Analytics: Automatic Parameter Tuning for Databases and Big Data Systems}},
        author = {Lu, Jiaheng and Chen, Yuxing and Herodotou, Herodotos and Babu, Shivnath},
        journal = {PVLDB},
        series = {{VLDB} '19},
        volume = {12},
        number = {12},
        pages = {1970--1973},
        doi = {10.14778/3352063.3352112},
        url = {https://doi.org/10.14778/3352063.3352112},
        year = {2019}
}

Incoming Citations (Sorted by Pagerank)

Showing 9 of 9 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
2,888	AI Meets Database: AI4DB and DB4AI	2021	SIGMOD	7.9941489e-05
4,449	From BERT to GPT-3 Codex: Harnessing the Potential of Very Large Language Models for Data Management	2022	VLDB	6.697553e-05
5,226	Breaking Down Memory Walls: Adaptive Memory Management in LSM-based Storage Systems	2021	VLDB	6.3090383e-05
5,974	Towards instance-optimized data systems	2021	VLDB	6.0230488e-05
6,939	Multi-Tenant Cloud Data Services: State-of-the-Art, Challenges and Opportunities	2022	SIGMOD	5.7338637e-05
7,686	TDSQL: Tencent Distributed Database System	2024	VLDB	5.5676271e-05
9,973	Exploiting Structure in Regular Expression Queries	2023	SIGMOD	5.1845938e-05
10,700	TXSQL: Lock Optimizations Towards High Contented Workloads	2025	SIGMOD	5.093636e-05
11,382	How To Optimize My Blockchain? A Multi-Level Recommendation Approach	2023	SIGMOD	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
44	A Comparison of Approaches to Large-Scale Data Analysis	2009	SIGMOD	0.00046055057
86	Automatic Database Management System Tuning Through Large-scale Machine Learning	2017	SIGMOD	0.00035316107
347	Tuning Database Configuration Parameters with iTuned	2009	VLDB	0.00020651582
523	Adaptive Self-Tuning Memory in DB2	2006	VLDB	0.00017133451
625	Automatic Performance Diagnosis and Tuning in Oracle	2005	CIDR	0.0001566968
735	Profiling, What-if Analysis, and Cost-based Optimization of MapReduce Programs	2011	VLDB	0.00014522606
923	Starfish: A Self-tuning System for Big Data Analytics	2011	CIDR	0.00013189886
1,436	The Performance of MapReduce: An In-depth Study	2010	VLDB	0.00010797443
3,400	A Demonstration of the OtterTune Automatic Database Management System Tuning Service	2018	VLDB	7.4433294e-05
6,131	Foundations of Automated Database Tuning	2006	VLDB	5.966557e-05
6,700	Self-Managing Technology in Database Management Systems	2004	VLDB	5.7981065e-05
7,546	MRTuner: A Toolkit to Enable Holistic Optimization for MapReduce Jobs	2014	VLDB	5.6024593e-05
9,039	Tempo: Robust and Self-Tuning Resource Management in Multi-tenant Parallel Databases	2016	VLDB	5.3267474e-05

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