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)
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}
}
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