MFTune: An Efficient Multi-fidelity Framework for Spark SQL Configuration Tuning
Summary: MFTune enables multi-fidelity Spark SQL tuning via representative SQL-subset fidelities that preserve bottleneck/performance correlations, unlike data reduction or early stopping. Density-based knob/range compression, transfer learning, and two-phase warm starts accelerate search and outperform five baselines. (summarized by gpt-5.6-luna on Aug 28 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Beicheng Xu (Peking University)
- 2. Lingching Tung (Peking University)
- 3. Yuchen Wang (Peking University)
- 4. Yupeng Lu (Peking University)
- 5. Bin Cui (Peking University)
BibTeX Citation
@article{xu_vldb26,
title = {{MFTune: An Efficient Multi-fidelity Framework for Spark SQL Configuration Tuning}},
author = {Xu, Beicheng and Tung, Lingching and Wang, Yuchen and Lu, Yupeng and Cui, Bin},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {11},
pages = {3649--3662},
doi = {10.14778/3836663.3836715},
url = {https://doi.org/10.14778/3836663.3836715},
year = {2026}
}Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 23 of 23 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 3,041 | Configuration-Parametric Query Optimization for Physical Design Tuning | 2008 | SIGMOD |
| 2 | 4,681 | LOCAT: Low-Overhead Online Configuration Auto-Tuning of Spark SQL Applications | 2022 | SIGMOD |
| 3 | 8,346 | SparkCruise: Workload Optimization in Managed Spark Clusters at Microsoft | 2021 | VLDB |
| 4 | 2,772 | Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation | 2022 | VLDB |
| 5 | 10,580 | MCTuner: Spatial Decomposition-Enhanced Database Tuning via LLM-Guided Exploration | 2026 | SIGMOD |
| 6 | 9,023 | Rockhopper: A Robust Optimizer for Spark Configuration Tuning in Production Environment | 2025 | SIGMOD |
| 7 | 5,967 | Speedup Your Analytics: Automatic Parameter Tuning for Databases and Big Data Systems | 2019 | VLDB |
| 8 | 9,321 | Dynamic Speculative Optimizations for SQL Compilation in Apache Spark | 2020 | VLDB |
| 9 | 6,450 | Towards General and Efficient Online Tuning for Spark | 2023 | VLDB |
| 10 | 8,004 | A Spark Optimizer for Adaptive, Fine-Grained Parameter Tuning | 2024 | VLDB |