Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing
Summary: Fine-grained instance-level modeling with a MaxCompute-based architecture decomposes resource optimization into simpler, multi-objective decisions (partition count, placement, per-instance resources). Novel predictive models and optimization methods enable sub-second RO and yield 37–72% latency and 43–78% cost reductions on production workloads. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Chenghao Lyu (University of Massachusetts Amherst)
- 2. Qi Fan (Ecole Polytechnique)
- 3. Fei Song (Ecole Polytechnique)
- 4. Arnab Sinha (Ecole Polytechnique)
- 5. Yanlei Diao (Ecole Polytechnique; University of Massachusetts Amherst)
- 6. Wei Chen (Alibaba)
- 7. Li Ma (Alibaba)
- 8. Yihui Feng (Alibaba)
- 9. Yaliang Li (Alibaba)
- 10. Kai Zeng (Alibaba)
- 11. Jingren Zhou (Alibaba)
BibTeX Citation
@article{lyu_vldb22,
title = {{Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing}},
author = {Lyu, Chenghao and Fan, Qi and Song, Fei and Sinha, Arnab and Diao, Yanlei and Chen, Wei and Ma, Li and Feng, Yihui and Li, Yaliang and Zeng, Kai and Zhou, Jingren},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {11},
pages = {3098--3111},
doi = {10.14778/3551793.3551855},
url = {https://doi.org/10.14778/3551793.3551855},
year = {2022}
}
Incoming Citations (Sorted by Pagerank)
Showing 8 of 8 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,107 | Stage: Query Execution Time Prediction in Amazon Redshift | 2024 | SIGMOD | 6.3623786e-05 |
| 5,188 | Resource Management in Aurora Serverless | 2024 | VLDB | 6.3278921e-05 |
| 7,589 | Cost-Intelligent Data Analytics in the Cloud | 2024 | CIDR | 5.5907048e-05 |
| 7,846 | The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions | 2024 | VLDB | 5.5331459e-05 |
| 8,572 | T3: Accurate and Fast Performance Prediction for Relational Database Systems With Compiled Decision Trees | 2025 | SIGMOD | 5.4102362e-05 |
| 8,615 | A Spark Optimizer for Adaptive, Fine-Grained Parameter Tuning | 2024 | VLDB | 5.4005602e-05 |
| 10,969 | Improving DBMS Scheduling Decisions with Accurate Performance Prediction on Concurrent Queries | 2025 | VLDB | 5.093636e-05 |
| 11,083 | Graph Transformers for Query Plan Representation: Potentials and Challenges | 2025 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 41 of 41 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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