Fangorn: Adaptive Execution Framework for Heterogeneous Workloads on Shared Clusters
Summary: Fangorn is an adaptive execution framework on shared clusters, built on an enriched graph model to orchestrate heterogeneous workloads with both long-running and on-demand resources. Runtime statistics and pluggable components enable cross-engine adaptation (relational to DL) on Alibaba production clusters, handling tens of millions of jobs daily, from one to half-million. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Yingda Chen (Alibaba)
- 2. Jiamang Wang (Alibaba)
- 3. Yifeng Lu (Alibaba)
- 4. Ying Han (Alibaba)
- 5. Zhiqiang Lv (Alibaba)
- 6. Xuebin Min (Alibaba)
- 7. Hua Cai (Alibaba)
- 8. Wei Zhang (Alibaba)
- 9. Haochuan Fan (Alibaba)
- 10. Chao Li (Alibaba)
- 11. Tao Guan (Alibaba)
- 12. Wei Lin (Alibaba)
- 13. Yangqing Jia (Alibaba)
- 14. Jingren Zhou (Alibaba)
BibTeX Citation
@article{chen_vldb21,
title = {{Fangorn: Adaptive Execution Framework for Heterogeneous Workloads on Shared Clusters}},
author = {Chen, Yingda and Wang, Jiamang and Lu, Yifeng and Han, Ying and Lv, Zhiqiang and Min, Xuebin and Cai, Hua and Zhang, Wei and Fan, Haochuan and Li, Chao and Guan, Tao and Lin, Wei and Jia, Yangqing and Zhou, Jingren},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {12},
pages = {2972--2985},
doi = {10.14778/3476311.3476376},
url = {https://doi.org/10.14778/3476311.3476376},
year = {2021}
}
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