Peering through the Dark: An Owl's View of Inter-job Dependencies and Jobs' Impact in Shared Clusters
Summary: Owl analyzes cluster logs to extract and visualize inter-job dependencies in shared multi-tenant infrastructures. It introduces a novel job-valuation algorithm that quantifies a job's impact on dependents and downstream users. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Andrew Chung (Carnegie Mellon University)
- 2. Carlo Curino (Microsoft)
- 3. Subru Krishnan (Microsoft)
- 4. Konstantinos Karanasos (Microsoft)
- 5. Panagiotis Garefalakis (Imperial College London)
- 6. Gregory R. Ganger (Carnegie Mellon University)
BibTeX Citation
@inproceedings{chung_sigmod19,
title = {{Peering through the Dark: An Owl's View of Inter-job Dependencies and Jobs' Impact in Shared Clusters}},
author = {Chung, Andrew and Curino, Carlo and Krishnan, Subru and Karanasos, Konstantinos and Garefalakis, Panagiotis and Ganger, Gregory R.},
series = {{SIGMOD} '19},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3299869.3320239},
url = {https://dl.acm.org/doi/10.1145/3299869.3320239},
year = {2019}
}
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Outgoing Citations (Sorted by Pagerank)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 514 | Goods: Organizing Google's Datasets | 2016 | SIGMOD | 0.00017178673 |
| 1,077 | DataHub: Collaborative Data Science & Dataset Version Management at Scale | 2015 | CIDR | 0.00012269438 |
| 1,902 | Ground: A Data Context Service | 2017 | CIDR | 9.506714e-05 |
| 7,878 | Dependency-Driven Analytics: a Compass for Uncharted Data Oceans | 2017 | CIDR | 5.5246167e-05 |
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