ROBUS: Fair Cache Allocation for Data-parallel Workloads
Summary: ROBUS: a fair cache allocator for data-parallel, multi-tenant workloads. Defines a core-based fairness model (Pareto efficiency, envy-freeness) with randomized batching and polynomial-time approximations to achieve core-in-expectation fairness; prototype on Spark's RDD store demonstrates performance and fairness gains. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Mayuresh Kunjir (Duke University)
- 2. Brandon Fain (Duke University)
- 3. Kamesh Munagala (Duke University)
- 4. Shivnath Babu (Duke University)
BibTeX Citation
@inproceedings{kunjir_sigmod17,
title = {{ROBUS: Fair Cache Allocation for Data-parallel Workloads}},
author = {Kunjir, Mayuresh and Fain, Brandon and Munagala, Kamesh and Babu, Shivnath},
series = {{SIGMOD} '17},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3035918.3064018},
url = {https://dl.acm.org/doi/10.1145/3035918.3064018},
year = {2017}
}
Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,686 | Black or White? How to Develop an AutoTuner for Memory-based Analytics | 2020 | SIGMOD | 0.00010008686 |
| 1,765 | Selecting Subexpressions to Materialize at Datacenter Scale | 2018 | VLDB | 9.8079546e-05 |
| 3,605 | Computation Reuse in Analytics Job Service at Microsoft | 2018 | SIGMOD | 7.2640711e-05 |
| 7,639 | Budget Sharing for Multi-Analyst Differential Privacy | 2021 | VLDB | 5.5767645e-05 |
| 7,722 | ChronoCache: Predictive and Adaptive Mid-Tier Query Result Caching | 2020 | SIGMOD | 5.5586232e-05 |
| 9,982 | Thoth in Action: Memory Management in Modern Data Analytics | 2017 | VLDB | 5.1844786e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 18 of 18 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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