iQCAR: A Demonstration of an Inter-Query Contention Analyzer for Cluster Computing Frameworks
Summary: Demonstrates iQCAR, a model of inter-query contention in clusters, using an iQC-Graph to attribute interference among concurrent queries. An interactive demo to identify top victims/sources, diagnose hotspots, and compare scheduler rules by predicting impact on later runs. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Prajakta Kalmegh (Duke University)
- 2. Harrison Lundberg (Duke University)
- 3. Frederick Xu (Duke University)
- 4. Shivnath Babu (Duke University)
- 5. Sudeepa Roy (Duke University)
BibTeX Citation
@inproceedings{kalmegh_sigmod18,
title = {{iQCAR: A Demonstration of an Inter-Query Contention Analyzer for Cluster Computing Frameworks}},
author = {Kalmegh, Prajakta and Lundberg, Harrison and Xu, Frederick and Babu, Shivnath and Roy, Sudeepa},
series = {{SIGMOD} '18},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3183713.3193567},
url = {https://dl.acm.org/doi/10.1145/3183713.3193567},
year = {2018}
}Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,112 | iQCAR: inter-Query Contention Analyzer for Data Analytics Frameworks | 2019 | SIGMOD | 5.8826029e-05 |
| 6,699 | Toward Interpretable and Actionable Data Analysis with Explanations and Causality | 2022 | VLDB | 5.7058728e-05 |
| 10,739 | Database Views as Explanations for Relational Deep Learning | 2026 | VLDB | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 1 of 1 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,708 | PerfXplain: Debugging MapReduce Job Performance | 2012 | VLDB | 9.8224587e-05 |
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