A Concave Path to Low-overhead Robust Query Processing
Summary: FrugalSpillBound exploits concave-down plan costs to slash SpillBound’s compilation overhead while retaining robust-query guarantees. Relaxing guarantees 2× cuts overhead by 100–1000×, extending worst-case query processing from canned to ad-hoc OLAP workloads. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Srinivas Karthik (Indian Institute of Science)
- 2. Jayant R. Haritsa (Indian Institute of Science)
- 3. Sreyash Kenkre (IBM)
- 4. Vinayaka Pandit (IBM)
BibTeX Citation
@article{karthik_vldb18,
title = {{A Concave Path to Low-overhead Robust Query Processing}},
author = {Karthik, Srinivas and Haritsa, Jayant R. and Kenkre, Sreyash and Pandit, Vinayaka},
journal = {PVLDB},
series = {{VLDB} '18},
volume = {11},
number = {13},
pages = {2183--2195},
doi = {10.14778/3275366.3275368},
url = {https://doi.org/10.14778/3275366.3275368},
year = {2018}
}
Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,958 | Robust Query Processing: Mission Possible | 2020 | VLDB | 5.4164639e-05 |
| 8,393 | PARQO: Penalty-Aware Robust Plan Selection in Query Optimization | 2024 | VLDB | 5.3387995e-05 |
| 8,681 | Adaptive Code Generation for Data-Intensive Analytics | 2021 | VLDB | 5.288863e-05 |
| 9,735 | PAR2QO: Parametric Penalty-Aware Robust Query Optimization | 2025 | VLDB | 5.1325223e-05 |
| 10,380 | Coresets for Robust Query Optimization | 2026 | PODS | 4.9769913e-05 |
| 11,291 | Robust Plan Evaluation based on Approximate Probabilistic Machine Learning | 2025 | VLDB | 4.9769913e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 11 of 11 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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