Verdict: A System for Stochastic Query Planning
Summary: Verdict: an approximate query-processing system that provides immediate, interactive answers using carefully chosen samples with statistical error bounds. Novelty: stochastic query planning that schedules execution over samples to guarantee interactivity at any scale, trading exactness for bounded error. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Barzan Mozafari (University of Michigan)
BibTeX Citation
@inproceedings{mozafari_cidr15,
address = {Amsterdam, Netherlands},
series = {{CIDR} '15},
title = {{Verdict: A System for Stochastic Query Planning}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Mozafari, Barzan},
year = {2015}
}Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 772 | VerdictDB: Universalizing Approximate Query Processing | 2018 | SIGMOD | 0.00014147905 |
| 1,995 | Database Learning: Toward a Database that Becomes Smarter Every Time | 2017 | SIGMOD | 9.3403665e-05 |
| 5,906 | Approximate Query Engines: Commercial Challenges and Research Opportunities | 2017 | SIGMOD | 6.0457047e-05 |
| 11,916 | Demonstration of VerdictDB, the Platform-Independent AQP System | 2018 | SIGMOD | 5.093636e-05 |
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