Scalable Approximate Query Processing With The DBO Engine
Summary: Scalable AQP for ad-hoc analytics in DBO; running aggregate guess with statistically meaningful bounds. As more data is processed, the guess converges to exact result; users may stop early when accuracy is satisfactory, enabling exploratory data analysis. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Christopher Jermaine (University of Florida)
- 2. Subramanian Arumugam (University of Florida)
- 3. Abhijit Pol (University of Florida)
- 4. Alin Dobra (University of Florida)
BibTeX Citation
@inproceedings{jermaine_sigmod07,
title = {{Scalable Approximate Query Processing With The DBO Engine}},
author = {Jermaine, Christopher and Arumugam, Subramanian and Pol, Abhijit and Dobra, Alin},
series = {{SIGMOD} '07},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1247480.1247560},
url = {https://dl.acm.org/doi/10.1145/1247480.1247560},
year = {2007}
}Incoming Citations (Sorted by Pagerank)
Showing 38 of 38 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9 | Online Aggregation | 1997 | SIGMOD | 0.00076195956 |
| 57 | On Random Sampling over Joins | 1999 | SIGMOD | 0.00040108301 |
| 135 | Ripple Joins for Online Aggregation | 1999 | SIGMOD | 0.00029866033 |
| 477 | Random Sampling from B+ trees | 1989 | VLDB | 0.00017632787 |
| 1,229 | Random Sampling from Hash Files | 1990 | SIGMOD | 0.00011420642 |
| 1,820 | A Scalable Hash Ripple Join Algorithm | 2002 | SIGMOD | 9.5690887e-05 |
| 2,845 | Progressive Merge Join: A Generic and Non-Blocking Sort-Based Join Algorithm | 2002 | VLDB | 7.9474809e-05 |
| 4,217 | A Disk-Based Join With Probabilistic Guarantees* | 2005 | SIGMOD | 6.7271293e-05 |
| 5,608 | On Producing Join Results Early | 2003 | PODS | 6.0692914e-05 |
| 13,050 | Online Estimation For Subset-Based SQL Queries | 2005 | VLDB | 4.9793485e-05 |
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| 1 | 931 | Dynamic Sample Selection for Approximate Query Processing | 2003 | SIGMOD |
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| 3 | 1,428 | Knowing When You’re Wrong: Building Fast and Reliable Approximate Query Processing Systems | 2014 | SIGMOD |
| 4 | 4,781 | Learned Approximate Query Processing: Make it Light, Accurate and Fast | 2021 | CIDR |
| 5 | 518 | Query by Output | 2009 | SIGMOD |
| 6 | 2,655 | A Robust, Optimization-Based Approach for Approximate Answering of Aggregate Queries | 2001 | SIGMOD |
| 7 | 2,224 | DAQ: A New Paradigm for Approximate Query Processing | 2015 | VLDB |
| 8 | 3,213 | Turbo-Charging Estimate Convergence in DBO | 2009 | VLDB |
| 9 | 1,829 | DBEst: Revisiting Approximate Query Processing Engines with Machine Learning Models | 2019 | SIGMOD |
| 10 | 8,543 | The DBO Database System | 2008 | SIGMOD |