Demonstration of BitGourmet: Data Analysis via Deterministic Approximation
Summary: BitGourmet demonstrates deterministic approximate query processing (DAQ) for bounds-guaranteed aggregates. Vertical bitwise partitioning with bit-vector subsets and a scenario-aware optimizer let users specify precision and trade latency for interactivity. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Saehan Jo (Cornell University)
- 2. Immanuel Trummer (Cornell University)
BibTeX Citation
@inproceedings{jo_sigmod20,
title = {{Demonstration of BitGourmet: Data Analysis via Deterministic Approximation}},
author = {Jo, Saehan and Trummer, Immanuel},
series = {{SIGMOD} '20},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3318464.3384709},
url = {https://dl.acm.org/doi/10.1145/3318464.3384709},
year = {2020}
}Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|
Previous
Page 1 / 1
Next
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 |
| 336 | The Aqua Approximate Query Answering System | 1999 | SIGMOD | 0.00020657819 |
| 596 | Wander Join: Online Aggregation via Random Walks | 2016 | SIGMOD | 0.00015785583 |
| 840 | Quickr: Lazily Approximating Complex AdHoc Queries in BigData Clusters | 2016 | SIGMOD | 0.0001354605 |
| 1,082 | Approximate Query Processing: No Silver Bullet | 2017 | SIGMOD | 0.00012122749 |
| 2,027 | Database Learning: Toward a Database that Becomes Smarter Every Time | 2017 | SIGMOD | 9.1618139e-05 |
| 2,224 | DAQ: A New Paradigm for Approximate Query Processing | 2015 | VLDB | 8.80823e-05 |
| 2,456 | A Sampling Algebra for Aggregate Estimation | 2013 | VLDB | 8.4377192e-05 |
| 3,424 | AQP++: Connecting Approximate Query Processing With Aggregate Precomputation for Interactive Analytics | 2018 | SIGMOD | 7.3117029e-05 |
| 12,052 | BitGourmet: Deterministic Approximation via Optimized Bit Selection | 2020 | CIDR | 4.9793485e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 4,781 | Learned Approximate Query Processing: Make it Light, Accurate and Fast | 2021 | CIDR |
| 2 | 12,145 | Query-Driven Learning for Next Generation Predictive Modeling & Analytics | 2019 | SIGMOD |
| 3 | 12,758 | Conditioning and Aggregating Uncertain Data Streams: Going Beyond Expectations | 2010 | VLDB |
| 4 | 11,079 | Efficient Approximate Query Processing with Block Sampling | 2025 | CIDR |
| 5 | 4,391 | Bitvector-aware Query Optimization for Decision Support Queries | 2020 | SIGMOD |
| 6 | 1,829 | DBEst: Revisiting Approximate Query Processing Engines with Machine Learning Models | 2019 | SIGMOD |
| 7 | 2,000 | Sample + Seek: Approximating Aggregates with Distribution Precision Guarantee | 2016 | SIGMOD |
| 8 | 12,117 | Demonstration of ScroogeDB: Getting More Bang For the Buck with Deterministic Approximation in the Cloud | 2020 | VLDB |
| 9 | 2,224 | DAQ: A New Paradigm for Approximate Query Processing | 2015 | VLDB |
| 10 | 12,052 | BitGourmet: Deterministic Approximation via Optimized Bit Selection | 2020 | CIDR |