Online Query Processing: A Tutorial
Summary: Survey of online query processing: aggregation with estimates and confidence intervals; online enumeration yields incremental results. Highlights feedback and user control; outlines a research agenda: architectures, sampling/estimation, visualization. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Peter J. Haas (IBM)
- 2. Joseph M. Hellerstein (University of California Berkeley)
BibTeX Citation
@inproceedings{haas_sigmod01,
title = {{Online Query Processing: A Tutorial}},
author = {Haas, Peter J. and Hellerstein, Joseph M.},
series = {{SIGMOD} '01},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/375663.375800},
url = {https://dl.acm.org/doi/10.1145/375663.375800},
year = {2001}
}Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 926 | Improving Approximate Nearest Neighbor Search through Learned Adaptive Early Termination | 2020 | SIGMOD | 0.00013181732 |
| 5,367 | Tweets as Data: Demonstration of TweeQL and TwitInfo | 2011 | SIGMOD | 6.2448491e-05 |
| 6,562 | Query Sampling in DB2 Universal Database | 2004 | SIGMOD | 5.838575e-05 |
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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