Dynamic Sample Selection for Approximate Query Processing
Summary: Dynamic per-query biased sampling for approximate query processing using a pre-built library of non-uniform samples. Runtime selects the most informative sub-sample via an index, delivering tighter aggregations than static sampling with improved accuracy and responsiveness. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Brian Babcock (Stanford University)
- 2. Surajit Chaudhuri (Microsoft)
- 3. Gautam Das (Microsoft)
BibTeX Citation
@inproceedings{babcock_sigmod03,
title = {{Dynamic Sample Selection for Approximate Query Processing}},
author = {Babcock, Brian and Chaudhuri, Surajit and Das, Gautam},
series = {{SIGMOD} '03},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/872757.872822},
url = {https://dl.acm.org/doi/10.1145/872757.872822},
year = {2003}
}
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