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A Bi-Level Bernoulli Scheme for Database Sampling

Summary: Bi-level Bernoulli sampling unites row- and page-level sampling for ISO-style queries, enabling a tunable speed–precision trade-off with SQL extensions and data-aware parameter optimization. A bang-bang policy governed by a page-heterogeneity index (PHI) guides parameter choice; pilot sampling or catalog statistics set PHI, with a heuristic achieving near-optimal accuracy on clustered or skewed data across 1,100 experiments. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3587
Venue
SIGMOD
Year
2004
Pagerank
7.1114677e-05
Overall Rank
3,803 | 73.91%
DOI
10.1145/1007568.1007601

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{haas_sigmod04,
        title = {{A Bi-Level Bernoulli Scheme for Database Sampling}},
        author = {Haas, Peter J. and König, Christian},
        series = {{SIGMOD} '04},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1007568.1007601},
        url = {https://dl.acm.org/doi/10.1145/1007568.1007601},
        year = {2004}
}

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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 0.00077458002
54 On Random Sampling over Joins 1999 SIGMOD 0.00040810225
55 Statistical Estimators for Relational Algebra Expressions 1988 PODS 0.00040746149
136 Join Synopses for Approximate Query Answering 1999 SIGMOD 0.00030123303
173 Simple Random Sampling from Relational Databases 1986 VLDB 0.00027273858
730 Bifocal Sampling for Skew-Resistant Join Size Estimation 1996 SIGMOD 0.00014539362
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