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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
3526
Venue
SIGMOD
Year
2004
Pagerank
6.4473679e-05
Overall Rank
4,100 | 71.51%
DOI
-

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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
14 Online Aggregation 1997 SIGMOD 0.0010813443
18 On Random Sampling over Joins 1999 SIGMOD 0.00092569117
37 Statistical Estimators for Relational Algebra Expressions 1988 PODS 0.00075597514
46 Simple Random Sampling from Relational Databases 1986 VLDB 0.00071588702
212 Join Synopses for Approximate Query Answering 1999 SIGMOD 0.00033997204
553 Bifocal Sampling for Skew-Resistant Join Size Estimation 1996 SIGMOD 0.00020272747
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