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Error-Constrained COUNT Query Evaluation in Relational Databases

Summary: Introduces double sampling for error-constrained COUNT(E) in relational algebra, guaranteeing an estimator within a user-specified error e at a given confidence. Compares double sampling to adaptive sampling, showing sample-size tradeoffs, with prototype CASE-MDB and real-time experiments. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
2536
Venue
SIGMOD
Year
1991
Pagerank
0.0002802103
Overall Rank
315 | 97.82%
DOI
-

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