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On the Relative Cost of Sampling for Join Selectivity Estimation

Summary: Quantifies when sampling (t_cross) is cheaper than computing the exact star-join for selectivity estimation, deriving bounds and approximations for relative cost as functions of input relation sizes, arity, and the estimator's precision criterion. Identifies dangling tuples as a major negative factor and characterizes mixed effects of data skew, yielding concrete regimes and thresholds that indicate when sampling is or isn't cost-effective for join selectivity estimation. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1012
Venue
PODS
Year
1994
Pagerank
0.00016425612
Overall Rank
811 | 94.36%
DOI
-

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