Q-error Bounds of Random Uniform Sampling for Cardinality Estimation

TL;DR

This paper analyzes the Q-error bounds of random uniform sampling for cardinality estimation, providing guidelines on sample size based on confidence intervals and true cardinality.

Contribution

It offers the first analysis of Q-error bounds for uniform sampling in cardinality estimation, establishing practical sample size rules.

Findings

Upper Q-error bound depends on sample size and true cardinality.

Provides confidence interval analysis for sampling with and without replacement.

Offers practical guidelines for sample size selection in cardinality estimation.

Abstract

Random uniform sampling has been studied in various statistical tasks but few of them have covered the Q-error metric for cardinality estimation (CE). In this paper, we analyze the confidence intervals of random uniform sampling with and without replacement for single-table CE. Results indicate that the upper Q-error bound depends on the sample size and true cardinality. Our bound gives a rule-of-thumb for how large a sample should be kept for single-table CE.