Query size estimation by adaptive sampling

Abstract

We present an adaptive, random sampling algorithm for estimating the size of general queries. The algorithm can be used for any query 𝒟 over a database D such that (1) for some n, the answer to ℒ can be partitioned into n disjoint subsets ℒ 1, ℒ 2, …, ℒ n, and (2) for 1 ≤ i ≤ n, the size of qqi is bounded by some function b(D, ℒ), and (3) there is some algorithm by which we can compute the size of ℒ i, where i is chosen randomly. We consider the performance of the algorithm on three special cases of the algorithm: join queries, transitive closure queries, and general recursive Datalog queries. © 1995 by Academic Press, Inc.