Query size estimation by adaptive sampling (extended abstract)

Abstract

We present an adaptive, random sampling algorithm for estimating the size of general queries. The algorithm can be used for any query Q over a database D such that 1) for some n, the answer to Q can be partitioned into n disjoint subsets Q1, Q2, …, Qn, and 2) for 1 ≤ i ≤ n, the size of Qi is bounded by some function b(D, Q), and 3) there is some algorithm by which we can compute the size of Qi, 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.