Instance Optimal Join Size Estimation

TL;DR

This paper introduces an instance optimal algorithm for estimating the size of relational join results efficiently, regardless of join size, and also provides a method for uniform sampling of join rows.

Contribution

It presents the first instance optimal join size estimation algorithm that works for all instances, removing the previous dependency on join size.

Findings

Algorithm achieves instance optimality for all join sizes.

Provides a method for uniform random sampling of join rows.

Reduces estimation time independent of join size.

Abstract

We consider the problem of efficiently estimating the size of the inner join of a collection of preprocessed relational tables from the perspective of instance optimality analysis. The run time of instance optimal algorithms is comparable to the minimum time needed to verify the correctness of a solution. Previously instance optimal algorithms were only known when the size of the join was small (as one component of their run time that was linear in the join size). We give an instance optimal algorithm for estimating the join size for all instances, including when the join size is large, by removing the dependency on the join size. As a byproduct, we show how to sample rows from the join uniformly at random in a comparable amount of time.