Aggregate Queries on Sparse Databases

TL;DR

This paper introduces an algebraic framework for efficient query evaluation and aggregation on sparse databases, providing a powerful query language and optimal algorithms for enumeration with constant delay.

Contribution

It presents a unified algebraic approach for query processing on sparse databases and introduces a new query language extending first-order logic with aggregation.

Findings

Linear-time algorithm for answer enumeration on bounded expansion databases

Constant delay enumeration of query answers

Framework unifies various query evaluation problems

Abstract

We propose an algebraic framework for studying efficient algorithms for query evaluation, aggregation, enumeration, and maintenance under updates, on sparse databases. Our framework allows to treat those problems in a unified way, by considering various semirings, depending on the considered problem. As a concrete application, we propose a powerful query language extending first-order logic by aggregation in multiple semirings. We obtain an optimal algorithm for computing the answers of such queries on sparse databases. More precisely, given a database from a fixed class with bounded expansion, the algorithm computes in linear time a data structure which allows to enumerate the set of answers to the query, with constant delay between two outputs.