Aggregation and Ordering in Factorised Databases

TL;DR

This paper extends the FDB system for factorised databases to support aggregate functions and ordering, introducing new optimization techniques that significantly improve query evaluation efficiency.

Contribution

It introduces novel optimization and evaluation methods for factorised databases to handle aggregates and ordering, enhancing their practical applicability.

Findings

FDB outperforms traditional relational engines by orders of magnitude.

Factorisation with partial aggregation reduces query operation counts.

Ordered enumeration of query results is achieved efficiently through factorisation.

Abstract

A common approach to data analysis involves understanding and manipulating succinct representations of data. In earlier work, we put forward a succinct representation system for relational data called factorised databases and reported on the main-memory query engine FDB for select-project-join queries on such databases. In this paper, we extend FDB to support a larger class of practical queries with aggregates and ordering. This requires novel optimisation and evaluation techniques. We show how factorisation coupled with partial aggregation can effectively reduce the number of operations needed for query evaluation. We also show how factorisations of query results can support enumeration of tuples in desired orders as efficiently as listing them from the unfactorised, sorted results. We experimentally observe that FDB can outperform off-the-shelf relational engines by orders of magnitude.