2013/07/01 by Nurzhan Bakibayev, Bakibayev, Nurzhan, Tomáš Kočiský +5 · 1 citation
Computer Science · #Advanced Database Systems and Queries #Data Management and Algorithms #Data Mining Algorithms and Applications #Data Structures and Algorithms (cs.DS) #Databases (cs.DB) #FOS: Computer and information sciences
paper · pdf · doi:10.48550/arxiv.1307.0441
openalex publication_date 2013/07/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.