Column-Oriented Datalog Materialization for Large Knowledge Graphs

From korrekt.org

Jump to: navigation, search


Jacopo Urbani, Ceriel J. H. Jacobs, Markus Krötzsch

Column-Oriented Datalog Materialization for Large Knowledge Graphs



Abstract. The evaluation of Datalog rules over large Knowledge Graphs (KGs) is essential for many applications. In this paper, we present a new method of materializing Datalog inferences, which combines a column-based memory layout with novel optimization methods that avoid redundant inferences at runtime. The pro-active caching of certain subqueries further increases efficiency. Our empirical evaluation shows that this approach can often match or even surpass the performance of state-of-the-art systems, especially under restricted resources.

Published at AAAI2016 (Conference paper)

Download PDF (last update: July 2 2016)

Citation details


Topics

Rule languages

Personal tools