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arXiv · 1511.08915

Column-Oriented Datalog Materialization for Large Knowledge Graphs (Extended Technical Report)

Jacopo Urbani·Ceriel Jacobs·Markus Krötzsch
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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.

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Jacopo Urbani, Ceriel Jacobs, Markus Krötzsch. 2016-02-11. Column-Oriented Datalog Materialization for Large Knowledge Graphs (Extended Technical Report). https://arxiv.org/abs/1511.08915

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