Distributed Rdf Query Answering With Dynamic Data Exchange

Evaluating joins over RDF data stored in a shared-nothing server cluster is key to processing truly large RDF datasets. To the best of our knowledge, the existing approaches use a variant of the data exchange operator that is inserted into the query plan statically (i.e., at query compile time) to shuffle data between servers. We argue that such approaches often miss opportunities for local computation, and we present a novel solution to distributed query answering that consists of two main components. First, we present a query answering algorithm based on dynamic data exchange, which exploits data locality to maximise the amount of computation on a single server. Second, we present a partitioning algorithm for RDF data based on graph partitioning whose aim is to increase data locality. We have implemented our approach in the RDFox system, and our performance evaluation suggests that our techniques outperform the state of the art by up to an order of magnitude in terms of query evaluation times, network communication, and memory use.