Distributed SPARQL Query Answering over RDF Data Streams

The RDF framework is the underpinning element of Semantic Web stack, its widespread adoption requires efficient tools to store and query RDF data. A number of efficient local RDF stores already exist, while distributed indexing and distributed query processing are only starting to develop, furthermore dynamically growing and fail-safe solutions are not yet available. To remedy this situation, we propose an approach for efficient and scalable query processing over RDF graphs, distributed over a local data grid. Our system is based on a distributed architecture, where neither single point of failure nor specialised nodes exist. The query processing framework, presented in the paper, includes a sophisticated query planning and query execution algorithm, which is designed expressively for storage and query of a stream of incoming RDF triples, allowing the users to register queries that will be notified in real time of new relevant data. We finally evaluate our approach through performance measurement of a real deployment in the areas of business process monitoring.