MaRVIN: A platform for large-scale analysis of Semantic Web data

Abstract

Web Science requires efficient techniques for analysing large datasets.Many Semantic Web problems are difficult to solve through common divide-and-conquer strategies, since they are hard to partition.We present MARVIN, a parallel and distributed platform for processing large amounts of RDF data, on a network of loosely-coupled peers.We present our divide-conquer-swap strategy and show that this model converges towards completeness.We evaluate performance, scalability, load balancing and efficiency of our system.