Materialisation and data partitioning algorithms for distributed RDF systems

Many RDF systems support reasoning with Datalog rules via materialisation, where all conclusions of data and the are precomputed explicitly stored in a preprocessing step. As amount used applications keeps increasing, processing large datasets often requires distributing cluster shared-nothing servers. While numerous distributed query answering techniques known, materialisation is less well understood. In this paper, we present several that facilitate scalable systems. First, new algorithm aims to minimise communication synchronisation cluster. Second, two algorithms for partitioning data, both which aim produce tightly connected partitions, but without loading complete into memory. We evaluate our against state-of-the-art show technique offers competitive performance, particularly when complex. Moreover, analyse depth effects on performance offer comparable or superior state art min-cut partitioning, computing partitions considerably time