The Vadalog Parallel System: Distributed Reasoning with Datalog+/-

Over the past years, there has been a growing demand for ontological reasoning systems based on languages of the Datalog+/- family, such as Vadalog, for their ability to effectively model a wide range of real-world problems with powerful features such as existential quantification. As the scale and complexity of data analysis tasks continue to grow, the ability to distribute the computational workload across multiple non-communicating processors has become vital for these systems to achieve scalable performance. The joint presence of existential quantification and recursion poses new challenges, currently unsolved by existing distributed systems, which only concentrate on Datalog and are therefore unsuitable for ontological reasoning. When working across multiple processors, generating all the facts to answer a specific reasoning query, avoiding duplication, and guaranteeing termination are non-trivial tasks as infinitely many new symbols and facts can be generated by existential quantification and recursion. In this paper, we address such challenges and introduce the first distributed framework in the Datalog+/- space. We propose the condition of homomorphic decomposability, which identifies sets of Datalog+/- rules with good distribution properties. We put homomorphic decomposability into action with a distributed reasoning algorithm for Warded Datalog+/-, the core of Vadalog. We implement Vadalog Parallel, a distributed reasoner for Vadalog and provide experimental evaluation against state-of-the-art systems.