Fast datalog evaluation for batch and stream graph processing
Muhammad Imran, Gábor Gévay, Jorge-Arnulfo Quiané-Ruiz, Volker Markl · World Wide Web · 2022
Abstract Implementing complex algorithms for big data, artificial intelligence, and graph processing requires enormous effort. Succinct, declarative programs to solve complex problems that can be efficiently executed for batching and streaming data are in demand. This paper presents Nexus, a distributed Datalog evaluation system. It evaluates Datalog programs using thesemi-naivealgorithm for batch and streaming data using incremental and asynchronous iteration. Furthermore, we evaluate Datalog programs with aggregates to determine the advantages of implementing thesemi-naivealgorithm using incremental iteration on its performance. Our experimental results show that Nexus significantly outperforms acyclic dataflow-based systems.