An Algorithm for Context-Free Path Queries over Graph Databases

Abstract

Path queries are used to specify paths inside a data graph to match a given pattern. Query languages such as SPARQL usually include support for regular path patterns defined by means of regular expressions. Context-free path queries define a path whose language can be defined by a context-free grammar. This kind of query is interesting in practice in domains such as genetics, data science, or source code analysis. In this paper, we present a novel algorithm for context-free path query processing. Our algorithm works by looking for localized paths, allowing us to process subgraphs, in contrast to other approaches that have to process the whole graph. It also takes any context-free grammar as input, avoiding the use of normal forms that are more problematic in practice. The output of our algorithm provides enough information to reconstruct the paths matching the query. We prove the correctness of our approach and show its runtime and memory complexity. We show the viability of our approach by means of a prototype implemented in Go. We run experiments proposed in recent works, which include both synthetic and real RDF databases. Our algorithm shows some performance gains when compared with other algorithms implemented using single-thread programs.