A Survey of Relational Approaches for Graph Pattern Matching over Large Graphs

Due to rapid growth of the Internet and new scientific/technological advances, there exist many new applications that model data as graphs, because graphs have sufficient expressiveness to model complicated structures. The dominance of graphs in real-world applications demands new graph processing techniques to access and analyze large graph datasets effectively and efficiently. Among those techniques, a graph pattern matching problem receives increasing attention, which is to find all patterns in a large data graph that match a user-given graph pattern. In this survey, we review approaches to process such graph pattern queries with a framework of multi joins, which can be easily implemented in relational databases and requires no specialized native storage for graphs. We also discuss the top-k graph pattern matching problem.