This chapter aims to teach us how to represent various types of networks and complex systems as property graphs in Spark and GraphX. Before we can describe the behavior, and analyze the inner structure of these systems, we first need to map their components to vertices or nodes, and map the interactions between the individual components to edges or links. Building on what we learned in the previous chapter, we will delve into the details on how graphs are stored and represented in GraphX. In addition, this chapter introduces the language of graph theory, and the basic characteristics of graphs. Throughout this chapter, we will use real-world datasets that we will map to the different types of graphs. The examples include e-mail communication networks, food flavor network, and social ego networks. On completing this chapter, you will understand how to: