This chapter explains the common usage patterns and operations that constitute the core of the Neo4j Graph Data Science library.
The GDS library usage pattern is typically split in two phases: development and production. In the development phase the goal is to establish a workflow of useful algorithms. In order to do this, the system must be configured, graph projections must be defined, and algorithms must be selected. It is typical to make use of the memory estimation features of the library. This enables you to successfully configure your system to handle the amount of data to be processed. There are two kinds of resources to keep in mind: the in-memory graph and the algorithm data structures.
In the production phase, the system would be configured appropriately to successfully run the desired algorithms. The sequence of operations would normally be to create a graph, run one or more algorithms on it, and consume results.
The below image illustrates an overview of standard operation of the GDS library:
The more detail on each individual operation, see the corresponding section:
In this chapter, we will go through these aspects and guide you towards the most useful operations.
This chapter is divided into the following sections: