Running GDS Algorithms
Learn to execute various graph algorithms from the GDS library, including loading graphs into memory and configuring algorithms.
GDS Algorithm Workflow
The Graph Data Science (GDS) library in Neo4j helps us run powerful graph algorithms. To use GDS, you generally follow a three-step process:
- Project: Load a subset of your graph into GDS's optimized in-memory store.
- Execute: Run an algorithm on this in-memory graph.
- Write Back: Optionally, write the results back to your Neo4j database.
Projecting Your Graph
Before running an algorithm, GDS needs to know which part of your database graph to analyze. This process is called graph projection.
You define which nodes and relationships, based on their labels and types, should be copied into GDS's fast in-memory representation. This makes algorithm execution much quicker.
All lessons in this course
- Introduction to GDS Library
- Running GDS Algorithms
- GDS Pipelines and Machine Learning
- Graph Embeddings with GDS