4.8 Executing Built-in Algorithms
The in-memory graph server (PGX) contains a set of built-in algorithms that are available as Java APIs.
The following table provides an overview of the available algorithms, grouped by category.
Note:
These algorithms can be invoked through theAnalyst
interface. See the Analyst Class in Javadoc for more details.
Table 4-5 Overview of Built-In Algorithms
Category | Algorithms |
---|---|
Classic graph algorithms | Prim's Algorithm |
Community detection | Conductance Minimization (Soman and Narang Algorithm), Infomap, Label Propagation, Louvain |
Connected components | Strongly Connected Components, Weakly Connected Components (WCC) |
Link predition | WTF (Whom To Follow) Algorithm |
Matrix factorization | Matrix Factorization |
Other | Graph Traversal Algorithms |
Path finding | All Vertices and Edges on Filtered Path, Bellman-Ford Algorithms, Bidirectional Dijkstra Algorithms, Compute Distance Index, Compute High-Degree Vertices, Dijkstra Algorithms, Enumerate Simple Paths, Fast Path Finding, Fattest Path, Filtered Fast Path Finding, Hop Distance Algorithms |
Ranking and walking | Closeness Centrality Algorithms, Degree Centrality Algorithms, Eigenvector Centrality, Hyperlink-Induced Topic Search (HITS), PageRank Algorithms, Random Walk with Restart, Stochastic Approach for Link-Structure Analysis (SALSA) Algorithms, Vertex Betweenness Centrality Algorithms |
Structure evaluation | Adamic-Adar index, Bipartite Check, Conductance, Cycle Detection Algorithms, Degree Distribution Algorithms, Eccentricity Algorithms, K-Core, Local Clustering Coefficient (LCC), Modularity, Partition Conductance, Reachability Algorithms, Topological Ordering Algorithms, Triangle Counting Algorithms |
This following topics describe the use of the in-memory graph server (PGX) using Triangle Counting and PageRank analytics as examples.