graph

A library that can be used as a building block for high-performant graph algorithms.

Graph provides implementations for directed and undirected graphs. Graphs can be created programatically or read from custom input formats in a type-safe way. The library uses rayon to parallelize all steps during graph creation.

The implementation uses a Compressed-Sparse-Row (CSR) data structure which is tailored for fast and concurrent access to the graph topology.

Note: The development is mainly driven by Neo4j developers. However, the library is not an official product of Neo4j.

What is a graph?

A graph consists of nodes and edges where edges connect exactly two nodes. A graph can be either directed, i.e., an edge has a source and a target node or undirected where there is no such distinction.

In a directed graph, each node u has outgoing and incoming neighbors. An outgoing neighbor of node u is any node v for which an edge (u, v) exists. An incoming neighbor of node u is any node v for which an edge (v, u) exists.

In an undirected graph there is no distinction between source and target node. A neighbor of node u is any node v for which either an edge (u, v) or (v, u) exists.

How to use graph?

The library provides a builder that can be used to construct a graph from a given list of edges.

For example, to create a directed graph that uses usize as node identifier, one can use the builder like so:

use graph::prelude::*;

let graph: DirectedCsrGraph<usize> = GraphBuilder::new()
    .edges(vec![(0, 1), (0, 2), (1, 2), (1, 3), (2, 3)])
    .build();

assert_eq!(graph.node_count(), 4);
assert_eq!(graph.edge_count(), 5);

assert_eq!(graph.out_degree(1), 2);
assert_eq!(graph.in_degree(1), 1);

assert_eq!(graph.out_neighbors(1), &[2, 3]);
assert_eq!(graph.in_neighbors(1), &[0]);

To build an undirected graph using u32 as node identifer, we only need to change the expected types:

use graph::prelude::*;

let graph: UndirectedCsrGraph<u32> = GraphBuilder::new()
    .edges(vec![(0, 1), (0, 2), (1, 2), (1, 3), (2, 3)])
    .build();

assert_eq!(graph.node_count(), 4);
assert_eq!(graph.edge_count(), 5);

assert_eq!(graph.degree(1), 3);

assert_eq!(graph.neighbors(1), &[0, 2, 3]);

It is also possible to create a graph from a specific input format. In the following example we use the EdgeListInput which is an input format where each line of a file contains an edge of the graph.

use std::path::PathBuf;

use graph::prelude::*;

let path = [env!("CARGO_MANIFEST_DIR"), "resources", "example.el"]
    .iter()
    .collect::<PathBuf>();

let graph: DirectedCsrGraph<usize> = GraphBuilder::new()
    .csr_layout(CsrLayout::Sorted)
    .file_format(EdgeListInput::default())
    .path(path)
    .build()
    .expect("loading failed");

assert_eq!(graph.node_count(), 4);
assert_eq!(graph.edge_count(), 5);

assert_eq!(graph.out_degree(1), 2);
assert_eq!(graph.in_degree(1), 1);

assert_eq!(graph.out_neighbors(1), &[2, 3]);
assert_eq!(graph.in_neighbors(1), &[0]);

Examples?

Check the TriangleCount and PageRank implementations to see how the library is used to implement high-performant graph algorithms.

License: MIT