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Graphs are powerful data structures widely used to model real-world problems like social networks, maps, and web page linking. In Java, one of the most efficient ways to implement a graph is through an adjacency list. This article provides a complete guide to building a simple graph data structure in Java, including code for adding/removing vertices and edges, and printing the graph.

1. The Vertex Class (Optional)

We begin with a Vertex class to represent each node in the graph. It encapsulates a label and implements equals() and hashCode() so it works well with Java collections.

java

import java.util.Objects;

public class Vertex {
    private String label;

    public Vertex(String label) {
        this.label = label;
    }

    public String getLabel() {
        return label;
    }

    @Override
    public boolean equals(Object o) {
        if (this == o) return true;
        if (!(o instanceof Vertex)) return false;
        Vertex vertex = (Vertex) o;
        return Objects.equals(label, vertex.label);
    }

    @Override
    public int hashCode() {
        return Objects.hash(label);
    }

    @Override
    public String toString() {
        return label;
    }
}

2. Graph Class Using Adjacency List

The Graph class maintains a map of vertices and their neighbors, allowing efficient lookups and insertions.

java

import java.util.*;

public class Graph {
    private final Map<Vertex, List<Vertex>> adjVertices;

    public Graph() {
        this.adjVertices = new HashMap<>();
    }

    // Add a vertex
    public void addVertex(String label) {
        adjVertices.putIfAbsent(new Vertex(label), new ArrayList<>());
    }

    // Remove a vertex
    public void removeVertex(String label) {
        Vertex v = new Vertex(label);
        adjVertices.values().forEach(e -> e.remove(v));
        adjVertices.remove(v);
    }

    // Add an edge (undirected)
    public void addEdge(String label1, String label2) {
        Vertex v1 = new Vertex(label1);
        Vertex v2 = new Vertex(label2);
        adjVertices.get(v1).add(v2);
        adjVertices.get(v2).add(v1);
    }

    // Remove an edge
    public void removeEdge(String label1, String label2) {
        Vertex v1 = new Vertex(label1);
        Vertex v2 = new Vertex(label2);
        List<Vertex> eV1 = adjVertices.get(v1);
        List<Vertex> eV2 = adjVertices.get(v2);
        if (eV1 != null) eV1.remove(v2);
        if (eV2 != null) eV2.remove(v1);
    }

    // Get adjacent vertices
    public List<Vertex> getAdjVertices(String label) {
        return adjVertices.get(new Vertex(label));
    }

    // Print the graph
    public void printGraph() {
        for (Vertex v : adjVertices.keySet()) {
            System.out.print(v + " -> ");
            for (Vertex w : adjVertices.get(v)) {
                System.out.print(w + " ");
            }
            System.out.println();
        }
    }
}

3. Example Usage

java

public class Main {
    public static void main(String[] args) {
        Graph graph = new Graph();

        graph.addVertex("A");
        graph.addVertex("B");
        graph.addVertex("C");
        graph.addVertex("D");
        graph.addVertex("E");

        graph.addEdge("A", "B");
        graph.addEdge("A", "C");
        graph.addEdge("B", "D");
        graph.addEdge("C", "D");
        graph.addEdge("D", "E");

        graph.printGraph();
    }
}

Output:

mathematica

A -> B C 
B -> A D 
C -> A D 
D -> B C E 
E -> D 

4. Key Concepts Explained

FeatureDescriptionaddVertex()Adds a new vertex if it doesn’t already exist.addEdge()Adds an undirected edge between two vertices.removeEdge()Removes the edge between two vertices.removeVertex()Removes a vertex and all edges connected to it.adjVerticesA map representing the graph as an adjacency list.

5. Additional Tips

🔁 Directed Graph

To make it directed, simply remove the second line in addEdge() that adds the reverse connection:

java

// adjVertices.get(v2).add(v1); // Remove this line

🧮 Weighted Graph

To handle weights, replace List<Vertex> with something like Map<Vertex, Integer> or use a wrapper class.

6. Applications of Graphs

• Social Networks (users and friendships)
• Routing and Maps
• Web Crawling (pages and links)
• Dependency Resolution
• Knowledge Graphs

Final Thoughts

This implementation provides a flexible foundation for building both simple and complex graphs. Whether you're working on a backend system, pathfinding algorithm, or interview prep, mastering graphs in Java is a critical skill.