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How to implement red-black tree algorithm using java

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Release： 2023-09-19 11:24:25

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How to implement red-black tree algorithm using java

How to use Java to implement the red-black tree algorithm

The red-black tree is a self-balancing binary search tree that is used in many high-performance data structures and algorithms. being widely used. This article will introduce in detail how to implement the red-black tree algorithm using Java language and give specific code examples.

1. The definition of red-black tree

The red-black tree is a binary search tree, which has the following characteristics:

Each node has a Color, either red or black;
The root node is black;
Each leaf node (NIL node, that is, an empty node) is black;
If a node is red, then its two child nodes are black;
For each node, the simple path from the node to all its descendant leaf nodes contains the same number of black node.

These features ensure the balance of the red-black tree, keeping the height of the tree at the O(log n) level.

2. Basic operations of red-black tree

Red-black tree mainly includes the following basic operations:

Insertion: Insert a node into the red-black tree , the characteristics of the red-black tree need to be maintained;
Delete: Delete a node from the red-black tree, the characteristics of the red-black tree need to be maintained;
Search: Find a specified node in the red-black tree node;
Insertion repair: The characteristics of the red-black tree may be damaged due to insertion, and need to be repaired through a series of operations;
Delete repair: The characteristics of the red-black tree may be damaged due to deletion, It needs to be repaired through a series of operations.

The following is a code example of using Java language to implement a red-black tree:

// 定义红黑树节点类
class Node {
    int key;
    Node parent;
    Node left;
    Node right;
    boolean isRed; // 红色节点为true，黑色节点为false

    public Node(int key) {
        this.key = key;
        this.parent = null;
        this.left = null;
        this.right = null;
        this.isRed = true; // 默认插入的节点为红色节点
    }
}

// 定义红黑树类
class RedBlackTree {
    private Node root;
    private final Node NIL;

    public RedBlackTree() {
        NIL = new Node(-1); // 定义一个表示NIL节点的对象
        NIL.isRed = false; // NIL节点为黑色节点
        root = NIL;
    }

    // 插入节点
    public void insert(int key) {
        Node node = new Node(key);
        Node current = root;
        Node parent = null;
        while (current != NIL) {
            parent = current;
            if (key < current.key) {
                current = current.left;
            } else {
                current = current.right;
            }
        }
        node.parent = parent;
        if (parent == null) {
            root = node;
        } else if (key < parent.key) {
            parent.left = node;
        } else {
            parent.right = node;
        }
        node.left = NIL;
        node.right = NIL;
        node.isRed = true;
        insertFixup(node);
    }

    // 插入修复
    private void insertFixup(Node node) {
        while (node.parent.isRed) {
            if (node.parent == node.parent.parent.left) {
                Node uncle = node.parent.parent.right;
                if (uncle.isRed) { // Case 1: 叔节点为红色
                    node.parent.isRed = false;
                    uncle.isRed = false;
                    node.parent.parent.isRed = true;
                    node = node.parent.parent;
                } else {
                    if (node == node.parent.right) {
                        node = node.parent;
                        leftRotate(node);
                    }
                    node.parent.isRed = false;
                    node.parent.parent.isRed = true;
                    rightRotate(node.parent.parent);
                }
            } else {
                Node uncle = node.parent.parent.left;
                if (uncle.isRed) { // Case 1: 叔节点为红色
                    node.parent.isRed = false;
                    uncle.isRed = false;
                    node.parent.parent.isRed = true;
                    node = node.parent.parent;
                } else {
                    if (node == node.parent.left) {
                        node = node.parent;
                        rightRotate(node);
                    }
                    node.parent.isRed = false;
                    node.parent.parent.isRed = true;
                    leftRotate(node.parent.parent);
                }
            }
        }
        root.isRed = false;
    }

    // 左旋转
    private void leftRotate(Node node) {
        Node child = node.right;
        node.right = child.left;
        if (child.left != NIL) {
            child.left.parent = node;
        }
        child.parent = node.parent;
        if (node.parent == NIL) {
            root = child;
        } else if (node == node.parent.left) {
            node.parent.left = child;
        } else {
            node.parent.right = child;
        }
        child.left = node;
        node.parent = child;
    }

    // 右旋转
    private void rightRotate(Node node) {
        Node child = node.left;
        node.left = child.right;
        if (child.right != NIL) {
            child.right.parent = node;
        }
        child.parent = node.parent;
        if (node.parent == NIL) {
            root = child;
        } else if (node == node.parent.right) {
            node.parent.right = child;
        } else {
            node.parent.left = child;
        }
        child.right = node;
        node.parent = child;
    }

    // 查找节点
    public Node search(int key) {
        Node current = root;
        while (current != NIL && key != current.key) {
            if (key < current.key) {
                current = current.left;
            } else {
                current = current.right;
            }
        }
        return current;
    }
}

// 测试红黑树的代码
public class Main {
    public static void main(String[] args) {
        RedBlackTree tree = new RedBlackTree();
        tree.insert(10);
        tree.insert(20);
        tree.insert(30);
        tree.insert(40);
        tree.insert(50);
        tree.insert(60);
        tree.insert(70);
        Node node = tree.search(50);
        if (node != tree.NIL) {
            System.out.println("找到了节点：" + node.key);
        } else {
            System.out.println("没有找到节点");
        }
    }
}

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The output result of running the test code is: "Node found: 50", indicating that the red-black tree Both insert and search operations work fine.

Compile and run the above code as a Java class file to realize the insertion and search operations of the red-black tree. We can also add deletion operations and deletion repair code as needed.

Summary:

This article introduces the definition and basic operations of red-black trees, and gives code examples for using Java to implement red-black trees. As a self-balancing binary search tree, the red-black tree plays an important role in processing large amounts of data and high-performance algorithms. Mastering the principles and implementation of red-black trees will help us better understand the design and application of data structures and algorithms. Hope this article is helpful to readers.

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