LeetCode208 --- Implement Trie (Prefix Tree)

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#leetcode #trie #字典树 #前缀树

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本文详细介绍了如何使用字典树数据结构实现插入、搜索和前缀匹配的方法，适用于处理大量字符串数据的高效查找场景。

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Implement a trie with insert, search, and startsWith methods.
Note:
You may assume that all inputs are consist of lowercase letters a-z.

题意：构造一个字典树，并实现insert方法，search方法，startWith方法
注意：

insert方法：插入的过程中注意标注节点是字符串结尾节点还是前缀节点
search方法：遍历树，需要判断是否是字符串结尾节点
startWith方法：与search方法类似，但是不需要判断节点是字符串结尾节点还是前缀节点

class TrieNode {
    // Initialize your data structure here.
    public char key;
    public TrieNode[] nodes;
    //flag == 1 表示是字符串
    //flag == 0 表示是前缀
    public int flag;
    public TrieNode() {
        key='\0';
        nodes = new TrieNode[26];
    }
    public TrieNode(char c){
        key = c;
        nodes = new TrieNode[26];
        flag = 0;
    }
}

public class Trie {
    private TrieNode root;

    public Trie() {
        root = new TrieNode();
    }

    // Inserts a word into the trie.
    public void insert(String word) {
        TrieNode p = root;
        for(int i = 0; i < word.length();i++){
            char c = word.charAt(i);
            if(p.nodes[c-'a'] == null){
                TrieNode tmp = new TrieNode(c);
                p.nodes[c - 'a'] = tmp;
                p = tmp;
            }else{
                p = p.nodes[c-'a'];
            }
        }
        //更新节点标志
        p.flag = 1;
    }

    // Returns if the word is in the trie.
    public boolean search(String word) {
        TrieNode p = root;
        for(int i = 0; i < word.length();i++){
            char c = word.charAt(i);
            if(p.nodes[c-'a'] == null){
                return false;
            }else{
                p = p.nodes[c-'a'];
            }
        }
        if(p.flag == 1){
            return true;
        }else{
            return false;
        }

    }

    // Returns if there is any word in the trie
    // that starts with the given prefix.
    public boolean startsWith(String prefix) {
        TrieNode p = root;
        for(int i = 0; i < prefix.length();i++){
            char c = prefix.charAt(i);
            if(p.nodes[c-'a'] == null){
                return false;
            }else{
                p = p.nodes[c-'a'];
            }
        }
        return true;
    }
}

// Your Trie object will be instantiated and called as such:
// Trie trie = new Trie();
// trie.insert("somestring");
// trie.search("key");