[LeetCode]Implement Trie(Prefix Tree)，解题报告

目录

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概述

Trie树，又称为字典树、单词查找树或者前缀树，是一种用于快速检索的多叉数结构。例如，英文字母的字典树是26叉数，数字的字典树是10叉树。
Trie树的基本性质有三点，归纳为：

1. 根节点不包含字符，根节点外每一个节点都只包含一个字符。
2. 从根节点到某一节点，路径上经过的字符连接起来，为该节点对应的字符串。
3. 每个节点的所有子节点包含的字符串不相同。

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Trie树基本实现

我们通过LeetCode的上的一道Trie题目来描述Trie树的实现。Implement Trie(Prefix Tree)。

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定义Trie树节点

class TrieNode {    boolean isWord;    HashMap<Character, TrieNode> nexts;    public TrieNode() {        nexts = new HashMap<Character, TrieNode>();    }}

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添加操作

我们向Trie树中添加一个字符串word，具体步骤如下：

    // Inserts a word into the trie.    public void insert(String word) {        char[] s = word.toCharArray();        TrieNode p = root;        int i = 0, n = s.length;        // traverse existing        while (i < n) {            TrieNode next = p.nexts.get(s[i]);            if (next != null) {                p = next;                i ++;            } else {                break;            }        }        // append new nodes        while (i < n) {            TrieNode newTrie = new TrieNode();            p.nexts.put(s[i], newTrie);            p = newTrie;            i ++;        }        // set word end        p.isWord = true;    }

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查询word是否在Trie树中

    // Returns if the word is in the trie.    public boolean search(String word) {        TrieNode p = root;        for (int i = 0; i < word.length(); i ++) {            TrieNode child = p.nexts.get(word.charAt(i));            if (child == null) {                return false;            }            p = child;        }        return p.isWord;    }    // 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 ++) {            TrieNode child = p.nexts.get(prefix.charAt(i));            if (child == null) {                return false;            }            p = child;        }        return true;    }

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AC完整代码

import java.util.HashMap;class TrieNode {    boolean isWord;    HashMap<Character, TrieNode> nexts;    public TrieNode() {        nexts = new HashMap<Character, TrieNode>();    }}public class Trie {    private TrieNode root;    public Trie() {        root = new TrieNode();    }    // Inserts a word into the trie.    public void insert(String word) {        char[] s = word.toCharArray();        TrieNode p = root;        int i = 0, n = s.length;        // traverse existing        while (i < n) {            TrieNode next = p.nexts.get(s[i]);            if (next != null) {                p = next;                i ++;            } else {                break;            }        }        // append new nodes        while (i < n) {            TrieNode newTrie = new TrieNode();            p.nexts.put(s[i], newTrie);            p = newTrie;            i ++;        }        // set word end        p.isWord = true;    }    // Returns if the word is in the trie.    public boolean search(String word) {        TrieNode p = root;        for (int i = 0; i < word.length(); i ++) {            TrieNode child = p.nexts.get(word.charAt(i));            if (child == null) {                return false;            }            p = child;        }        return p.isWord;    }    // 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 ++) {            TrieNode child = p.nexts.get(prefix.charAt(i));            if (child == null) {                return false;            }            p = child;        }        return true;    }    public static void main(String[] args) {        Trie trie = new Trie();        trie.insert("keydsdsds");        System.out.println(trie.startsWith("key"));    }}