[LeetCode] 208. Implement Trie (Prefix Tree)

A trie (pronounced as "try") or prefix tree is a tree data structure used to efficiently store and retrieve keys in a dataset of strings. There are various applications of this data structure, such as autocomplete and spellchecker.

Implement the Trie class:

• Trie() Initializes the trie object.
• void insert(String word) Inserts the string word into the trie.
• boolean search(String word) Returns true if the string word is in the trie (i.e., was inserted before), and false otherwise.
• boolean startsWith(String prefix) Returns true if there is a previously inserted string word that has the prefix prefix, and false otherwise.

Example 1:

Input
["Trie", "insert", "search", "search", "startsWith", "insert", "search"]
[[], ["apple"], ["apple"], ["app"], ["app"], ["app"], ["app"]]
Output
[null, null, true, false, true, null, true]

Explanation
Trie trie = new Trie();
trie.insert("apple");
trie.search("apple");   // return True
trie.search("app");     // return False
trie.startsWith("app"); // return True
trie.insert("app");
trie.search("app");     // return True

Constraints:

• 1 <= word.length, prefix.length <= 2000
• word and prefix consist only of lowercase English letters.
• At most 3 * 104 calls in total will be made to insert, search, and startsWith.

实现 Trie (前缀树)。

Trie（发音类似 "try"）或者说 前缀树 是一种树形数据结构，用于高效地存储和检索字符串数据集中的键。这一数据结构有相当多的应用情景，例如自动补完和拼写检查。

请你实现 Trie 类：

Trie() 初始化前缀树对象。
void insert(String word) 向前缀树中插入字符串 word 。
boolean search(String word) 如果字符串 word 在前缀树中，返回 true（即，在检索之前已经插入）；否则，返回 false 。
boolean startsWith(String prefix) 如果之前已经插入的字符串 word 的前缀之一为 prefix ，返回 true ；否则，返回 false 。

来源：力扣（LeetCode）
链接：https://leetcode.cn/problems/implement-trie-prefix-tree
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题意基本跟211题一致，需要实现几个字典树的函数。思路是需要自己实现一个 TrieNode 的类然后遍历单词的每个字母。这就是模板题，需要背下来。

时间O(n), n是需要遍历的单词的长度

空间O(num of TrieNode * 26) = O(num of words * word.length() * 26)

Java实现

class Trie {
    class Node {
        Node[] children;
        boolean isEnd;
        String word;

        public Node() {
            children = new Node[26];
            isEnd = false;
            word = "";
        }
    }

    Node root;

    /** Initialize your data structure here. */
    public Trie() {
        root = new Node();
    }

    /** Inserts a word into the trie. */
    public void insert(String word) {
        Node node = root;
        for (int i = 0; i < word.length(); i++) {
            int j = word.charAt(i) - 'a';
            if (node.children[j] == null) {
                node.children[j] = new Node();
            }
            node = node.children[j];
        }
        node.isEnd = true;
    }

    /** Returns if the word is in the trie. */
    public boolean search(String word) {
        Node node = root;
        for (int i = 0; i < word.length(); i++) {
            int j = word.charAt(i) - 'a';
            if (node.children[j] == null) {
                return false;
            }
            node = node.children[j];
        }
        return node.isEnd;
    }

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

/**
 * Your Trie object will be instantiated and called as such:
 * Trie obj = new Trie();
 * obj.insert(word);
 * boolean param_2 = obj.search(word);
 * boolean param_3 = obj.startsWith(prefix);
 */

 

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