实现一个 Trie (前缀树),包含 insert, search, 和 startsWith 这三个操作。
示例:
Trie trie = new Trie();
trie.insert("apple");
trie.search("apple"); // 返回 true
trie.search("app"); // 返回 false
trie.startsWith("app"); // 返回 true
trie.insert("app");
trie.search("app"); // 返回 true
说明:你可以假设所有的输入都是由小写字母 a-z 构成的。
保证所有输入均为非空字符串。
来源:力扣(LeetCode)
链接:https://leetcode-cn.com/problems/implement-trie-prefix-tree
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构建字典树
class Trie {
private TrieNode root;
/**
* Initialize your data structure here.
*/
public Trie() {
root = new TrieNode();
}
/**
* Inserts a word into the trie.
*/
public void insert(String word) {
TrieNode node = root;
int charIndex;
for (int i = 0; i < word.length(); i++) {
charIndex = word.charAt(i) - 'a';
if (node.childrens[charIndex] == null) {
node.childrens[charIndex] = new TrieNode();
}
node = node.childrens[charIndex];
}
node.endOfWord = true;
}
/**
* Returns if the word is in the trie.
*/
public boolean search(String word) {
TrieNode node = root;
for (int i = 0; i < word.length(); i++) {
node = node.childrens[word.charAt(i) - 'a'];
if (node == null) {
return false;
}
}
return node.endOfWord;
}
/**
* Returns if there is any word in the trie that starts with the given prefix.
*/
public boolean startsWith(String prefix) {
TrieNode node = root;
for (int i = 0; i < prefix.length(); i++) {
node = node.childrens[prefix.charAt(i) - 'a'];
if (node == null) {
return false;
}
}
return true;
}
private class TrieNode {
// index代表路径值
public TrieNode[] childrens = new TrieNode[26];
// 到当前节点,之前的路径能否组成一个完整的代词
public boolean endOfWord;
}
}
/**
* 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);
*/
运行效率