Trie树又被称为字典树、前缀树,是一种用于快速检索的多叉树。Tried树可以利用字符串的公共前缀来节省存储空间。
但如果系统存在大量没有公共前缀的字符串,相应的Trie树将非常消耗内存。(下图为Wiki上的Trie树示意图, https://en.wikipedia.org/wiki/Trie)
- 子节点用hashMap表示
- isWord标记从根节点到该节点是否表示一个单词,还是另一单词的前缀。
Implement a trie with insert
, search
, and startsWith
methods.
class TrieNode { // Initialize your data structure here. boolean isWord; public 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) { int start=0; int end=word.length(); TrieNode p=root; while(start<end){ TrieNode node= p.nexts.get(word.charAt(start)); if(node!=null){ p=node; start++; }else break; } while(start<end){ TrieNode trie=new TrieNode(); p.nexts.put(word.charAt(start),trie); p=trie; start++; } 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; } } // Your Trie object will be instantiated and called as such: // Trie trie = new Trie(); // trie.insert("somestring"); // trie.search("key");
时间: 2024-10-25 18:55:01