LeetCode Implement Trie (Prefix Tree)

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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.

思路分析：这题主要考察Trie 即前缀树的实现，Trie可以用于字典的压缩存储，可以节省空间，但是不节省时间（和HashSet相比）。这题实质是实现一颗多叉树（分支因子26）的插入和查找操作。定义每个TrieNode保存char c，保存一个HashMap用于储存所有的孩子节点，key是对应的字符，value是孩子节点，定义flag hasWord来标记这个node上是否存在word。对于插入操作，直接从上向下分层扫描树，如果没有对应字符节点存在就新建节点，如果有就去相应路径向下探察。对于查询操作，前缀树的定义可以保证当我们从前向后扫描字符串时候，每一个字符都可以从上到下对应前缀树的每一层，所以扫描过程中如果有任何一个字符不存在于当前层中，就可以立刻停止查找返回null，也就是不存在这样的word或者前缀，否则继续从对应的分支向下探察。时间复杂度是O（L），L是树的高度，也就是最长word的长度，空间复杂度26^L，每一层分支因子26，有L层。

AC Code

class TrieNode {
    // Initialize your data structure here.
    //0908
    char c;
    HashMap<Character, TrieNode> children = new HashMap<Character, TrieNode>();
    boolean hasWord;
    
    public TrieNode(){
        
    }
    
    public TrieNode(char c){
        this.c = c;
    }
}

public class Trie {
    private TrieNode root;

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

    // Inserts a word into the trie.
    public void insert(String word) {
        TrieNode cur = root;
        HashMap<Character, TrieNode> curChildren = root.children;
        char[] wordArray = word.toCharArray();
        for(int i = 0; i < wordArray.length; i++){
            char wc = wordArray[i];
            if(curChildren.containsKey(wc)){
                cur = curChildren.get(wc);
            } else {
                TrieNode newNode = new TrieNode(wc);
                curChildren.put(wc, newNode);
                cur = newNode;
            }
            curChildren = cur.children;
            if(i == wordArray.length - 1){
                cur.hasWord= true;
            }
        }
    }

    // Returns if the word is in the trie.
    public boolean search(String word) {
        if(searchWordNodePos(word) == null){
            return false;
        } else if(searchWordNodePos(word).hasWord) 
          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) {
        if(searchWordNodePos(prefix) == null){
            return false;
        } else return true;
    }
    
    public TrieNode searchWordNodePos(String s){
        HashMap<Character, TrieNode> children = root.children;
        TrieNode cur = null;
        char[] sArray = s.toCharArray();
        for(int i = 0; i < sArray.length; i++){
            char c = sArray[i];
            if(children.containsKey(c)){
                cur = children.get(c);
                children = cur.children;
            } else{
                return null;
            }
        }
        return cur;
    }
}

// Your Trie object will be instantiated and called as such:
// Trie trie = new Trie();
// trie.insert("somestring");
// trie.search("key");
//0918

LeetCode Implement Trie (Prefix Tree)

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原文地址：http://blog.csdn.net/yangliuy/article/details/46287671