LeetCode Implement Trie (Prefix Tree)

原题链接在这里：https://leetcode.com/problems/implement-trie-prefix-tree/

Trie 是一种数据结构，用来做字典查找，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。

下面有两种方法，第一种相对简洁

AC Java:

 1 class TrieNode {
 2     String val = "";
 3     TrieNode [] nexts; 
 4     
 5     public TrieNode() {
 6         nexts = new TrieNode[26];
 7     }
 8 }
 9 
10 public class Trie {
11     private TrieNode root;
12     
13     public Trie() {
14         root = new TrieNode();
15     }
16 
17     // Inserts a word into the trie.
18     public void insert(String word) {
19         TrieNode p = root;
20         for(char c : word.toCharArray()){
21             if(p.nexts[c-'a'] == null){
22                 p.nexts[c-'a'] = new TrieNode();
23             }
24             p = p.nexts[c-'a'];
25         }
26         p.val = word;
27     }
28 
29     // Returns if the word is in the trie.
30     public boolean search(String word) {
31         TrieNode p = root;
32         for(char c : word.toCharArray()){
33             if(p.nexts[c-'a'] == null){
34                 return false;
35             }
36             p = p.nexts[c-'a'];
37         }
38         return p.val.equals(word);
39     }
40 
41     // Returns if there is any word in the trie
42     // that starts with the given prefix.
43     public boolean startsWith(String prefix) {
44         TrieNode p = root;
45         for(char c : prefix.toCharArray()){
46             if(p.nexts[c-'a'] == null){
47                 return false;
48             }
49             p = p.nexts[c-'a'];
50         }
51         return true;
52     }
53 }

第二种方法用的是存是否为叶子节点。与第一种方法的存val不同，但本质上都是一回事。

Note: search() 和 startsWith() 有所不同，search时还需要注意跳出loop时是否已经打了Trie树的叶子节点。

AC Java:

 1 class TrieNode {
 2     //Mark if this node is the end of the word
 3     boolean isLeaf;
 4     HashMap<Character,TrieNode> nexts;
 5     public TrieNode() {
 6         nexts = new HashMap<Character,TrieNode>();
 7     }
 8 }
 9 
10 public class Trie {
11     private TrieNode root;
12     
13     public Trie() {
14         root = new TrieNode();
15     }
16 
17     // Inserts a word into the trie.
18     public void insert(String word) {
19         TrieNode p = root;
20         char [] s = word.toCharArray();
21         int len = s.length;
22         int i = 0;
23         //traverse the existing character
24         while(i<len){
25             if(p.nexts.containsKey(s[i])){
26                 p = p.nexts.get(s[i]);
27                 i++;
28             }else{
29                 break;
30             }
31         }
32         //append new nodes
33         while(i<len){
34             TrieNode newNode = new TrieNode();
35             p.nexts.put(s[i],newNode);
36             p = newNode;
37             i++;
38         }
39         //Set the end of the word
40         p.isLeaf = true;
41     }
42 
43     // Returns if the word is in the trie.
44     public boolean search(String word) {
45         TrieNode p = root;
46         char [] s = word.toCharArray();
47         int len = s.length;
48         int i = 0;
49         while(i<len){
50             TrieNode nextNode = p.nexts.get(s[i]);
51             if(nextNode == null){
52                 return false;
53             }
54             p = nextNode;
55             i++;
56         }
57         //return if this is a leaf node
58         return p.isLeaf;
59     }
60 
61     // Returns if there is any word in the trie
62     // that starts with the given prefix.
63     public boolean startsWith(String prefix) {
64         TrieNode p = root;
65         char [] s = prefix.toCharArray();
66         int len = s.length;
67         int i = 0;
68         while(i<len){
69             TrieNode nextNode = p.nexts.get(s[i]);
70             if(nextNode == null){
71                 return false;
72             }
73             p = nextNode;
74             i++;
75         }
76         return true;
77     }
78 }
79 
80 // Your Trie object will be instantiated and called as such:
81 // Trie trie = new Trie();
82 // trie.insert("somestring");
83 // trie.search("key");

参考了这篇帖子：http://blog.csdn.net/wzy_1988/article/details/45744067#trie树基本实现