簡介
Trie樹,又稱為前綴樹或字典樹,是一種有序樹,用于保存關聯數組,其中的鍵通常是字符串。與二叉查找樹不同,鍵不是直接保存在節點中,而是由節點在樹中的位置決定。一個節點的所有子孫都有相同的前綴,也就是這個節點對應的字符串,而根節點對應空字符串。
它的主要特點如下:
根節點不包含字符,除根節點外的每一個節點都只包含一個字符。
從根節點到某一節點,路徑上經過的字符連接起來,為該節點對應的字符串。
每個節點的所有子節點包含的字符都不相同。
如下是一棵典型的Trie樹:

Trie的來源是Retrieval,它常用于前綴匹配和詞頻統計。可能有人要說了,詞頻統計簡單啊,一個hash或者一個堆就可以搞定,但問題來了,如果內存有限呢?還能這么 玩嗎?所以這里我們就可以用trie樹來壓縮下空間,因為公共前綴都是用一個節點保存的。
1、定義
這里為了簡化,只考慮了26個小寫字母。
首先是節點的定義:
public class TrieNode { public TrieNode[] children; public char data; public int freq; public TrieNode() { //因為有26個字母 children = new TrieNode[26]; freq = 0; }}然后是Trie樹的定義:
public class TrieTree { private TrieNode root; public TrieTree(){ root=new TrieNode(); } ...}2、插入
由于是26叉樹,故可通過charArray[index]-‘a';來得知字符應該放在哪個孩子中。
public void insert(String word){ if(TextUtils.isEmpty(word)){ return; } insertNode(root,word.toCharArray(),0); } private static void insertNode(TrieNode rootNode,char[]charArray,int index){ int k=charArray[index]-'a'; if(k<0||k>25){ throw new RuntimeException("charArray[index] is not a alphabet!"); } if(rootNode.children[k]==null){ rootNode.children[k]=new TrieNode(); rootNode.children[k].data=charArray[index]; } if(index==charArray.length-1){ rootNode.children[k].freq++; return; }else{ insertNode(rootNode.children[k],charArray,index+1); } }3、移除節點
移除操作中,需要對詞頻進行減一操作。
public void remove(String word){ if(TextUtils.isEmpty(word)){ return; } remove(root,word.toCharArray(),0); } private static void remove(TrieNode rootNode,char[]charArray,int index){ int k=charArray[index]-'a'; if(k<0||k>25){ throw new RuntimeException("charArray[index] is not a alphabet!"); } if(rootNode.children[k]==null){ //it means we cannot find the word in this tree return; } if(index==charArray.length-1&&rootNode.children[k].freq >0){ rootNode.children[k].freq--; } remove(rootNode.children[k],charArray,index+1); }4、查找頻率
public int getFreq(String word){ if(TextUtils.isEmpty(word)){ return 0; } return getFreq(root,word.toCharArray(),0); } private static int getFreq(TrieNode rootNode,char[]charArray,int index){ int k=charArray[index]-'a'; if(k<0||k>25){ throw new RuntimeException("charArray[index] is not a alphabet!"); } //it means the word is not in the tree if(rootNode.children[k]==null){ return 0; } if(index==charArray.length-1){ return rootNode.children[k].freq; } return getFreq(rootNode.children[k],charArray,index+1); }5、測試
測試代碼如下:
public static void test(){ TrieTree trieTree=new TrieTree(); String sourceStr="Democratic presumptive nominee Hillary Clintons campaign posed pounced on Trumps assertion that British term monetary turmoil might benefit his business venture in Scotland"; //String sourceStr="the that"; sourceStr=sourceStr.toLowerCase(); String[]strArray=sourceStr.split(" "); for(String str:strArray){ trieTree.insert(str); } String sourceStr2="Every president is tested by world events But Donald Trump thinks about how is his golf resort can profit from that"; sourceStr2=sourceStr2.toLowerCase(); String[]strArray2=sourceStr2.split(" "); for(String str:strArray2){ trieTree.insert(str); } BinaryTree.print("frequence of 'that':"+trieTree.getFreq("that")); BinaryTree.print("/nfrequence of 'donald':"+trieTree.getFreq("donald")); trieTree.remove("that"); BinaryTree.print("/nafter remove 'that' once,freq of 'that':"+trieTree.getFreq("that")); trieTree.remove("that"); BinaryTree.print("/nafter remove 'that' twice,freq of 'that':"+trieTree.getFreq("that")); trieTree.remove("donald"); BinaryTree.print("/nafter remove 'donald' once,freq of 'donald':"+trieTree.getFreq("donald")); BinaryTree.reallyStartPrint(); }測試結果如下:

總結
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