Trie Basics
import java.util.TreeMap;
public class Trie {
private class Node{
public boolean isWord;
public TreeMap<Character, Node> next;
public Node(boolean isWord){
this.isWord = isWord;
next = new TreeMap<>();
}
public Node(){
this(false);
}
}
private Node root;
private int size;
public Trie(){
root = new Node();
size = 0;
}
// 获得Trie中存储的单词数量
public int getSize(){
return size;
}
// 向Trie中添加一个新的单词word
public void add(String word){
Node cur = root;
for(int i = 0 ; i < word.length() ; i ++){
char c = word.charAt(i);
if(cur.next.get(c) == null)
cur.next.put(c, new Node());
cur = cur.next.get(c);
}
if(!cur.isWord){
cur.isWord = true;
size ++;
}
}
}
searchig in trie
// 查询单词word是否在Trie中
public boolean contains(String word){
Node cur = root;
for(int i = 0 ; i < word.length() ; i ++){
char c = word.charAt(i);
if(cur.next.get(c) == null)
return false;
cur = cur.next.get(c);
}
return cur.isWord;
}
前缀查询
// 查询是否在Trie中有单词以prefix为前缀
public boolean isPrefix(String prefix){
Node cur = root;
for(int i = 0 ; i < prefix.length() ; i ++){
char c = prefix.charAt(i);
if(cur.next.get(c) == null)
return false;
cur = cur.next.get(c);
}
return true;
}
Leetcode208 实现Trie
/// 208. Implement Trie (Prefix Tree)
/// https://leetcode.com/problems/implement-trie-prefix-tree/description/
import java.util.TreeMap;
public class Trie208 {
private class Node{
public boolean isWord;
public TreeMap<Character, Node> next;
public Node(boolean isWord){
this.isWord = isWord;
next = new TreeMap<>();
}
public Node(){
this(false);
}
}
private Node root;
public Trie208(){
root = new Node();
}
// 向Trie中添加一个新的单词word
public void insert(String word){
Node cur = root;
for(int i = 0 ; i < word.length() ; i ++){
char c = word.charAt(i);
if(cur.next.get(c) == null)
cur.next.put(c, new Node());
cur = cur.next.get(c);
}
cur.isWord = true;
}
// 查询单词word是否在Trie中
public boolean search(String word){
Node cur = root;
for(int i = 0 ; i < word.length() ; i ++){
char c = word.charAt(i);
if(cur.next.get(c) == null)
return false;
cur = cur.next.get(c);
}
return cur.isWord;
}
// 查询是否在Trie中有单词以prefix为前缀
public boolean startsWith(String isPrefix){
Node cur = root;
for(int i = 0 ; i < isPrefix.length() ; i ++){
char c = isPrefix.charAt(i);
if(cur.next.get(c) == null)
return false;
cur = cur.next.get(c);
}
return true;
}
}
Leetcode211 添加与搜索单词
/// Leetcode 211. Add and Search Word - Data structure design
/// https://leetcode.com/problems/add-and-search-word-data-structure-design/description/
import java.util.TreeMap;
public class WordDictionary {
private class Node{
public boolean isWord;
public TreeMap<Character, Node> next;
public Node(boolean isWord){
this.isWord = isWord;
next = new TreeMap<>();
}
public Node(){
this(false);
}
}
private Node root;
/** Initialize your data structure here. */
public WordDictionary() {
root = new Node();
}
/** Adds a word into the data structure. */
public void addWord(String word) {
Node cur = root;
for(int i = 0 ; i < word.length() ; i ++){
char c = word.charAt(i);
if(cur.next.get(c) == null)
cur.next.put(c, new Node());
cur = cur.next.get(c);
}
cur.isWord = true;
}
/** Returns if the word is in the data structure. A word could contain the dot character '.' to represent any one letter. */
public boolean search(String word) {
return match(root, word, 0);
}
private boolean match(Node node, String word, int index){
if(index == word.length())
return node.isWord;
char c = word.charAt(index);
if(c != '.'){
if(node.next.get(c) == null)
return false;
return match(node.next.get(c), word, index + 1);
}
else{
for(char nextChar: node.next.keySet())
if(match(node.next.get(nextChar), word, index + 1))
return true;
return false;
}
}
}
Leetcode 677 Map Sum Pairs
import java.util.TreeMap;
public class MapSum {
private class Node{
public int value;
public TreeMap<Character, Node> next;
public Node(int value){
this.value = value;
next = new TreeMap<>();
}
public Node(){
this(0);
}
}
private Node root;
/** Initialize your data structure here. */
public MapSum() {
root = new Node();
}
public void insert(String key, int val) {
Node cur = root;
for(int i = 0 ; i < key.length() ; i ++){
char c = key.charAt(i);
if(cur.next.get(c) == null)
cur.next.put(c, new Node());
cur = cur.next.get(c);
}
cur.value = val;
}
public int sum(String prefix) {
Node cur = root;
for(int i = 0 ; i < prefix.length() ; i ++){
char c = prefix.charAt(i);
if(cur.next.get(c) == null)
return 0;
cur = cur.next.get(c);
}
return sum(cur);
}
private int sum(Node node){
int res = node.value;
// 遍历所有的子树，把value值加入res
for(char c: node.next.keySet())
res += sum(node.next.get(c));
return res;
}
}
Trie的删除操作
- 当搜索到该单词的最后一个字母时，自底向上的删除
- 当首字母被公用的时候，保留首字母，只删除后面的字母就行
- 当删除的最后一个字母根本不是叶子节点的时候，直接删除isword就行
Trie局限性
