LeetCode 208. Implement Trie (Prefix Tree)

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字典树。

测试中有：aaaaaaaaaaa... 的输入，如果每个节点用定长数组存储孩子的话，那就是26^len的空间复杂度（len为输入的长度），内存会不够的。

所以用map<char, TrieNode*>保存其孩子。

第三遍（将第二遍中search和startsWith的行为抽象成searchNode方法）：

struct TrieNode{map<char, shared_ptr<TrieNode>> children;bool is_word = false;};class Trie{public:Trie(): root(shared_ptr<TrieNode>(new TrieNode)) {}// Inserts a word into the trie.void insert(string word) const{if (word.empty()){return ;}auto node = root;for (size_t i = 0; i < word.size(); node = node->children[word[i ++]]){if (node->children.find((word[i])) == node->children.end()){node->children[word[i]] = shared_ptr<TrieNode>(new TrieNode);}}node->is_word = true;}// Returns if the word is in the trie.bool search(string word) const{auto node = searchNode(word);return node!=nullptr && node->is_word;}// Returns if there is any word in the trie// that starts with the given prefix.bool startsWith(string prefix) const{return searchNode(prefix) != nullptr;}private:shared_ptr<TrieNode> searchNode(string word) const{auto node = root;for (size_t i = 0; i < word.size(); node = node->children[word[i ++]]){if (node->children.find(word[i]) == node->children.end()){return nullptr;}}return node;}shared_ptr<TrieNode> root;};

第二遍（将第一次代码中的尾递归改成了迭代，速度从270ms提升到了200ms）：

struct TrieNode{map<char, shared_ptr<TrieNode>> children;bool is_word = false;};class Trie{public:Trie(): root(shared_ptr<TrieNode>(new TrieNode)) {}// Inserts a word into the trie.void insert(string word) const{if (word.empty()){return ;}auto node = root;for (size_t i = 0; i < word.size(); node = node->children[word[i ++]]){if (node->children.find((word[i])) == node->children.end()){node->children[word[i]] = shared_ptr<TrieNode>(new TrieNode);}}node->is_word = true;}// Returns if the word is in the trie.bool search(string word) const{// no special judge for empty word hereauto node = root;for (size_t i = 0; i < word.size(); node = node->children[word[i ++]]){if (node->children.find(word[i]) == node->children.end()){return false;}}return node->is_word;}// Returns if there is any word in the trie// that starts with the given prefix.bool startsWith(string prefix) const{auto node = root;for (size_t i = 0; i < prefix.size(); node = node->children[prefix[i ++]]){if (node->children.find(prefix[i]) == node->children.end()){return false;}}return true;}private:shared_ptr<TrieNode> root;};

第一遍：

class TrieNode{public:// Initialize your data structure here.TrieNode(){is_word = false;}void insert(const string& word){if (!word.empty()){nodes[word.front()] =nodes[word.front()] != nullptr ?nodes[word.front()] : new TrieNode();nodes[word.front()]->insert(word.substr(1));} else{is_word = true;}}bool search(string word){if (!word.empty()){if (nodes[word.front()] == nullptr){return false;} else{return nodes[word.front()]->search(word.substr(1));}}return is_word;}bool startsWith(string prefix){if (!prefix.empty()){if (nodes[prefix.front()] == nullptr){return false;} else{return nodes[prefix.front()]->startsWith(prefix.substr(1));}}return true;}// MLE!!!// TrieNode* nodes[26];map<char, TrieNode*> nodes;bool is_word;};class Trie{public:Trie(){root = new TrieNode();}// Inserts a word into the trie.void insert(string word){root->insert(word);}// Returns if the word is in the trie.bool search(string word){return root->search(word);}// Returns if there is any word in the trie// that starts with the given prefix.bool startsWith(string prefix){return root->startsWith(prefix);}private:TrieNode* root;};

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