Trie memory optimization using hash map
We introduced and discussed an implementation in below post. Trie | (Insert and Search) – w3wiki The implementation used in above post uses an array of alphabet size with every node. It can be made memory efficient. One way to implementing Trie is linked set of nodes, where each node contains an array of child pointers, one for each symbol in the alphabet. This is not efficient in terms of time as we can’t quickly find a particular child. The efficient way is an implementation where we use hash map to store children of a node. Now we allocate memory only for alphabets in use, and don’t waste space storing null pointers.
CPP
// A memory optimized CPP implementation of trie // using unordered_map #include <iostream> #include <unordered_map> using namespace std; struct Trie { // isEndOfWord is true if the node // represents end of a word bool isEndOfWord; /* nodes store a map to child node */ unordered_map< char , Trie*> map; }; /*function to make a new trie*/ Trie* getNewTrieNode() { Trie* node = new Trie; node->isEndOfWord = false ; return node; } /*function to insert in trie*/ void insert(Trie*& root, const string& str) { if (root == nullptr) root = getNewTrieNode(); Trie* temp = root; for ( int i = 0; i < str.length(); i++) { char x = str[i]; /* make a new node if there is no path */ if (temp->map.find(x) == temp->map.end()) temp->map[x] = getNewTrieNode(); temp = temp->map[x]; } temp->isEndOfWord = true ; } /*function to search in trie*/ bool search(Trie* root, const string& str) { /*return false if Trie is empty*/ if (root == nullptr) return false ; Trie* temp = root; for ( int i = 0; i < str.length(); i++) { /* go to next node*/ temp = temp->map[str[i]]; if (temp == nullptr) return false ; } return temp->isEndOfWord; } /*Driver function*/ int main() { Trie* root = nullptr; insert(root, "Beginner" ); cout << search(root, "Beginner" ) << " " ; insert(root, "for" ); cout << search(root, "for" ) << " " ; cout << search(root, "geekk" ) << " " ; insert(root, "gee" ); cout << search(root, "gee" ) << " " ; insert(root, "science" ); cout << search(root, "science" ) << endl; return 0; } |
Java
// A memory optimized Java implementation of trie // using unordered_map import java.util.HashMap; public class Trie { // isEndOfWord is true if the node // represents end of a word boolean isEndOfWord; /* nodes store a map to child node */ HashMap<Character, Trie> map; /* function to make a new trie */ static Trie getNewTrieNode() { Trie node = new Trie(); node.isEndOfWord = false ; node.map = new HashMap<>(); return node; } /* function to insert in trie */ static void insert(Trie root, String str) { Trie temp = root; for ( int i = 0 ; i < str.length(); i++) { char x = str.charAt(i); /* make a new node if there is no path */ if (!temp.map.containsKey(x)) temp.map.put(x, getNewTrieNode()); temp = temp.map.get(x); } temp.isEndOfWord = true ; } /* function to search in trie */ static boolean search(Trie root, String str) { /* return false if Trie is empty */ if (root == null ) return false ; Trie temp = root; for ( int i = 0 ; i < str.length(); i++) { /* go to next node */ if (!temp.map.containsKey(str.charAt(i))) return false ; temp = temp.map.get(str.charAt(i)); } return temp.isEndOfWord; } /*Driver function*/ public static void main(String[] args) { Trie root = getNewTrieNode(); insert(root, "Beginner" ); System.out.print(search(root, "Beginner" ) + " " ); insert(root, "for" ); System.out.print(search(root, "for" ) + " " ); System.out.print(search(root, "geekk" ) + " " ); insert(root, "gee" ); System.out.print(search(root, "gee" ) + " " ); insert(root, "science" ); System.out.println(search(root, "science" )); insert(root, "scienc" ); System.out.println(search(root, "scienc" )); } } // This code is contributed by Aman Kumar. |
Python3
# A memory optimized Python implementation of trie # using dictionary from collections import defaultdict class TrieNode: def __init__( self ): # nodes store a map to child node self . map = defaultdict(TrieNode) # isEndOfWord is true if the node # represents end of a word self .is_end_of_word = False class Trie: # function to make a new trie def __init__( self ): self .root = TrieNode() # function to insert in trie def insert( self , word: str ) - > None : node = self .root for char in word: # make a new node if there is no path node = node. map [char] node.is_end_of_word = True # function to search in trie def search( self , word: str ) - > bool : node = self .root for char in word: if char not in node. map : return False node = node. map [char] return node.is_end_of_word # Driver function if __name__ = = '__main__' : # create a new Trie root = Trie() root.insert( 'Beginner' ) print (root.search( 'Beginner' ), end = ' ' ) root.insert( 'for' ) print (root.search( 'for' ), end = ' ' ) print (root.search( 'geekk' ), end = ' ' ) root.insert( 'gee' ) print (root.search( 'gee' ), end = ' ' ) root.insert( 'science' ) print (root.search( 'science' )) # This code is contributed by Utkarsh Kumar |
C#
// A memory optimized C# implementation of trie // using Dictionary using System.Collections.Generic; public class Trie { // isEndOfWord is true if the node // represents end of a word bool isEndOfWord; /* nodes store a dictionary to child node */ Dictionary< char , Trie> map; /* function to make a new trie */ static Trie getNewTrieNode() { Trie node = new Trie(); node.isEndOfWord = false ; node.map = new Dictionary< char , Trie>(); return node; } /* function to insert in trie */ static void insert(Trie root, string str) { Trie temp = root; for ( int i = 0; i < str.Length; i++) { char x = str[i]; /* make a new node if there is no path */ if (!temp.map.ContainsKey(x)) temp.map[x] = getNewTrieNode(); temp = temp.map[x]; } temp.isEndOfWord = true ; } /* function to search in trie */ static bool search(Trie root, string str) { /* return false if Trie is empty */ if (root == null ) return false ; Trie temp = root; for ( int i = 0; i < str.Length; i++) { /* go to next node */ if (!temp.map.ContainsKey(str[i])) return false ; temp = temp.map[str[i]]; } return temp.isEndOfWord; } /*Driver function*/ public static void Main() { Trie root = getNewTrieNode(); insert(root, "Beginner" ); System.Console.Write(search(root, "Beginner" ) + " " ); insert(root, "for" ); System.Console.Write(search(root, "for" ) + " " ); System.Console.Write(search(root, "geekk" ) + " " ); insert(root, "gee" ); System.Console.Write(search(root, "gee" ) + " " ); insert(root, "science" ); System.Console.WriteLine(search(root, "science" )); } } // This code is contributed by Pushpesh Raj. |
Javascript
// A memory optimized JS implementation of trie // using unordered_map class TrieNode { constructor() { // isEndOfWord is true if the node // represents end of a word this .isEndOfWord = false ; /* nodes store a map to child node */ this .map = new Map(); } } class Trie { constructor() { this .root = new TrieNode(); } /*function to insert in trie*/ insert(str) { let temp = this .root; for (let i = 0; i < str.length; i++) { const x = str[i]; /* make a new node if there is no path */ if (!temp.map.has(x)) { temp.map.set(x, new TrieNode()); } /* go to next node*/ temp = temp.map.get(x); } temp.isEndOfWord = true ; return this .root; } /*function to search in trie*/ search(str) { let temp = this .root; for (let i = 0; i < str.length; i++) { const x = str[i]; temp = temp.map.get(x); if (!temp) { return false ; } } return temp.isEndOfWord; } } /*Driver function*/ const trie = new Trie(); let root = null ; root = trie.insert( "Beginner" ); console.log(trie.search( "Beginner" )); // output: true root = trie.insert( "for" ); console.log(trie.search( "for" )); // output: true console.log(trie.search( "geekk" )); // output: false root = trie.insert( "gee" ); console.log(trie.search( "gee" )); // output: true root = trie.insert( "science" ); console.log(trie.search( "science" )); // output: true |
Output:
1 1 0 1 1
Space used here with every node here is proportional to number of children which is much better than proportional to alphabet size, especially if alphabet is large.
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