Hash Table vs Trie - GeeksforGeeks (2024)

Trie memory optimization using hash map

We introduced and discussed an implementation in below post. Trie | (Insert and Search) - GeeksforGeeks 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 i

What are Hash Functions and How to choose a good Hash Function?

Prerequisite: Hashing | Set 1 (Introduction) What is a Hash Function? A function that converts a given big phone number to a small practical integer value. The mapped integer value is used as an index in the hash table. In simple terms, a hash function maps a big number or string to a small integer that can be used as the index in the hash table. W

Hash Functions and Types of Hash functions

Hash functions are a fundamental concept in computer science and play a crucial role in various applications such as data storage, retrieval, and cryptography. In data structures and algorithms (DSA), hash functions are primarily used in hash tables, which are essential for efficient data management. This article delves into the intricacies of hash

Comparison of an Array and Hash table in terms of Storage structure and Access time complexity

Arrays and Hash Tables are two of the most widely used data structures in computer science, both serving as efficient solutions for storing and accessing data in Java. They have different storage structures and time complexities, making them suitable for different use cases. In this article, we will explore the differences between arrays and hash t

Various load balancing techniques used in Hash table to ensure efficient access time

Load balancing refers to the process of distributing workloads evenly across multiple servers, nodes, or other resources to ensure optimal resource utilization, maximize output, minimize response time, and avoid overload of any single resource. Load balancing helps to improve the reliability and scalability of applications and systems, as well as r

Implementation of Hash Table in Python using Separate Chaining

A hash table is a data structure that allows for quick insertion, deletion, and retrieval of data. It works by using a hash function to map a key to an index in an array. In this article, we will implement a hash table in Python using separate chaining to handle collisions. Separate chaining is a technique used to handle collisions in a hash table.

Implementation of Hash Table in C/C++ using Separate Chaining

Introduction: Hashing is a technique that maps a large set of data to a small set of data. It uses a hash function for doing this mapping. It is an irreversible process and we cannot find the original value of the key from its hashed value because we are trying to map a large set of data into a small set of data, which may cause collisions. It is n

Hash Table vs STL Map

This article focus on : Compare and contrast Hash table and an STL Map. How is the hash table implemented? If the number of inputs is small, which data structure options can be used instead of a hash table? Hash table In a hash table, a value is stored by calling a hash function on a key. Values are not stored in sorted order.Additionally, since ha

Why use an Array to implement a "list" instead of a Hash Table?

What is an Array?An array is a collection of similar data elements stored at contiguous memory locations. It is the simplest data structure where each data element can be accessed directly by only using its index number. C/C++ Code #include <iostream> using namespace std; // driver program int main() { // initaizling array int arr[] = {1, 2,

Implementing our Own Hash Table with Separate Chaining in Java

All data structure has their own special characteristics, for example, a BST is used when quick searching of an element (in log(n)) is required. A heap or a priority queue is used when the minimum or maximum element needs to be fetched in constant time. Similarly, a hash table is used to fetch, add and remove an element in constant time. Anyone mus

Advantages of BST over Hash Table

Hash Table supports following operations in O(1) time. 1) Search 2) Insert 3) Delete The time complexity of above operations in a self-balancing Binary Search Tree (BST) (like Red-Black Tree, AVL Tree, Splay Tree, etc) is O(Logn). So Hash Table seems to beating BST in all common operations. When should we prefer BST over Hash Tables, what are advan

Hash Table Data Structure

What is Hash Table?A Hash table is defined as a data structure used to insert, look up, and remove key-value pairs quickly. It operates on the hashing concept, where each key is translated by a hash function into a distinct index in an array. The index functions as a storage location for the matching value. In simple words, it maps the keys with th

Sorting array of strings (or words) using Trie | Set-2 (Handling Duplicates)

Given an array of strings, print them in alphabetical (dictionary) order. If there are duplicates in input array, we need to print all the occurrences.Examples: Input : arr[] = { "abc", "xyz", "abcd", "bcd", "abc" } Output : abc abc abcd bcd xyz Input : arr[] = { "geeks", "for", "geeks", "a", "portal", "to", "learn" } Output : a for geeks geeks lea

Persistent Trie | Set 1 (Introduction)

Prerequisite: TriePersistency in Data Structure Trie is one handy data structure that often comes into play when performing multiple string lookups. In this post, we will introduce the concept of Persistency in this data structure. Persistency simply means to retain the changes. But obviously, retaining the changes cause extra memory consumption an

Bottom-up traversal of a Trie

Trie is an efficient information retrieval data structure. Using Trie, search complexities can be brought to an optimal limit (key length). Given a trie. The task is to print the characters in a bottom-up manner Bottom-up traversal: First print string of left most subtree(from bottom to top) then print string of second left subtree(from bottom to t

Check if the given Trie contains words starting from every alphabet

Given a Trie, the task is to check if it contains words starting from every alphabet from [a - z]. Examples: Input: keys[] = {"element", "fog", "great", "hi", "ok", "ios", "parrot", "quiz", "kim", "mango", "nature", "apple", "ball", "cat", "dog", "lime", "ruby", "shine", "tinkter", "ultra", "volly", "wow", "xerox", "yak", "zenon", "joke"} Output: Y

Implement a Dictionary using Trie

Implement a dictionary using Trie such that if the input is a string representing a word, the program prints its meaning from the prebuilt dictionary. Examples: Input: str = "map" Output: a diagrammatic representation of an area Input: str = "language" Output: the method of human communication Approach: We can use a Trie to efficiently store string

Insertion in a Trie recursively

Trie is an efficient information retrieval data structure. Using Trie, search complexities can be brought to an optimal limit (key length). Given multiple strings. The task is to insert the string in a Trie using recursion.Examples: Input : str = {"cat", "there", "caller", "their", "calling"} Output : caller calling cat there their root / \ c t | |

Search in a trie Recursively

Trie is an efficient information retrieval data structure. Using Trie, search complexities can be brought to an optimal limit (key length).The task is to search a string in a Trie using recursion.Examples : root / \ t a | | h n | | \ e s y / | | i r w | | | r e e | r Input : str = "anywhere" Output : not found Input : str = "answer" Output : found

Trie Data Structure using smart pointer and OOP in C++

We will implement trie using smart pointers in C++ and OOP. Here, We have already discussed the implementation of trie data using recursionIn our implementation node of a trie look like : C/C++ Code class TrieNode{ public: // Use of shared_ptr for storing Children // Pointers of TrieNode shared_ptr children[ALPHABET_SIZE]; // Tracks whether If this

Count inversions in an array | Set 4 ( Using Trie )

Inversion Count for an array indicates – how far (or close) the array is from being sorted. If the array is already sorted then inversion count is 0. If the array is sorted in reverse order that inversion count is the maximum. Two elements a[i] and a[j] form an inversion if a[i] > a[j] and i < j. For simplicity, we may assume that all element

Print Strings In Reverse Dictionary Order Using Trie

Trie is an efficient information retrieval data structure. Using Trie, search complexities can be brought to an optimal limit. Given an array of strings. The task is to print all strings in reverse dictionary order using Trie. If there are duplicates in the input array, we need to print them only once. Examples: Input: str = {"cat", "there", "calle

Print all possible joints of a Trie constructed from a given list of strings

Given a set of strings str, the task is to print all the joints of the Trie constructed from the given set of strings. Joints of a Trie is the nodes in a trie that have more than one child. Examples: Input: str = {"cat", "there", "caller", "their", "calling"} Output: l, a, e Explanation: root / \ c t | | a h / | | t l e | | \ l i r | \ | | e i r e

Spell Checker using Trie

Given an array of strings str[] and a string key, the task is to check if the spelling of the key is correct or not. If found to be true, then print "YES". Otherwise, print the suggested correct spellings. Examples: Input:str[] = { “gee”, “geeks”, “ape”, “apple”, “geeksforgeeks” }, key = “geek” Output: geeks geeksforgeeks Explanation: The string "g

Applications, Advantages and Disadvantages of Trie

Trie(pronounced as "try"): Trie(also known as the digital tree or prefix tree) is a sorted and efficient tree-based special data structure that is used to store and retrieve keys in a dataset of strings. The basic ideology behind this is retrieving information. It is based on the prefix of a string. It can be visualized as a graph consisting of nod

Trie meaning in DSA

Trie data structure is defined as a Tree based data structure that is used for storing some collection of strings and performing efficient search operations on them. The word Trie is derived from reTRIEval, which means finding something or obtaining it. Representation of trie is similar to a tree data structure with a root node connected to its ele

Program for assigning usernames using Trie

Suppose there is a queue of n users and your task is to assign a username to them. The system works in the following way. Every user has preferred login in the form of a string 's' s consists only of small case letters and numbers. User name is assigned in the following order s, s0, s1, s2....s11.... means first you check s if s is available assign

Construct a String from another String using Suffix Trie

A suffix tree is a data structure based on trie compression that stores all the suffixes of a given string. Apart from detecting patterns in strings, it has a range of applications in fields like bioinformatics, string algorithms, and data compression. Features of Suffix Trie:A Suffix Trie, commonly referred to as a suffix tree, is a data structure

Count of given Strings in 2D character Array using Trie

Counting the number of occurrences of a given string in a 2D character array using a Trie. Examples: Input: vector<string> grid = {"abcde", "fghij", "xyabc", "klmno",}; string word = "abc";Output: 2Explanation: abc occurs twice in "abcde", "xyabc" Input: vector<string> grid = {"abcde", "fghij", "xyabc", "klmno",}; string word = "klm";Ou