sreddy-96 / top-hash-table

The Odin Project - Hash Tables project

Hash Tables Implementation - The Odin Project

Project Overview

This project involves implementing custom Hash Map and Hash Set data structures in JavaScript. The goal is to create efficient hash-based data structures that can store and retrieve data quickly, while handling collisions effectively.

Key Features

• Custom hash function for optimal bucket distribution
• Collision handling using linked lists
• Separate implementations for Hash Map (key-value pairs) and Hash Set (unique keys)
• Dynamic resizing to maintain performance as the data structure grows

Core Functionalities

Both Hash Map and Hash Set implementations include the following methods:

• set(key, value): Add or update a key-value pair (Hash Map only)
• has(key): Check if a key exists
• get(key): Retrieve the value associated with a key (Hash Map only)
• remove(key): Delete a key-value pair
• length(): Return the number of stored elements
• clear(): Remove all entries
• keys(): Return an array of all keys
• values(): Return an array of all values (Hash Map only)
• entries(): Return an array of key-value pairs (Hash Map only)

Technical Highlights

• Prime number-based hash function to minimize collisions
• Use of linked lists for efficient collision resolution
• Constant time O(1) complexity for basic operations
• Automatic resizing based on load factor to maintain performance

Challenges and Solutions

1. Efficient Hashing: Implemented a hash function using prime numbers and modulo operation to distribute keys evenly across buckets.
2. Collision Handling: Utilized linked lists within buckets to manage multiple entries with the same hash.
3. Dynamic Resizing: Implemented a _resize method to increase bucket count when the load factor exceeds a threshold, maintaining performance as the data structure grows.

Skills Developed

• Deep understanding of hash table internals
• Improved problem-solving skills in handling edge cases and collisions
• Enhanced proficiency in JavaScript, particularly with array operations and object-oriented programming

Reflections

This project provided valuable insights into the inner workings of hash-based data structures. It highlighted the importance of efficient hashing and collision resolution in maintaining constant-time operations. The implementation of dynamic resizing demonstrated the trade-off between memory usage and performance in data structure design.

How to Use

1. Clone the repository:

   git clone https://github.com/SReddy-96/TOP-hash-table.git
   

2. Navigate to the project directory:

   cd hash-table
   

3. Run the script (if using Node.js):

   node index.js
   

Feel free to explore the code and test the various methods implemented in this Hash Table project!