Data structure comparison: Set VS Map

Last update: 06-20-2024

Understanding Set and Map Data Structures Through Hash Tables

In modern programming languages, two fundamental data structures are widely implemented: the Set and the Map (also known as a Dictionary). Both play critical roles in data management and organization but serve different purposes and are implemented in subtly different ways.

What are Set and Map Used For?

• Set: This data structure is used to store a collection of unique elements. It does not allow duplicates, making it ideal for situations where you need to ensure no repeated values, such as in user ID collections or to remove duplicates from data efficiently.
• Map (or Dictionary): A Map stores pairs of keys and values where each key must be unique. This structure is perfect for cases where items need to be retrieved quickly by a unique identifier, like a product code or a person’s ID number.

How are Set and Map Implemented?

Both Set and Map can be effectively implemented using hash tables, a basic yet powerful concept in computer science.

Hash Table:

A hash table stores elements in an array format. To add an element X to the hash table, a hash function is applied to X to determine the index in the array where X should be placed. The hash function is designed to evenly distribute entries across the array to minimize collisions (where two elements are hashed to the same index).

Implementation Details of Set and Map Using Hash Tables

Set Implementation:

• Inserting an Element: When adding a new element, the hash function is used to find the appropriate index. If the index is already occupied (a collision), strategies like linear probing or chaining are used to find an available space.
• Existence Check: To determine if an element is present in the Set, compute its hash and check the corresponding index in the array.

Map Implementation:

• Inserting Key-Value Pairs: To add a new pair, apply the hash function to the key to find the array index. If a pair with the same key exists at that index, the value is updated. If there’s a collision with a different key, the same collision resolution strategies as used in Set are applied.
• Searching and Accessing Values: To find a value, hash the key to locate the correct index and perform a search at that position.

How Does the Implementation Affect Runtime?

Operations such as insertion, searching, and deletion in a hash table typically have an average time complexity of O(1), thanks to the direct index access provided by hashing. However, poor hash function design or a high number of collisions can degrade performance, potentially to O(n) in the worst-case scenario.

Similarities and Differences

While both Set and Map use hash tables and share similar implementation techniques, they serve different purposes. The Set is solely focused on unique elements, making it simpler in terms of data handling. The Map, on the other hand, manages pairs and involves more complexity due to the necessity of handling both keys and values.