Which Data Structure Is Used for LRU Cache?


Scott Campbell

The Least Recently Used (LRU) cache is a popular data structure used in computer science and software engineering. It is designed to store a limited number of items and efficiently manage the most recently accessed items. In this article, we will explore the data structure commonly used for implementing an LRU cache.

What is an LRU Cache?

An LRU cache is a type of cache that evicts the least recently used items when it reaches its capacity limit. It is widely used in scenarios where there is a need to store frequently accessed items, such as in web browsers, databases, and operating systems.

Choosing the Right Data Structure

When implementing an LRU cache, it is crucial to choose an appropriate data structure that provides efficient operations for inserting, accessing, and removing items. The two common data structures used for this purpose are:

  • Doubly Linked List: A doubly linked list is a linear data structure that consists of nodes linked together via two pointers: one pointing to the previous node and another to the next node. Each node in the list stores the key-value pair of an item in the cache.

    The head of the list represents the most recently used item, while the tail represents the least recently used item.

  • Hash Map: A hash map (also known as hash table) is a data structure that uses hash functions to map keys to values. It provides constant-time average case complexity for insertion, deletion, and retrieval operations. In the context of an LRU cache, a hash map can be used to quickly locate items based on their keys.

Combining Doubly Linked List and Hash Map

The most efficient way to implement an LRU cache is by combining the strengths of both the doubly linked list and the hash map. The doubly linked list ensures constant-time operations for eviction and moving items to the front, while the hash map provides faster access to items based on their keys.

Here’s a step-by-step process of using these data structures to implement an LRU cache:

  1. Create a fixed-size doubly linked list with a maximum capacity.
  2. Create an empty hash map to store references to the nodes in the linked list.
  3. When inserting a new item into the cache:
    • If the item is already present, move it to the front of the linked list.
    • If the cache is at its maximum capacity, remove the least recently used item from both the linked list and hash map.
    • Create a new node for the item and insert it at the front of the linked list. Add a reference to this node in the hash map for quick access.
  4. When accessing an item from the cache:
    • If it exists in the hash map, move it to the front of the linked list and return its value.
    • If it doesn’t exist, return an appropriate value (e.g., null).

This combination of data structures ensures efficient caching operations while maintaining constant-time complexity for most operations. It allows for fast lookup, insertion, removal, and eviction of items in an LRU cache.


The LRU cache is a powerful data structure that efficiently manages frequently accessed items while keeping memory usage under control. By combining a doubly linked list with a hash map, we can create an LRU cache that provides fast operations for insertion, retrieval, and eviction.

Now that you understand the data structure used for LRU cache, you can confidently design and implement efficient caching mechanisms in your applications.

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