lru-cache

Least Recently Used (LRU) Cache

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A Least Recently Used (LRU) Cache organizes items in order of use, allowing you to quickly identify which item hasn't been used for the longest amount of time.

Picture a clothes rack, where clothes are always hung up on one side. To find the least-recently used item, look at the item on the other end of the rack.

The problem statement

Implement the LRUCache class:

• LRUCache(int capacity) Initialize the LRU cache with positive size capacity.
• int get(int key) Return the value of the key if the key exists, otherwise return undefined.
• void set(int key, int value) Update the value of the key if the key exists. Otherwise, add the key-value pair to the cache. If the number of keys exceeds the capacity from this operation, evict the least recently used key.

The functions get() and set() must each run in O(1) average time complexity.

Implementation

Version 1: Doubly Linked List + Hash Map

See the LRUCache implementation example in LRUCache.js. The solution uses a HashMap for fast O(1) (in average) cache items access, and a DoublyLinkedList for fast O(1) (in average) cache items promotions and eviction (to keep the maximum allowed cache capacity).

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You may also find more test-case examples of how the LRU Cache works in LRUCache.test.js file.

Version 2: Ordered Map

The first implementation that uses doubly linked list is good for learning purposes and for better understanding of how the average O(1) time complexity is achievable while doing set() and get().

However, the simpler approach might be to use a JavaScript Map object. The Map object holds key-value pairs and remembers the original insertion order of the keys. We can use this fact in order to keep the recently-used items in the "end" of the map by removing and re-adding items. The item at the beginning of the Map is the first one to be evicted if cache capacity overflows. The order of the items may checked by using the IterableIterator like map.keys().

See the LRUCacheOnMap implementation example in LRUCacheOnMap.js.

You may also find more test-case examples of how the LRU Cache works in LRUCacheOnMap.test.js file.

Complexities

	Average
Space	O(n)
Get item	O(1)
Set item	O(1)

References

• LRU Cache on LeetCode
• LRU Cache on InterviewCake
• LRU Cache on Wiki