![]() It shows the time at which the key is stored. Here each data element stores extra information to mark with an access time stamp. We initialize an array of sizes equal to that of our cache. Brute force approach: LRU cache using simple array The main idea of the LRU cache is to store the n recently accessed elements (assume that the size of the cache is n). There are different ways of handling this LRU cache is one such way. So we cannot fit everything from the main memory into the cache. The cache memory size is generally much smaller than the main memory. Thus, cache memory reduces the average time for accessing data from the main memory. A cache holds frequently requested data and instructions to be immediately available to the CPU. A high-speed memory known as cache memory is used to avoid accessing data from memory repeatedly. Generally, retrieving data from a computer’s memory is an expensive task. Since our cache can store only three elements, we need to discard the least recently used element from our cache.īefore designing the implementation of the LRU cache, we will look at the need for a cache. So, we remove the least recently used element, A1, in this case. But where will we store it in our cache? We have to remove some elements so that we can keep A4. Notice that the position of A2 is at the top again, as A2 is the most recently used element now. Instead of getting this from memory, we can get this from our cache. A2 gets stored at the topmost level, and A1 is moved down as it is no longer the most recently used element. We get the value of A1 from memory and store it in the cache. Initially, the cache is empty, and all the elements are stored in memory. ![]() Suppose we have five elements in the main memory, A1 to A5. Let's understand the problem via an example Time required to put any item should be O(1).Time required to get the least recently used element should be O(1).Access time for any item should be O(1).We want the following specifications from our LRU cache: If number of keys exceeds the capacity of lru cache, evict the least recently used key. Otherwise, add key-value pair to the cache. void put(int key, int value): Update the value of key if key exists.int get(int key): Return the value of key if key exists, otherwise, return -1.LRUCache(int capacity): Initialize LRU cache with positive size capacity.We need to implement LRUCache class with the following operations: So our goal is to design a data structure that follows the constraints of a Least Recently Used (LRU) cache. This strategy is useful for optimizing the use of limited cache space and improving the performance of caching systems. It organizes items in the order of their use, allowing us to easily identify items that have not been used for a long time. The Least Recently Used (LRU) cache is a popular caching strategy that discards the least recently used items first to make room for new elements when the cache is full. Key takeaway: an excellent algorithm to learn data structure design and problem-solving using hash tables and doubly-linked lists. Difficulty: Hard, Asked-in: Amazon, Microsoft, Adobe, Google
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