Add an example of the LRU Cache based on the Map.

trekhleb · trekhleb · commit 4b4d77071cee · 2023-01-24T09:43:12.000+01:00
diff --git a/src/data-structures/lru-cache/LRUCache.js b/src/data-structures/lru-cache/LRUCache.js
@@ -24,7 +24,7 @@ class LinkedListNode {
  * Implementation of the LRU (Least Recently Used) Cache
  * based on the HashMap and Doubly Linked List data-structures.
  *
- * Current implementation allows to have fast (O(1)) read and write operations.
+ * Current implementation allows to have fast O(1) (in average) read and write operations.
  *
  * At any moment in time the LRU Cache holds not more that "capacity" number of items in it.
  */
@@ -43,7 +43,7 @@ class LRUCache {
 
   /**
    * Returns the cached value by its key.
-   * Time complexity: O(1).
+   * Time complexity: O(1) in average.
    * @param {string} key
    * @returns {any}
    */
@@ -56,7 +56,7 @@ class LRUCache {
 
   /**
    * Sets the value to cache by its key.
-   * Time complexity: O(1).
+   * Time complexity: O(1) in average.
    * @param {string} key
    * @param {any} val
    */
diff --git a/src/data-structures/lru-cache/LRUCacheOnMap.js b/src/data-structures/lru-cache/LRUCacheOnMap.js
@@ -0,0 +1,53 @@
+/* eslint-disable no-restricted-syntax, no-unreachable-loop */
+
+/**
+ * Implementation of the LRU (Least Recently Used) Cache
+ * based on the (ordered) Map data-structure.
+ *
+ * Current implementation allows to have fast O(1) (in average) read and write operations.
+ *
+ * At any moment in time the LRU Cache holds not more that "capacity" number of items in it.
+ */
+class LRUCacheOnMap {
+  /**
+   * Creates a cache instance of a specific capacity.
+   * @param {number} capacity
+   */
+  constructor(capacity) {
+    this.capacity = capacity; // How many items to store in cache at max.
+    this.items = new Map(); // The ordered hash map of all cached items.
+  }
+
+  /**
+   * Returns the cached value by its key.
+   * Time complexity: O(1) in average.
+   * @param {string} key
+   * @returns {any}
+   */
+  get(key) {
+    if (!this.items.has(key)) return undefined;
+    const val = this.items.get(key);
+    this.items.delete(key);
+    this.items.set(key, val);
+    return val;
+  }
+
+  /**
+   * Sets the value to cache by its key.
+   * Time complexity: O(1).
+   * @param {string} key
+   * @param {any} val
+   */
+  set(key, val) {
+    this.items.delete(key);
+    this.items.set(key, val);
+    if (this.items.size > this.capacity) {
+      for (const headKey of this.items.keys()) {
+        this.items.delete(headKey);
+        break;
+      }
+    }
+  }
+}
+
+export default LRUCacheOnMap;
diff --git a/src/data-structures/lru-cache/README.md b/src/data-structures/lru-cache/README.md
@@ -16,6 +16,8 @@ The functions `get()` and `set()` must each run in `O(1)` average time complexit
 
 ## Implementation
 
+### Version 1: Doubly Linked List + Hash Map
+
 See the `LRUCache` implementation example in [LRUCache.js](./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).
 
 ![Linked List](./images/lru-cache.jpg)
@@ -24,6 +26,16 @@ See the `LRUCache` implementation example in [LRUCache.js](./LRUCache.js). The s
 
 You may also find more test-case examples of how the LRU Cache works in [LRUCache.test.js](./__test__/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](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/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](./LRUCacheOnMap.js).
+
+You may also find more test-case examples of how the LRU Cache works in [LRUCacheOnMap.test.js](./__test__/LRUCacheOnMap.test.js) file.
+
 ## Complexities
 
 |   | Average |
diff --git a/src/data-structures/lru-cache/__test__/LRUCacheOnMap.test.js b/src/data-structures/lru-cache/__test__/LRUCacheOnMap.test.js
@@ -0,0 +1,148 @@
+import LRUCache from '../LRUCacheOnMap';
+
+describe('LRUCacheOnMap', () => {
+  it('should set and get values to and from the cache', () => {
+    const cache = new LRUCache(100);
+    expect(cache.get('key-1')).toBeUndefined();
+
+    cache.set('key-1', 15);
+    cache.set('key-2', 16);
+    cache.set('key-3', 17);
+    expect(cache.get('key-1')).toBe(15);
+    expect(cache.get('key-2')).toBe(16);
+    expect(cache.get('key-3')).toBe(17);
+    expect(cache.get('key-3')).toBe(17);
+    expect(cache.get('key-2')).toBe(16);
+    expect(cache.get('key-1')).toBe(15);
+
+    cache.set('key-1', 5);
+    cache.set('key-2', 6);
+    cache.set('key-3', 7);
+    expect(cache.get('key-1')).toBe(5);
+    expect(cache.get('key-2')).toBe(6);
+    expect(cache.get('key-3')).toBe(7);
+  });
+
+  it('should evict least recently used items from cache with cache size of 1', () => {
+    const cache = new LRUCache(1);
+    expect(cache.get('key-1')).toBeUndefined();
+
+    cache.set('key-1', 15);
+    expect(cache.get('key-1')).toBe(15);
+
+    cache.set('key-2', 16);
+    expect(cache.get('key-1')).toBeUndefined();
+    expect(cache.get('key-2')).toBe(16);
+
+    cache.set('key-2', 17);
+    expect(cache.get('key-2')).toBe(17);
+
+    cache.set('key-3', 18);
+    cache.set('key-4', 19);
+    expect(cache.get('key-2')).toBeUndefined();
+    expect(cache.get('key-3')).toBeUndefined();
+    expect(cache.get('key-4')).toBe(19);
+  });
+
+  it('should evict least recently used items from cache with cache size of 2', () => {
+    const cache = new LRUCache(2);
+    expect(cache.get('key-21')).toBeUndefined();
+
+    cache.set('key-21', 15);
+    expect(cache.get('key-21')).toBe(15);
+
+    cache.set('key-22', 16);
+    expect(cache.get('key-21')).toBe(15);
+    expect(cache.get('key-22')).toBe(16);
+
+    cache.set('key-22', 17);
+    expect(cache.get('key-22')).toBe(17);
+
+    cache.set('key-23', 18);
+    expect(cache.get('key-21')).toBeUndefined();
+    expect(cache.get('key-22')).toBe(17);
+    expect(cache.get('key-23')).toBe(18);
+
+    cache.set('key-24', 19);
+    expect(cache.get('key-21')).toBeUndefined();
+    expect(cache.get('key-22')).toBeUndefined();
+    expect(cache.get('key-23')).toBe(18);
+    expect(cache.get('key-24')).toBe(19);
+  });
+
+  it('should evict least recently used items from cache with cache size of 3', () => {
+    const cache = new LRUCache(3);
+
+    cache.set('key-1', 1);
+    cache.set('key-2', 2);
+    cache.set('key-3', 3);
+    expect(cache.get('key-1')).toBe(1);
+    expect(cache.get('key-2')).toBe(2);
+    expect(cache.get('key-3')).toBe(3);
+
+    cache.set('key-3', 4);
+    expect(cache.get('key-1')).toBe(1);
+    expect(cache.get('key-2')).toBe(2);
+    expect(cache.get('key-3')).toBe(4);
+
+    cache.set('key-4', 5);
+    expect(cache.get('key-1')).toBeUndefined();
+    expect(cache.get('key-2')).toBe(2);
+    expect(cache.get('key-3')).toBe(4);
+    expect(cache.get('key-4')).toBe(5);
+  });
+
+  it('should promote the node while calling set() method', () => {
+    const cache = new LRUCache(2);
+
+    cache.set('2', 1);
+    cache.set('1', 1);
+    cache.set('2', 3);
+    cache.set('4', 1);
+    expect(cache.get('1')).toBeUndefined();
+    expect(cache.get('2')).toBe(3);
+  });
+
+  it('should promote the recently accessed item with cache size of 3', () => {
+    const cache = new LRUCache(3);
+
+    cache.set('key-1', 1);
+    cache.set('key-2', 2);
+    cache.set('key-3', 3);
+    expect(cache.get('key-1')).toBe(1);
+
+    cache.set('key-4', 4);
+    expect(cache.get('key-1')).toBe(1);
+    expect(cache.get('key-3')).toBe(3);
+    expect(cache.get('key-4')).toBe(4);
+    expect(cache.get('key-2')).toBeUndefined();
+  });
+
+  it('should promote the recently accessed item with cache size of 4', () => {
+    const cache = new LRUCache(4);
+
+    cache.set('key-1', 1);
+    cache.set('key-2', 2);
+    cache.set('key-3', 3);
+    cache.set('key-4', 4);
+    expect(cache.get('key-4')).toBe(4);
+    expect(cache.get('key-3')).toBe(3);
+    expect(cache.get('key-2')).toBe(2);
+    expect(cache.get('key-1')).toBe(1);
+
+    cache.set('key-5', 5);
+    expect(cache.get('key-1')).toBe(1);
+    expect(cache.get('key-2')).toBe(2);
+    expect(cache.get('key-3')).toBe(3);
+    expect(cache.get('key-4')).toBeUndefined();
+    expect(cache.get('key-5')).toBe(5);
+
+    cache.set('key-6', 6);
+    expect(cache.get('key-1')).toBeUndefined();
+    expect(cache.get('key-2')).toBe(2);
+    expect(cache.get('key-3')).toBe(3);
+    expect(cache.get('key-4')).toBeUndefined();
+    expect(cache.get('key-5')).toBe(5);
+    expect(cache.get('key-6')).toBe(6);
+  });
+});
