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Java-based LeetCode algorithm problem solutions, regularly updated
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package g0101_0200.s0146_lru_cache;

// #Medium #Top_100_Liked_Questions #Top_Interview_Questions #Hash_Table #Design #Linked_List
// #Doubly_Linked_List #Udemy_Linked_List #Big_O_Time_O(1)_Space_O(capacity)
// #2022_06_24_Time_87_ms_(50.80%)_Space_125.2_MB_(58.73%)

import java.util.HashMap;
import java.util.Map;

/**
 * 146 - LRU Cache\.
 *
 * Medium
 *
 * Design a data structure that follows the constraints of a **[Least Recently Used (LRU) cache](https://en.wikipedia.org/wiki/Cache_replacement_policies#LRU)**.
 *
 * 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 `-1`.
 * *   `void put(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 `put` must each run in `O(1)` average time complexity.
 *
 * **Example 1:**
 *
 * **Input** ["LRUCache", "put", "put", "get", "put", "get", "put", "get", "get", "get"] [[2], [1, 1], [2, 2], [1], [3, 3], [2], [4, 4], [1], [3], [4]]
 *
 * **Output:** [null, null, null, 1, null, -1, null, -1, 3, 4]
 *
 * **Explanation:**
 *
 *     LRUCache lRUCache = new LRUCache(2);
 *     lRUCache.put(1, 1); // cache is {1=1}
 *     lRUCache.put(2, 2); // cache is {1=1, 2=2}
 *     lRUCache.get(1); // return 1
 *     lRUCache.put(3, 3); // LRU key was 2, evicts key 2, cache is {1=1, 3=3}
 *     lRUCache.get(2); // returns -1 (not found)
 *     lRUCache.put(4, 4); // LRU key was 1, evicts key 1, cache is {4=4, 3=3}
 *     lRUCache.get(1); // return -1 (not found)
 *     lRUCache.get(3); // return 3
 *     lRUCache.get(4); // return 4 
 *
 * **Constraints:**
 *
 * *   `1 <= capacity <= 3000`
 * *   0 <= key <= 10⁴
 * *   0 <= value <= 10⁵
 * *   At most 2 * 10⁵ calls will be made to `get` and `put`.
**/
public class LRUCache {
    private static class LruCacheNode {
        int key;
        int value;
        LruCacheNode prev;
        LruCacheNode next;

        public LruCacheNode(int k, int v) {
            key = k;
            value = v;
        }
    }

    private int capacity;
    private Map cacheMap = new HashMap<>();
    // insert here
    private LruCacheNode head;
    // remove here
    private LruCacheNode tail;

    public LRUCache(int cap) {
        capacity = cap;
    }

    public int get(int key) {
        LruCacheNode val = cacheMap.get(key);
        if (val == null) {
            return -1;
        }
        moveToHead(val);
        return val.value;
    }

    /*
     * Scenarios :
     * 1. Value key is already present.
     *          update
     *          move node to head
     * 2. cache is not full
     *          cache is empty (create node and assign head and tail)
     *          cache is partially empty (add node to head and update head pointer)
     * 3. cache is full
     *          remove node at tail, update head, tail pointers
     *          Recursively call put
     *
     *
     * move node to head Scenarios
     * 1. node is at head
     * 2. node is at tail
     * 3. node is in middle
     *
     */
    public void put(int key, int value) {
        LruCacheNode valNode = cacheMap.get(key);
        if (valNode != null) {
            valNode.value = value;
            moveToHead(valNode);
        } else {
            if (cacheMap.size() < capacity) {
                if (cacheMap.size() == 0) {
                    LruCacheNode node = new LruCacheNode(key, value);
                    cacheMap.put(key, node);
                    head = node;
                    tail = node;
                } else {
                    LruCacheNode node = new LruCacheNode(key, value);
                    cacheMap.put(key, node);
                    node.next = head;
                    head.prev = node;
                    head = node;
                }
            } else {
                // remove from tail
                LruCacheNode last = tail;
                tail = last.prev;
                if (tail != null) {
                    tail.next = null;
                }
                cacheMap.remove(last.key);
                if (cacheMap.size() == 0) {
                    head = null;
                }
                // Call recursively
                put(key, value);
            }
        }
    }

    /*
     * check for 3 conditions
     * 1. node is already at head
     * 2. Node is tail node
     * 3. Node in middle node
     */
    private void moveToHead(LruCacheNode node) {
        if (node == head) {
            return;
        }
        if (node == tail) {
            tail = node.prev;
        }
        // node is not head, it should have some valid prev node
        LruCacheNode prev = node.prev;
        LruCacheNode next = node.next;
        prev.next = next;
        if (next != null) {
            next.prev = prev;
        }
        node.prev = null;
        node.next = head;
        head.prev = node;
        head = node;
    }
}

/*
 * Your LRUCache object will be instantiated and called as such:
 * LRUCache obj = new LRUCache(capacity);
 * int param_1 = obj.get(key);
 * obj.put(key,value);
 */