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LRUCache.java
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package Leetcode;
import java.util.HashMap;
import java.util.Map;
/**
* @author kalpak
*
* Design a data structure that follows the constraints of a Least Recently Used (LRU) cache.
*
* 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.
*
* Follow up:
* Could you do get and put in O(1) 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 <= 3000
* 0 <= value <= 104
* At most 3 * 104 calls will be made to get and put.
*/
public class LRUCache {
Map<Integer, DataNode> map;
DataNode head;
DataNode tail;
int itemsInCache;
int maxCapacity;
public LRUCache(int capacity) {
map = new HashMap<>();
head = new DataNode();
tail = new DataNode();
head.next = tail;
tail.prev = head;
maxCapacity = capacity;
itemsInCache = 0;
}
public int get(int key) {
DataNode result = map.get(key);
if(result != null) {
moveToHead(result);
return result.value;
}
return -1;
}
public void put(int key, int value) {
DataNode node = map.get(key);
if(node != null) {
node.value = value;
moveToHead(node);
} else {
DataNode data = new DataNode(key, value);
map.put(key, data);
itemsInCache++;
addToFront(data);
if(itemsInCache > maxCapacity) {
removeFromCache();
itemsInCache--;
}
}
}
private void moveToHead(DataNode node) {
removeData(node);
addToFront(node);
}
private void removeFromCache() {
DataNode tailNode = tail.prev;
removeData(tailNode);
map.remove(tailNode.key);
}
private void removeData(DataNode node) {
DataNode prevNode = node.prev;
DataNode nextNode = node.next;
prevNode.next = nextNode;
nextNode.prev = prevNode;
}
private void addToFront(DataNode node) {
node.prev = head;
node.next = head.next;
head.next.prev = node;
head.next = node;
}
private class DataNode {
int key;
int value;
DataNode prev;
DataNode next;
public DataNode() {
prev = next = null;
}
public DataNode(int key, int value) {
this.key = key;
this.value = value;
}
}
}