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LRUCache146.java
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LRUCache146.java
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/**
* 146. LRU Cache
*
* Design and implement a data structure for Least Recently Used (LRU) cache.
* https://en.wikipedia.org/wiki/Cache_replacement_policies#LRU
*
* It should support the following operations: get and put.
*
* get(key) - Get the value (will always be positive) of the key if the key
* exists in the cache, otherwise return -1.
* put(key, value) - Set or insert the value if the key is not already present.
* When the cache reached its capacity, it should invalidate
* the least recently used item before inserting a new item.
*
* Follow up:
* Could you do both operations in O(1) time complexity?
*
* Example:
*
* LRUCache cache = new LRUCache( 2 ); // capacity
*
* cache.put(1, 1);
* cache.put(2, 2);
* cache.get(1); // returns 1
* cache.put(3, 3); // evicts key 2
* cache.get(2); // returns -1 (not found)
* cache.put(4, 4); // evicts key 1
* cache.get(1); // returns -1 (not found)
* cache.get(3); // returns 3
* cache.get(4); // returns 4
*/
/**
* 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);
*/
public class LRUCache {
private class Node{
int key, value;
Node prev, next;
Node(int k, int v){
this.key = k;
this.value = v;
}
Node(){
this(0, 0);
}
}
private int capacity;
private Map<Integer, Node> map;
private Node head, tail;
public LRUCache(int capacity) {
this.capacity = capacity;
map = new HashMap<>();
head = new Node();
tail = new Node();
head.next = tail;
tail.prev = head;
}
public int get(int key) {
Node n = map.get(key);
if(null==n){
return -1;
}
update(n);
return n.value;
}
public void put(int key, int value) {
Node n = map.get(key);
if(null==n){
n = new Node(key, value);
map.put(key, n);
add(n);
}
else{
n.value = value;
update(n);
}
if(map.size()>capacity){
Node toDel = tail.prev;
remove(toDel);
map.remove(toDel.key);
}
}
private void update(Node node){
remove(node);
add(node);
}
private void add(Node node){
Node after = head.next;
head.next = node;
node.prev = head;
node.next = after;
after.prev = node;
}
private void remove(Node node){
Node before = node.prev, after = node.next;
before.next = after;
after.prev = before;
}
}
/**
* Easy LinkedHashMap Implementation
*/
import java.util.LinkedHashMap;
import java.util.Map;
public class LRUCache {
private Map<Integer, Integer> map;
private Integer capacity;
public LRUCache(int capacity) {
map = new LinkedHashMap<Integer, Integer>(capacity) {
@Override
protected boolean removeEldestEntry(Map.Entry eldest) {
return size() > capacity;
}
};
this.capacity = capacity;
}
public int get(int key) {
if (map.containsKey(key)) {
Integer i = map.get(key);
map.remove(key);
map.put(key, i);
return i;
}
return -1;
}
public void put(int key, int value) {
if (value < 0) return;
if (map.containsKey(key)) {
map.remove(key);
}
map.put(key, value);
}
}
// class LRUCache {
//
// private Map<Integer, Node> map = new HashMap<>();
// private Node head = new Node(-1, -1);
// private Node tail = new Node(-1, -1);
// private int capacity;
//
// public LRUCache(int capacity) {
// this.capacity = capacity;
// head.next = tail;
// tail.pre = head;
// }
//
// public int get(int key) {
// Node n = map.get(key);
// if (n == null) return -1;
// detach(n);
// toEnd(n);
// return n.val;
// }
//
// public void put(int key, int value) {
// Node n = map.get(key);
// if (n == null) {
// n = new Node(key, value);
// if (map.size() >= capacity) {
// Node first = head.next;
// if (first.val != -1) {
// detach(first);
// map.remove(first.key);
// }
// }
// toEnd(n);
// map.put(key, n);
// } else {
// n.key = key;
// n.val = value;
// detach(n);
// toEnd(n);
// }
// }
//
// private void detach(Node n) {
// n.pre.next = n.next;
// n.next.pre = n.pre;
// }
//
// private void toEnd(Node n) {
// n.pre = tail.pre;
// tail.pre.next = n;
// tail.pre = n;
// n.next = tail;
// }
//
// class Node {
// int val;
// int key;
// Node pre;
// Node next;
// public Node(int key, int val) {
// this.key = key;
// this.val = val;
// }
// }
//
// }