Design and implement a data structure for Least Recently Used (LRU) cache. 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


 

 

此题的思路是运用hashmap和double linked nodes

The hash makes the time of get() to be O(1). The list of double linked nodes make the nodes adding/removal operations O(1).

 



class LRUCache {
class Node{
int key;
int value;
Node pre;
Node next;
public Node(int key, int value){
this.key = key;
this.value = value;
}
}


int capacity;
Map<Integer, Node> map = new HashMap<>();
Node head=null;
Node end=null;

public LRUCache(int capacity) {
this.capacity = capacity;
}

public int get(int key) {
if(map.containsKey(key)){
Node n = map.get(key);
remove(n);
setHead(n);
return n.value;
}
return -1;
}

public void remove(Node n){
if(n.pre != null){
n.pre.next = n.next;
}
else{
head = n.next;
}
if(n.next != null){
n.next.pre = n.pre;
}
else{
end = n.pre;
}
}
public void setHead(Node n){
n.next = head;
n.pre = null;

if(head != null){
head.pre = n;
}
head = n;
if(end == null){
end = head;
}
}

public void put(int key, int value) {
if(map.containsKey(key)){
Node oldNode = map.get(key);
oldNode.value = value;
remove(oldNode);
setHead(oldNode);
}
else{
Node newNode = new Node(key, value);
if(map.size() >= capacity){
map.remove(end.key);
remove(end);
setHead(newNode);
}
else{
setHead(newNode);
}
map.put(key, newNode);
}
}
}

/**
* 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);
*/


 



class LRUCache {

class Node {
int key;
int value;
Node pre;
Node next;
}

int capacity;
HashMap<Integer, Node> map;
Node head;
Node tail;

public LRUCache(int capacity) {
this.capacity = capacity;
this.map = new HashMap<Integer, Node>();
this.head = null;
this.tail = null;
}

public int get(int key) {
int v = -1;
if(this.map.containsKey(key)){

Node n = this.map.get(key);
//remove node from current position
remove(n);
//insert node to head of the list
addToHead(n);
v = n.value;
}
return v;
}

public void put(int key, int value) {
if(map.containsKey(key)){
Node n = map.get(key);
n.value = value;
remove(n);
addToHead(n);
}
else{
Node n = new Node();
n.key = key;
n.value = value;
if(this.map.size() == this.capacity){
//remove tail
map.remove(this.tail.key);
remove(this.tail);

}
//add new node to head
addToHead(n);
map.put(key, n);
}
}

public void remove(Node node){
if(node.pre != null){
node.pre.next = node.next;
}
else{
this.head = node.next;
}
if(node.next != null){
node.next.pre = node.pre;
}
else{
this.tail = node.pre;
}


}

public void addToHead(Node node){
node.pre = null;
node.next = this.head;
if(this.head != null){
this.head.pre = node;
}
this.head = node;
if(this.tail == null){
this.tail = 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);
*/