146 LRU Cache

class LRUCache {
    
    class Node{
        int key;
        int value;
        Node prev;
        Node next;
        
        public Node(int key, int value){
            this.key = key;
            this.value = value;
        }
    }
    
    // initialize the data strcutures we need , global vars 
    HashMap<Integer, Node> map;
    int capacity, count;
    // for dll
    Node head, tail; // it's like dummy node, makes life easier 
    
    
    // constructor 
    public LRUCache(int capacity) {
      this.capacity = capacity;
      count = 0;
      map = new HashMap<>();
        
      // use a double linked list to maintain the freshness of the nodes (key, value)
      // every time, we call a node, if it still exists in the map, how to update the freshness of the node? remove the node from the dll, and add it to the head of the dll. 
    
     // so the map is used for quick get 
     // the double linked list is used to maintain which node is still fresh , 
     // the freshest is at the very begining 
      head = new Node(0, 0);
      tail = new Node(0, 0);
      // connect head and tail , double linked 
      head.next = tail;
      tail.prev = head;
      head.prev = null;
      tail.next = null;
    }
    
    public int get(int key) {
     // if the map contains Key, return the value , else , return -1, 
     // update the freshness 
        if(map.containsKey(key)){
            Node node = map.get(key);
            deleteNode(node);
            add(node);
            return node.value;
        }else{
            return -1;
        }
    }
    
    public void put(int key, int value) {
      // if the key already exists in the map, replace the value in the map, remove the key value from 
      // double linked list, and add it back to the head of the linked list 
        
      // else, add key value to the map, and add the key value pair to the head of the double linked list  
        // after that, we need to count the size, if within capacity, do nothing, else , remove the 
        // the last node, which is also the oldest node from the map and the double linked list 
        if(map.containsKey(key)){
            Node node = map.get(key);
            node.value = value;
            deleteNode(node);
            add(node);
        }else{
            Node node = new Node(key, value);
            map.put(key, node);
            add(node);
            count++;
            
            // check if the size exceeds the capacity
            if(count > capacity){
                Node old = tail.prev;
                map.remove(old.key);
                deleteNode(old);
                count--;
            }
        }
    }
    
    // helper functions that make life easier 
    // used in many places in this class
    private void add(Node node){
        // always add to the front 
        Node recent = head.next;
        head.next = node;
        node.next = recent;
        node.prev = head;
        recent.prev = node;
        
    }
    private void deleteNode(Node node){
        // this is why we use double linked list
        // so that we can use the previous pointer 
        Node prev = node.prev;
        Node next = node.next;
        prev.next = next;
        next.prev = prev;
        
    }
}

这个题的 node class, constructor, global vars , 怎么写 该注意

 

几点该注意的： 

use helper functions, add, and deleteNode,  add : add node to the front,   deleteNode: deleteNode any node 

put(key, value) function: first check if the key exists, if not, put and check if the size if out of capacity 

get(key) : return the value if exists in the map, and update freshness of the node by removing first and add in the double linked list 

用 head, tail dummy node， 

在 hashmap 里， <integer, node>

 

  class Node{
        int key;
        int value;
        Node prev;
        Node next;
        
        public Node(int key, int value){
            this.key = key;
            this.value = value;

 

 

 

 

 // initialize the data strcutures we need , global vars 
    HashMap<Integer, Node> map;
    int capacity, count;
    // for dll
    Node head, tail; // it's like dummy node, makes life easier 
    
    
    // constructor 
    public LRUCache(int capacity) {
      this.capacity = capacity;
      count = 0;
      map = new HashMap<>();
        
      // use a double linked list to maintain the freshness of the nodes (key, value)
      // every time, we call a node, if it still exists in the map, how to update the freshness of the node? remove the node from the dll, and add it to the head of the dll. 
    
     // so the map is used for quick get 
     // the double linked list is used to maintain which node is still fresh , 
     // the freshest is at the very begining 
      head = new Node(0, 0);
      tail = new Node(0, 0);
      // connect head and tail , double linked 
      head.next = tail;
      tail.prev = head;
      head.prev = null;
      tail.next = null;
    }
    

 

 

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