How to Implement a ConcurrentLRUCache

Although there are several third party cache available in Java such as enCache, soCache, Guava library - It's actually easy and important to know how to write a custom LRUCache (last recently used cache).
Simply put a cache is data loaded in to memory identified by a 'key'.
A ConcurrentLRUCache is essentially backed up by a ConcurrentHashMap and controlled by a ConcurrentLinkedQueue.

So let's see the sample code -

public class ConcurrentLRUCache<Key, Value> {
      private final int maxSize;
      private ConcurrentHashMap map<key, value>;
      private ConcurrentLinkedQueue queue<key>,

     public ConcurrentLRUCache(int maxSize) {
          //Set the size of map
          this.maxSize = maxSize;
          map = new ConcurrentHashMap<key, value>(maxSize);
          queue = new ConcurrentLinkedQueue();
    }

    public put(final Key key, final Value value) {
       //If map already contains the key, you want to reinsert a new value for existing item, then remove the item from queue to maintain FIFO order (the key gets added to queue in the end of the method
        if(map.containsKey(key) {
           queue.remove(key);
       }

       //If the Size of queue is full, remove the first element added from map and queue
       if(queue.size >= maxSize) {
          //Retrieves the oldest element added and removes it from queue
           key oldestKey = queue.poll;
           if(oldestKey != null) {
              //Remove oldest element added to the map
              map.remove(oldestKey);
          }    
       }

       //Add value to map and queue
       queue.put(key);
       map.add(key, value);
    }
   
    public get(final Key key) {
        return map.get(key);
    }
}







}