top button
Flag Notify
    Connect to us
      Site Registration

Site Registration

How to write LRU cache in Java using Generics?

+2 votes
756 views
How to write LRU cache in Java using Generics?
posted Oct 12, 2016 by Sahana

Share this question
Facebook Share Button Twitter Share Button LinkedIn Share Button

1 Answer

0 votes
 
Best answer

/* This is an efficient implementation of a fixed size cache using Java generics.
* It uses a least recently used eviction policy implemented via a combination hashtable/linked list data structure.

*/

import java.util.HashMap;
import java.util.Random;

public class Cache<KeyType, RecordType>{

    // Example usage of generic cache.
    public static void main(String args[]){
        //Initialize integer to String cache with maximum size of 500.
        Cache<Integer, String> cache = new Cache<Integer, String>(500);
        int hits = 0, misses = 0;
        for(int k=0;k<100000;k++){
            // Caches perform well in uneven key distributions.
            float power = 1 ;
            for(int j=0;j<5;j++){
                power*=Math.random();
            }
            int key = (int)(power*10000); // Keys up to 9999 but more common in lower numbers.
            // Try to fetch key from cache.
            String value = cache.get(key);
            if(value == null){
                // If it wasn't in the cache then do the full operation and cache it.
                value = expensiveDeterministicOperation(key);
                cache.put(key, value);
                misses++;
            }else{
                hits++;
            }
        }

        System.out.println(cache); // Print out the keys in the cache
        System.out.println("Hits:" + hits +"   Misses:" + misses);
    }
    // An expensive but deterministic operation such as retrieving a file from a remote server.
    public static String expensiveDeterministicOperation(Integer i){
        Random r = new Random(i);
        String s = "";
        for(int k=0;k<50;k++){
            s+= (char)(r.nextInt(26) + (int)'a');
        }
        return s ;
    }
//------------Generic Cache Implementation Begins Here ---------
    // Hash table to fetch records for keys. 
    // CacheValue includes record and pointer to queue position.
    HashMap<KeyType,CacheValue> table; 
    // Doubly linked queue to keep track of least recently used item.
    QueueNode head, tail; 

    // Allowed capacity of cache and how much is already full.
    int capacity, filled = 0 ;

    public Cache(int size) {  
        capacity = size;
        table = new HashMap<KeyType,CacheValue>(2*size); // Double table size reduces hash collisions.
    }

    //Nodes for queue keeping track of item access order.
    private class QueueNode{
        QueueNode next ;
        QueueNode previous ;
        KeyType key;

        public QueueNode(KeyType k){
            key = k ;
        }

        void removeFromQueue(){
            if(this==head)head = next;
            if(this==tail)tail = previous;
            if(previous!=null)previous.next = next;
            if(next!=null)next.previous = previous;
            next = null;
            previous = null;
        }

        void removeFromTable(){
            table.remove(key);
        }
    }
    // Groups a queue node and a record, so they can be fetched from the hash table together.
    private class CacheValue{
        public CacheValue(RecordType r){
            record = r ;
        }
        QueueNode node;
        RecordType record;
    }

    // Fetch a Record from the cache or null if it is not present.
    // Keeps track of accesses for future evictions.
    public RecordType get(KeyType k){
        CacheValue c = table.get(k);
        if(c == null)return null;
        // If found move to head of queue.
        QueueNode n = c.node;
        n.removeFromQueue();
        n.next = head;
        if(head!=null)head.previous = n;
        head = n;
        return c.record;
    }

    // Puts a record in the cache. Replaces record with matching key if found.
    // If cache is full evicts least recently accessed item.
    public void put(KeyType k, RecordType r){
        //If item is in the cache just update its value.
        CacheValue d = table.get(k);
        if(d!=null){ 
            d.record = r;
        }else{
            // If not in the cache then add it.
            CacheValue c = new CacheValue(r);
            QueueNode n = new QueueNode(k);
            c.node = n;
            table.put(k,c);
            // Put the item at the head of the queue.
            n.next = head;
            if(head!=null)head.previous = n;
            head = n;
            // First item in queue is also the tail
            if(tail==null)tail = head; 
            filled++;
            //If the cache is full remove the item at the tail of the queue.
            if(filled > capacity){
                QueueNode t = tail.previous;
                tail.removeFromTable();
                tail.removeFromQueue();
                tail = t;
                filled--;
            }
        }
    }
    // Prints the keys for the items currently in the cache.
    public String toString(){
        QueueNode node = head;
        String s = "Keys:" + node.key;
        while(node != tail){
            node = node.next;
            if(node==null){
                break;
            }
            s+=", " + node.key;
        }
        return s ;
    }
}
answer Oct 17, 2016 by Karthick.c
Similar Questions
+9 votes

how we can build LRU cache in java using concurrent package??
Can anyone give some code.

+3 votes

How can we implement an LRU cache using just a single container i.e. map or unordered_map?

Expected operations:
1. find(key_t) - find a certain value in cache
2. insert(key_t, value_t) - insert a new value to the cache

...