the best way to implement LRU cache

Andrey Yaskulsky picture Andrey Yaskulsky · Apr 11, 2013 · Viewed 8.5k times · Source

I want to create an efficient implementation of LRU cache. I've found that the most convenient way is to use LinkedHashMap but unfortunately it's quite slow if many threads are using a cache. My implementation is here:

/**
 * Class provides API for FixedSizeCache.
 * Its inheritors represent classes         
 * with concrete strategies     
 * for choosing elements to delete
 * in case of cache overflow. All inheritors
 * must implement {@link #getSize(K, V)}. 
 */
public abstract class FixedSizeCache <K, V> implements ICache <K, V> {
    /**
     * Current cache size.
     */
    private int currentSize;


    /**
     *  Maximum allowable cache size.
     */
    private int maxSize;


    /**
     * Number of {@link #get(K)} queries for which appropriate {@code value} was found.
     */
    private int keysFound;


    /**
     * Number of {@link #get(K)} queries for which appropriate {@code value} was not found.
     */
    private int keysMissed;


    /** 
     * Number {@code key-value} associations that were deleted from cache
     * because of cash overflow.
     */
    private int erasedCount; 


    /**
     * Basic data structure LinkedHashMap provides
     * convenient way for designing both types of cache:
     * LRU and FIFO. Depending on its constructor parameters
     * it can represent either of FIFO or LRU HashMap.
     */
    private LinkedHashMap <K, V> entries;


    /** 
     * If {@code type} variable equals {@code true}
     * then LinkedHashMap will represent LRU HashMap.
     * And it will represent FIFO HashMap otherwise.
     */ 
    public FixedSizeCache(int maxSize, boolean type) {

        if (maxSize <= 0) {
            throw new IllegalArgumentException("int maxSize parameter must be greater than 0");
        }

        this.maxSize = maxSize;
        this.entries = new LinkedHashMap<K, V> (0, 0.75f, type);
    }


    /** 
     * Method deletes {@code key-value} associations 
     * until current cache size {@link #currentSize} will become 
     * less than or equal to maximum allowable
     * cache size {@link #maxSize}
     */
    private void relaxSize()  {

        while (currentSize > maxSize) {

             // The strategy for choosing entry with the lowest precedence
             // depends on {@code type} variable that was used to create  {@link #entries} variable. 
             // If it was created with constructor LinkedHashMap(int size,double loadfactor, boolean type)
             // with {@code type} equaled to {@code true} then variable {@link #entries} represents
             // LRU LinkedHashMap and iterator of its entrySet will return elements in order
             // from least recently used to the most recently used.
             // Otherwise, if {@code type} equaled to {@code false} then {@link #entries} represents
             // FIFO LinkedHashMap and iterator will return its entrySet elements in FIFO order -
             // from oldest in the cache to the most recently added.

            Map.Entry <K, V> entryToDelete = entries.entrySet().iterator().next();

            if (entryToDelete == null) {
                throw new IllegalStateException(" Implemented method int getSize(K key, V value) " +
                        " returns different results for the same arguments.");  
            }

            entries.remove(entryToDelete.getKey());
            currentSize -= getAssociationSize(entryToDelete.getKey(), entryToDelete.getValue());
            erasedCount++;
        }

        if (currentSize < 0) {
            throw new IllegalStateException(" Implemented method int getSize(K key, V value) " +
                    " returns different results for the same arguments.");
        }
    }


    /** 
     * All inheritors must implement this method
     * which evaluates the weight of key-value association.
     * Sum of weights of all key-value association in the cache
     * equals to {@link #currentSize}.  
     * But developer must ensure that
     * implementation will satisfy two conditions:
     * <br>1) method always returns non negative integers;
     * <br>2) for every two pairs {@code key-value} and {@code key_1-value_1}
     * if {@code key.equals(key_1)} and {@code value.equals(value_1)} then 
     * {@code getSize(key, value)==getSize(key_1, value_1)};
     * <br> Otherwise cache can work incorrectly.
     */
    protected abstract int getSize(K key, V value);


    /** 
     * Helps to detect if the implementation of {@link #getSize(K, V)} method
     * can return negative values. 
     */
    private int getAssociationSize(K key, V value)  {

        int entrySize = getSize(key, value);

        if (entrySize < 0 ) {
            throw new IllegalStateException("int getSize(K key, V value) method implementation is invalid. It returned negative value.");
        }

        return entrySize;
    }


   /**
    * Returns the {@code value} corresponding to {@code key} or
    * {@code null} if  {@code key} is not present in the cache. 
    * Increases {@link #keysFound} if finds a corresponding {@code value}
    * or increases {@link #keysMissed} otherwise. 
    */
    public synchronized final V get(K key)  {

        if (key == null) {
            throw new NullPointerException("K key is null");
        }

        V value = entries.get(key);
        if (value != null) {
            keysFound++;
            return value;
        }

        keysMissed++;
        return value;
    }


    /** 
     * Removes the {@code key-value} association, if any, with the
    *  given {@code key}; returns the {@code value} with which it
    *  was associated, or {@code null}.
    */
    public synchronized final V remove(K key)  {

        if (key == null) {
            throw new NullPointerException("K key is null");
        }

        V value = entries.remove(key);

        // if appropriate value was present in the cache than decrease
        // current size of cache

        if (value != null) {
            currentSize -= getAssociationSize(key, value);
        }

        return value;
    }


   /**
    * Adds or replaces a {@code key-value} association.
    * Returns the old {@code value} if the
    * {@code key} was present; otherwise returns {@code null}.
    * If after insertion of a {@code key-value} association 
    * to cache its size becomes greater than
    * maximum allowable cache size then it calls {@link #relaxSize()} method which
    * releases needed free space. 
    */
    public synchronized final V put(K key, V value)  {

        if (key == null || value == null) {
            throw new NullPointerException("K key is null or V value is null");
        }

        currentSize += getAssociationSize(key, value);      
        value = entries.put(key, value);

        // if key was not present then decrease cache size

        if (value != null) {
            currentSize -= getAssociationSize(key, value);
        }

        // if cache size with new entry is greater
        // than maximum allowable cache size
        // then get some free space

        if (currentSize > maxSize) {
            relaxSize();
        }

        return value;
    }


    /**
     * Returns current size of cache. 
     */
    public synchronized int currentSize() {
        return currentSize;
    }


    /** 
     * Returns maximum allowable cache size. 
     */ 
    public synchronized int maxSize() {
        return maxSize;
    }


    /** 
     * Returns number of {@code key-value} associations that were deleted
     * because of cache overflow.   
     */
    public synchronized int erasedCount() {
        return erasedCount;
    }


    /** 
     * Number of {@link #get(K)} queries for which appropriate {@code value} was found.
     */
    public synchronized int keysFoundCount() {
        return keysFound;
    }


    /** 
     * Number of {@link #get(K)} queries for which appropriate {@code value} was not found.
     */
    public synchronized int keysMissedCount() {
        return keysMissed;
    }


    /**
     * Removes all {@code key-value} associations
     * from the cache. And turns {@link #currentSize},
     * {@link #keysFound}, {@link #keysMissed} to {@code zero}.  
     */
    public synchronized void clear() {
        entries.clear();
        currentSize = 0;
        keysMissed = 0;
        keysFound = 0;
        erasedCount = 0;
    }


    /**
     * Returns a copy of {@link #entries}
     * that has the same content.
     */
    public synchronized LinkedHashMap<K, V> getCopy() {
        return new LinkedHashMap<K, V> (entries);
    }
}

This implementation is quite slow (because of synchronization) if we have many threads are trying to call lets say get() method. Is there a better way?

Answer

Zim-Zam O&#39;Pootertoot picture Zim-Zam O'Pootertoot · Apr 11, 2013

I don't know if this is beneficial, but if you can replace your LinkedHashMap with a ConcurrentHashMap then you'll improve your throughput - a ConcurrentHashMap uses sharding to permit multiple simultaneous readers and writers. It is also thread-safe, so you won't need to synchronize your readers and writers.

Barring that, replace your use of the synchronized keyword with a ReadWriteLock. This will allow multiple simultaneous readers.