LRU算法 java实现

最简单的LRU算法实现，就是利用Java的LinkedHashMap，覆写其中的removeEldestEntry(Map.Entry)

 

import java.util.ArrayList;
import java.util.Collection;
import java.util.LinkedHashMap;
import java.util.concurrent.locks.Lock;
import java.util.concurrent.locks.ReentrantLock;
import java.util.Map;

/**
 * 类说明：利用LinkedHashMap实现简单的缓存， 必须实现removeEldestEntry方法，具体参见JDK文档
 * 
 * 
 * @param
 * @param
 */
public class LRULinkedHashMap<K, V> extends LinkedHashMap<K, V> {
	/**
	 * 
	 */
	private static final long serialVersionUID = -2960999970549803724L;

	private final int maxCapacity;

	private static final float DEFAULT_LOAD_FACTOR = 0.75f;

	private final Lock lock = new ReentrantLock();

	public LRULinkedHashMap(int maxCapacity) {
		super(maxCapacity, DEFAULT_LOAD_FACTOR, true);
		this.maxCapacity = maxCapacity;
	}

	@Override
	protected boolean removeEldestEntry(Map.Entry<K, V> eldest) {
		return size() > maxCapacity;
	}

	@Override
	public boolean containsKey(Object key) {
		try {
			lock.lock();
			return super.containsKey(key);
		} finally {
			lock.unlock();
		}
	}

	@Override
	public V get(Object key) {
		try {
			lock.lock();
			return super.get(key);
		} finally {
			lock.unlock();
		}
	}

	@Override
	public V put(K key, V value) {
		try {
			lock.lock();
			return super.put(key, value);
		} finally {
			lock.unlock();
		}
	}

	public int size() {
		try {
			lock.lock();
			return super.size();
		} finally {
			lock.unlock();
		}
	}

	public void clear() {
		try {
			lock.lock();
			super.clear();
		} finally {
			lock.unlock();
		}
	}

	public Collection<Map.Entry<K, V>> getAll() {
		try {
			lock.lock();
			return new ArrayList<Map.Entry<K, V>>(super.entrySet());
		} finally {
			lock.unlock();
		}
	}
}

 

如果你去看LinkedHashMap的源码可知，LRU算法是通过双向链表来实现，当某个位置被命中，通过调整链表的指向将该位置调整到头位置，新加入的内容直接放在链表头，如此一来，最近被命中的内容就向链表头移动，需要替换时，链表最后的位置就是最近最少使用的位置。

    LRU算法还可以通过计数来实现，缓存存储的位置附带一个计数器，当命中时将计数器加1，替换时就查找计数最小的位置并替换，结合访问时间戳来实现。这种算法比较适合缓存数据量较小的场景，显然，遍历查找计数最小位置的时间复杂度为O(n)。我实现了一个，结合了访问时间戳，当最小计数大于MINI_ACESS时(这个参数的调整对命中率有较大影响），就移除最久没有被访问的项：

 

import java.io.Serializable;
import java.util.ArrayList;
import java.util.Collection;
import java.util.HashMap;
import java.util.Iterator;
import java.util.Map;
import java.util.Map.Entry;
import java.util.Set;
import java.util.concurrent.atomic.AtomicLong;
import java.util.concurrent.locks.Lock;
import java.util.concurrent.locks.ReadWriteLock;
import java.util.concurrent.locks.ReentrantReadWriteLock;

/**
 * 
 * 类说明：当缓存数目不多时，才用缓存计数的传统LRU算法
 * 
 * @param
 * @param
 */
public class LRUCache<K, V> implements Serializable {

    /**
	 * 
	 */
	private static final long serialVersionUID = 2727577376847051556L;

	private static final int DEFAULT_CAPACITY = 100;

	protected Map<K, ValueEntry> map;

	private final ReadWriteLock lock = new ReentrantReadWriteLock();

	private final Lock readLock = lock.readLock();

	private final Lock writeLock = lock.writeLock();

	private volatile int maxCapacity; // 保持可见性

	public static int MINI_ACCESS = 5;

	public LRUCache() {
		this(DEFAULT_CAPACITY);
	}

	public LRUCache(int capacity) {
		if (capacity <= 0)
			throw new RuntimeException("缓存容量不得小于0");
		this.maxCapacity = capacity;
		this.map = new HashMap<K, ValueEntry>(maxCapacity);
	}

	public boolean ContainsKey(K key) {
		try {
			readLock.lock();
			return this.map.containsKey(key);
		} finally {
			readLock.unlock();
		}
	}

	public V put(K key, V value) {
		try {
			writeLock.lock();
			if ((map.size() > maxCapacity - 1) && !map.containsKey(key)) {
				// System.out.println("开始");
				Set<Entry<K, ValueEntry>> entries = this.map.entrySet();
				removeRencentlyLeastAccess(entries);
			}
			ValueEntry new_value = new ValueEntry(value);
			ValueEntry old_value = map.put(key, new_value);
			if (old_value != null) {
				new_value.count = old_value.count;
				return old_value.value;
			} else
				return null;
		} finally {
			writeLock.unlock();
		}
	}

    /**
     * 移除最近最少访问
     */
	protected V removeRencentlyLeastAccess(Set<Map.Entry<K, ValueEntry>> entries) {
		// 最小使用次数
		long least = 0;
		// 访问时间最早
		long earliest = 0;
		K toBeRemovedByCount = null;
		K toBeRemovedByTime = null;
		Iterator<Map.Entry<K, ValueEntry>> it = entries.iterator();
		if (it.hasNext()) {
			Map.Entry<K, ValueEntry> valueEntry = it.next();
			least = valueEntry.getValue().count.get();
			toBeRemovedByCount = valueEntry.getKey();
			earliest = valueEntry.getValue().lastAccess.get();
			toBeRemovedByTime = valueEntry.getKey();
		}
		while (it.hasNext()) {
			Map.Entry<K, ValueEntry> valueEntry = it.next();
			if (valueEntry.getValue().count.get() < least) {
				least = valueEntry.getValue().count.get();
				toBeRemovedByCount = valueEntry.getKey();
			}
			if (valueEntry.getValue().lastAccess.get() < earliest) {
				earliest = valueEntry.getValue().count.get();
				toBeRemovedByTime = valueEntry.getKey();
			}
		}
		// System.out.println("remove:" + toBeRemoved);
		// 如果最少使用次数大于MINI_ACCESS，那么移除访问时间最早的项(也就是最久没有被访问的项）
		if (least > MINI_ACCESS) {
			return map.remove(toBeRemovedByTime).value;
		} else {
			return map.remove(toBeRemovedByCount).value;
		}
	}

	public V get(K key) {
		try {
			readLock.lock();
			V value = null;
			ValueEntry valueEntry = map.get(key);
			if (valueEntry != null) {
				// 更新访问时间戳
				valueEntry.updateLastAccess();
				// 更新访问次数
				valueEntry.count.incrementAndGet();
				value = valueEntry.value;
			}
			return value;
		} finally {
			readLock.unlock();
		}
	}

	public void clear() {
		try {
			writeLock.lock();
			map.clear();
		} finally {
			writeLock.unlock();
		}
	}

	public int size() {
		try {
			readLock.lock();
			return map.size();
		} finally {
			readLock.unlock();
		}
	}

	public long getCount(K key) {
		try {
			readLock.lock();
			ValueEntry valueEntry = map.get(key);
			if (valueEntry != null) {
				return valueEntry.count.get();
			}
			return 0;
		} finally {
			readLock.unlock();
		}
	}

	public Collection<Entry<K, V>> getAll() {
		try {
			readLock.lock();
			Set<K> keys = map.keySet();
			Map<K, V> tmp = new HashMap<K, V>();
			for (K key : keys) {
				tmp.put(key, map.get(key).value);
			}
			return new ArrayList<Entry<K, V>>(tmp.entrySet());
		} finally {
			readLock.unlock();
		}
	}

	class ValueEntry implements Serializable {

		/**
		 * 
		 */
		private static final long serialVersionUID = -7626403101359191860L;

		private V value;

		private AtomicLong count;

		private AtomicLong lastAccess;

		public ValueEntry(V value) {
			this.value = value;
			this.count = new AtomicLong(0);
			lastAccess = new AtomicLong(System.nanoTime());
		}

		public void updateLastAccess() {
			this.lastAccess.set(System.nanoTime());
		}

	}
}

 

 

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