內存緩存LruCache實現原理

　　自己項目中一直都是用的開源的xUtils框架，包括BitmapUtils、DbUtils、ViewUtils和HttpUtils四大模塊，這四大模塊都是項目中比較常用的。最近決定研究一下xUtils的源碼，用了這么久總得知道它的實現原理吧。我是先從先從BitmapUtils模塊開始的。BitmapUtils和大多數圖片加載框架一樣，都是基於內存-文件-網絡三級緩存。也就是加載圖片的時候首先從內存緩存中取，如果沒有再從文件緩存中取，如果文件緩存沒有取到，就從網絡下載圖片並且加入內存和文件緩存。

　　這篇帖子先分析內存緩存是如何實現的。好吧開始進入正題。

　　BitmapUtils內存緩存的核心類LruMemoryCache，LruMemoryCache代碼和v4包的LruCache一樣，只是加了一個存儲超期的處理，這里分析LruCache源碼。LRU即Least Recently Used，近期最少使用算法。也就是當內存緩存達到設定的最大值時將內存緩存中近期最少使用的對象移除，有效的避免了OOM的出現。

 

        講到LruCache不得不提一下LinkedHashMap，因為LruCache中Lru算法的實現就是通過LinkedHashMap來實現的。LinkedHashMap繼承於HashMap，它使用了一個雙向鏈表來存儲Map中的Entry順序關系，這種順序有兩種，一種是LRU順序，一種是插入順序，這可以由其構造函數public LinkedHashMap(int initialCapacity,float loadFactor, boolean accessOrder)指定。所以，對於get、put、remove等操作，LinkedHashMap除了要做HashMap做的事情，還做些調整Entry順序鏈表的工作。LruCache中將LinkedHashMap的順序設置為LRU順序來實現LRU緩存，每次調用get(也就是從內存緩存中取圖片)，則將該對象移到鏈表的尾端。調用put插入新的對象也是存儲在鏈表尾端，這樣當內存緩存達到設定的最大值時，將鏈表頭部的對象（近期最少用到的）移除。關於LinkedHashMap詳解請前往http://www.cnblogs.com/children/archive/2012/10/02/2710624.html。

 

        下面看下LruCache的源碼，我都注釋的很詳細了。

/*
 * Copyright (C) 2011 The Android Open Source Project
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package android.support.v4.util;

import java.util.LinkedHashMap;
import java.util.Map;

/**
 * Static library version of {@link android.util.LruCache}. Used to write apps
 * that run on API levels prior to 12. When running on API level 12 or above,
 * this implementation is still used; it does not try to switch to the
 * framework's implementation. See the framework SDK documentation for a class
 * overview.
 */
public class LruCache<K, V> {
    private final LinkedHashMap<K, V> map;

    /** Size of this cache in units. Not necessarily the number of elements. */
    private int size;    //當前cache的大小
    private int maxSize; //cache最大大小

    private int putCount;       //put的次數
    private int createCount;    //create的次數
    private int evictionCount;  //回收的次數
    private int hitCount;       //命中的次數
    private int missCount;      //未命中次數

    /**
     * @param maxSize for caches that do not override {@link #sizeOf}, this is
     *     the maximum number of entries in the cache. For all other caches,
     *     this is the maximum sum of the sizes of the entries in this cache.
     */
    public LruCache(int maxSize) {
        if (maxSize <= 0) {
            throw new IllegalArgumentException("maxSize <= 0");
        }
        this.maxSize = maxSize;
        //將LinkedHashMap的accessOrder設置為true來實現LRU
        this.map = new LinkedHashMap<K, V>(0, 0.75f, true);  
    }

    /**
     * Returns the value for {@code key} if it exists in the cache or can be
     * created by {@code #create}. If a value was returned, it is moved to the
     * head of the queue. This returns null if a value is not cached and cannot
     * be created.
     * 通過key獲取相應的item，或者創建返回相應的item。相應的item會移動到隊列的尾部，
     * 如果item的value沒有被cache或者不能被創建，則返回null。
     */
    public final V get(K key) {
        if (key == null) {
            throw new NullPointerException("key == null");
        }

        V mapValue;
        synchronized (this) {
            mapValue = map.get(key);
            if (mapValue != null) {
                //mapValue不為空表示命中，hitCount+1並返回mapValue對象
                hitCount++;
                return mapValue;
            }
            missCount++;  //未命中
        }

        /*
         * Attempt to create a value. This may take a long time, and the map
         * may be different when create() returns. If a conflicting value was
         * added to the map while create() was working, we leave that value in
         * the map and release the created value.
         * 如果未命中，則試圖創建一個對象，這里create方法返回null,並沒有實現創建對象的方法
         * 如果需要事項創建對象的方法可以重寫create方法。因為圖片緩存時內存緩存沒有命中會去
         * 文件緩存中去取或者從網絡下載，所以並不需要創建。
         */
        V createdValue = create(key);
        if (createdValue == null) {
            return null;
        }
        //假如創建了新的對象，則繼續往下執行
        synchronized (this) {
            createCount++;  
            //將createdValue加入到map中，並且將原來鍵為key的對象保存到mapValue
            mapValue = map.put(key, createdValue);   
            if (mapValue != null) {
                // There was a conflict so undo that last put
                //如果mapValue不為空，則撤銷上一步的put操作。
                map.put(key, mapValue);
            } else {
                //加入新創建的對象之后需要重新計算size大小
                size += safeSizeOf(key, createdValue);
            }
        }

        if (mapValue != null) {
            entryRemoved(false, key, createdValue, mapValue);
            return mapValue;
        } else {
            //每次新加入對象都需要調用trimToSize方法看是否需要回收
            trimToSize(maxSize);
            return createdValue;
        }
    }

    /**
     * Caches {@code value} for {@code key}. The value is moved to the head of
     * the queue.
     *
     * @return the previous value mapped by {@code key}.
     */
    public final V put(K key, V value) {
        if (key == null || value == null) {
            throw new NullPointerException("key == null || value == null");
        }

        V previous;
        synchronized (this) {
            putCount++;
            size += safeSizeOf(key, value);  //size加上預put對象的大小
            previous = map.put(key, value);
            if (previous != null) {
                //如果之前存在鍵為key的對象，則size應該減去原來對象的大小
                size -= safeSizeOf(key, previous);
            }
        }

        if (previous != null) {
            entryRemoved(false, key, previous, value);
        }
        //每次新加入對象都需要調用trimToSize方法看是否需要回收
        trimToSize(maxSize);
        return previous;
    }

    /**
     * @param maxSize the maximum size of the cache before returning. May be -1
     *     to evict even 0-sized elements.
     * 此方法根據maxSize來調整內存cache的大小，如果maxSize傳入-1，則清空緩存中的所有對象
     */
    private void trimToSize(int maxSize) {
        while (true) {
            K key;
            V value;
            synchronized (this) {
                if (size < 0 || (map.isEmpty() && size != 0)) {
                    throw new IllegalStateException(getClass().getName()
                            + ".sizeOf() is reporting inconsistent results!");
                }
                //如果當前size小於maxSize或者map沒有任何對象,則結束循環
                if (size <= maxSize || map.isEmpty()) {
                    break;
                }
                //移除鏈表頭部的元素，並進入下一次循環
                Map.Entry<K, V> toEvict = map.entrySet().iterator().next();
                key = toEvict.getKey();
                value = toEvict.getValue();
                map.remove(key);
                size -= safeSizeOf(key, value);
                evictionCount++;  //回收次數+1
            }

            entryRemoved(true, key, value, null);
        }
    }

    /**
     * Removes the entry for {@code key} if it exists.
     *
     * @return the previous value mapped by {@code key}.
     * 從內存緩存中根據key值移除某個對象並返回該對象
     */
    public final V remove(K key) {
        if (key == null) {
            throw new NullPointerException("key == null");
        }

        V previous;
        synchronized (this) {
            previous = map.remove(key);
            if (previous != null) {
                size -= safeSizeOf(key, previous);
            }
        }

        if (previous != null) {
            entryRemoved(false, key, previous, null);
        }

        return previous;
    }

    /**
     * Called for entries that have been evicted or removed. This method is
     * invoked when a value is evicted to make space, removed by a call to
     * {@link #remove}, or replaced by a call to {@link #put}. The default
     * implementation does nothing.
     *
     * <p>The method is called without synchronization: other threads may
     * access the cache while this method is executing.
     *
     * @param evicted true if the entry is being removed to make space, false
     *     if the removal was caused by a {@link #put} or {@link #remove}.
     * @param newValue the new value for {@code key}, if it exists. If non-null,
     *     this removal was caused by a {@link #put}. Otherwise it was caused by
     *     an eviction or a {@link #remove}.
     */
    protected void entryRemoved(boolean evicted, K key, V oldValue, V newValue) {}

    /**
     * Called after a cache miss to compute a value for the corresponding key.
     * Returns the computed value or null if no value can be computed. The
     * default implementation returns null.
     *
     * <p>The method is called without synchronization: other threads may
     * access the cache while this method is executing.
     *
     * <p>If a value for {@code key} exists in the cache when this method
     * returns, the created value will be released with {@link #entryRemoved}
     * and discarded. This can occur when multiple threads request the same key
     * at the same time (causing multiple values to be created), or when one
     * thread calls {@link #put} while another is creating a value for the same
     * key.
     */
    protected V create(K key) {
        return null;
    }

    private int safeSizeOf(K key, V value) {
        int result = sizeOf(key, value);
        if (result < 0) {
            throw new IllegalStateException("Negative size: " + key + "=" + value);
        }
        return result;
    }

    /**
     * Returns the size of the entry for {@code key} and {@code value} in
     * user-defined units.  The default implementation returns 1 so that size
     * is the number of entries and max size is the maximum number of entries.
     *
     * <p>An entry's size must not change while it is in the cache.
     * 用來計算單個對象的大小，這里默認返回1，一般需要重寫該方法來計算對象的大小
     * xUtils中創建LruMemoryCache時就重寫了sizeOf方法來計算bitmap的大小
     * mMemoryCache = new LruMemoryCache<MemoryCacheKey, Bitmap>(globalConfig.getMemoryCacheSize()) {
     *       @Override
     *       protected int sizeOf(MemoryCacheKey key, Bitmap bitmap) {
     *           if (bitmap == null) return 0;
     *           return bitmap.getRowBytes() * bitmap.getHeight();
     *       }
     *   };
     *
     */
    protected int sizeOf(K key, V value) {
        return 1;
    }

    /**
     * Clear the cache, calling {@link #entryRemoved} on each removed entry.
     * 清空內存緩存
     */
    public final void evictAll() {
        trimToSize(-1); // -1 will evict 0-sized elements
    }

    /**
     * For caches that do not override {@link #sizeOf}, this returns the number
     * of entries in the cache. For all other caches, this returns the sum of
     * the sizes of the entries in this cache.
     */
    public synchronized final int size() {
        return size;
    }

    /**
     * For caches that do not override {@link #sizeOf}, this returns the maximum
     * number of entries in the cache. For all other caches, this returns the
     * maximum sum of the sizes of the entries in this cache.
     */
    public synchronized final int maxSize() {
        return maxSize;
    }

    /**
     * Returns the number of times {@link #get} returned a value.
     */
    public synchronized final int hitCount() {
        return hitCount;
    }

    /**
     * Returns the number of times {@link #get} returned null or required a new
     * value to be created.
     */
    public synchronized final int missCount() {
        return missCount;
    }

    /**
     * Returns the number of times {@link #create(Object)} returned a value.
     */
    public synchronized final int createCount() {
        return createCount;
    }

    /**
     * Returns the number of times {@link #put} was called.
     */
    public synchronized final int putCount() {
        return putCount;
    }

    /**
     * Returns the number of values that have been evicted.
     */
    public synchronized final int evictionCount() {
        return evictionCount;
    }

    /**
     * Returns a copy of the current contents of the cache, ordered from least
     * recently accessed to most recently accessed.
     */
    public synchronized final Map<K, V> snapshot() {
        return new LinkedHashMap<K, V>(map);
    }

    @Override public synchronized final String toString() {
        int accesses = hitCount + missCount;
        int hitPercent = accesses != 0 ? (100 * hitCount / accesses) : 0;
        return String.format("LruCache[maxSize=%d,hits=%d,misses=%d,hitRate=%d%%]",
                maxSize, hitCount, missCount, hitPercent);
    }
}

　　看完代碼是不是覺得內存緩存的實現其實很簡單？