android源码解析之（七）-->LruCache
android开发过程中经常会用到缓存，现在主流的app中图片等资源的缓存策略一般是分两级，一个是内存级别的缓存，一个是磁盘级别的缓存。
作为android系统的维护者google也开源了其缓存方案，LruCache和DiskLruCache。从android3.1开始LruCache已经作为android源码的一部分维护在android系统中，为了兼容以前的版本android的support-v4包也提供了LruCache的维护，如果App需要兼容到android3.1之前的版本就需要使用support-v4包中的LruCache，如果不需要兼容到android3.1则直接使用android源码中的LruCache即可，这里需要注意的是DiskLruCache并不是android源码的一部分。
在LruCache的源码中，关于LruCache有这样的一段介绍：
A cache that holds strong references to a limited number of values. Each time a value is accessed, it is moved to the head of a queue. When a value is added to a full cache, the value at the end of that queue is evicted and may become eligible for garbage collection.cache对象通过一个强引用来访问内容。每次当一个item被访问到的时候，这个item就会被移动到一个队列的队首。当一个item被添加到已经满了的队列时，这个队列的队尾的item就会被移除。
其实这个实现的过程就是LruCache的缓存策略，即Lru–>(Least recent used)最少最近使用算法。
下面我们具体看一下LruCache的实现：
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;
private int maxSize;
private int putCount;
private int createCount;
private int evictionCount;
private int hitCount;
private int missCount;
/** * @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;
this.map = new LinkedHashMap<K, V>(0, 0.75f, true);
}
/** * Sets the size of the cache. * * @param maxSize The new maximum size. */
public void resize(int maxSize) {
if (maxSize <= 0) {
throw new IllegalArgumentException("maxSize <= 0");
}
synchronized (this) {
this.maxSize = maxSize;
}
trimToSize(maxSize);
}
/** * 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. */
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) {
hitCount++;
return mapValue;
}
missCount++;
}
/* * 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. */
V createdValue = create(key);
if (createdValue == null) {
return null;
}
synchronized (this) {
createCount++;
mapValue = map.put(key, createdValue);
if (mapValue != null) {
// There was a conflict so undo that last put
map.put(key, mapValue);
} else {
size += safeSizeOf(key, createdValue);
}
}
if (mapValue != null) {
entryRemoved(false, key, createdValue, mapValue);
return mapValue;
} else {
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);
previous = map.put(key, value);
if (previous != null) {
size -= safeSizeOf(key, previous);
}
}
if (previous != null) {
entryRemoved(false, key, previous, value);
}
trimToSize(maxSize);
return previous;
}
/** * Remove the eldest entries until the total of remaining entries is at or * below the requested size. * * @param maxSize the maximum size of the cache before returning. May be -1 * to evict even 0-sized elements. */
public 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!");
}
if (size <= maxSize) {
break;
}
Map.Entry<K, V> toEvict = map.eldest();
if (toEvict == null) {
break;
}
key = toEvict.getKey();
value = toEvict.getValue();
map.remove(key);
size -= safeSizeOf(key, value);
evictionCount++;
}
entryRemoved(true, key, value, null);
}
}
/** * Removes the entry for {@code key} if it exists. * * @return the previous value mapped by {@code key}. */
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. */
protected int sizeOf(K key, V value) {
return 1;
}
/** * Clear the cache, calling {@link #entryRemoved} on each removed entry. */
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 that was * already present in the cache. */
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);
}
}可以看到LruCache初始化的时候需要使用泛型，一般的我们这样初始化LruCache对象：
// 获取应用程序最大可用内存
int maxMemory = (int) Runtime.getRuntime().maxMemory();
int cacheSize = maxMemory / 8;
// 设置图片缓存大小为程序最大可用内存的1/8
mMemoryCache = new LruCache<String, Bitmap>(cacheSize) {
@Override
protected int sizeOf(String key, Bitmap bitmap) {
return bitmap.getByteCount();
}
}; 这里我们假设通过String作为key保存bitmap对象，同时需要传递一个int型的maxSize数值，主要用于设置LruCache链表的最大值。
查看其构造方法：
// 获取应用程序最大可用内存
int maxMemory = (int) Runtime.getRuntime().maxMemory();
int cacheSize = maxMemory / 8;
// 设置图片缓存大小为程序最大可用内存的1/8
mMemoryCache = new LruCache<String, Bitmap>(cacheSize) {
@Override
protected int sizeOf(String key, Bitmap bitmap) {
return bitmap.getByteCount();
}
}; 可以看到其主要的是初始化了maxSize和map链表对象。
然后查看put方法：
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);
previous = map.put(key, value);
if (previous != null) {
size -= safeSizeOf(key, previous);
}
}
if (previous != null) {
entryRemoved(false, key, previous, value);
}
trimToSize(maxSize);
return previous;
}需要传递两个参数：K和V，首先做了一下参数的判断，然后定义一个保存前一个Value值得临时变量，让putCount（put执行的次数）自增，让map的size大小自增。
需要注意的是这里的
previous = map.put(key, value);我们看一下这里的map.put（）的具体实现：
@Override public V put(K key, V value) {
if (key == null) {
return putValueForNullKey(value);
}
int hash = Collections.secondaryHash(key);
HashMapEntry<K, V>[] tab = table;
int index = hash & (tab.length - 1);
for (HashMapEntry<K, V> e = tab[index]; e != null; e = e.next) {
if (e.hash == hash && key.equals(e.key)) {
preModify(e);
V oldValue = e.value;
e.value = value;
return oldValue;
}
}
// No entry for (non-null) key is present; create one
modCount++;
if (size++ > threshold) {
tab = doubleCapacity();
index = hash & (tab.length - 1);
}
addNewEntry(key, value, hash, index);
return null;
}将Key与Value的值压入Map中，这里判断了一下如果map中已经存在该key，value键值对，则不再压入map，并将Value值返回，否则将该键值对压入Map中，并返回null；
返回继续put方法：
previous = map.put(key, value);
if (previous != null) {
size -= safeSizeOf(key, previous);
}可以看到这里我们判断map.put方法的返回值是否为空，如果不为空的话，则说明我们刚刚并没有将我么你的键值对压入Map中，所以这里的size需要自减；
然后下面：
if (previous != null) {
entryRemoved(false, key, previous, value);
}这里判断previous是否为空，如果不为空的话，调用了一个空的实现方法entryRemoved()，也就是说我们可以实现自己的LruCache并在添加缓存的时候若存在该缓存可以重写这个方法；
下面调用了trimToSize(maxSize)方法：
public 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!");
}
if (size <= maxSize) {
break;
}
Map.Entry<K, V> toEvict = map.eldest();
if (toEvict == null) {
break;
}
key = toEvict.getKey();
value = toEvict.getValue();
map.remove(key);
size -= safeSizeOf(key, value);
evictionCount++;
}
entryRemoved(true, key, value, null);
}
}该方法主要是判断该Map的大小是否已经达到阙值，若达到，则将Map队尾的元素（最不常使用的元素）remove掉。
总结：
LruCache put方法，将键值对压入Map数据结构中，若这是Map的大小已经大于LruCache中定义的最大值，则将Map中最早压入的元素remove掉；
查看get方法：
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) {
hitCount++;
return mapValue;
}
missCount++;
}
/* * 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. */
V createdValue = create(key);
if (createdValue == null) {
return null;
}
synchronized (this) {
createCount++;
mapValue = map.put(key, createdValue);
if (mapValue != null) {
// There was a conflict so undo that last put
map.put(key, mapValue);
} else {
size += safeSizeOf(key, createdValue);
}
}
if (mapValue != null) {
entryRemoved(false, key, createdValue, mapValue);
return mapValue;
} else {
trimToSize(maxSize);
return createdValue;
}
}可以看到参数值为Key，简单的理解就是通过key值从map中取出Value值。
具体来说，判断map中是否含有key值value值，若存在，则hitCount（击中元素数量）自增，并返回Value值，若没有击中，则执行create(key)方法，这里看到create方法是一个空的实现方法，返回值为null，所以我们可以重写该方法，在调用get（key）的时候若没有找到value值，则自动创建一个value值并压入map中。
总结：
LruCache，内部使用Map保存内存级别的缓存
LruCache使用泛型可以设配各种类型
LruCache使用了Lru算法保存数据（最短最少使用least recent use）
LruCache只用使用put和get方法压入数据和取出数据