转载请标明出处：一片枫叶的专栏
android开发过程中常常会用到缓存。如今主流的app中图片等资源的缓存策略通常是分两级。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開始LruCache已经作为android源代码的一部分维护在android系统中。为了兼容曾经的版本号android的support-v4包也提供了LruCache的维护，假设App须要兼容到android3.1之前的版本号就须要使用support-v4包中的LruCache，假设不须要兼容到android3.1则直接使用android源代码中的LruCache就可以，这里须要注意的是DiskLruCache并非android源代码的一部分。
在LruCache的源代码中。关于LruCache有这种一段介绍：
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訪问内容。每次当一个item被訪问到的时候，这个item就会被移动到一个队列的队首。当一个item被加入到已经满了的队列时，这个队列的队尾的item就会被移除。
事实上这个实现的过程就是LruCache的缓存策略。即Lru–>(Least recent used)最少近期使用算法。
以下我们详细看一下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);
}
}能够看到LruCache初始化的时候须要使用泛型，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，同一时候须要传递一个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();
}
}; 能够看到其基本的是初始化了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;
}须要传递两个參数：K和V，首先做了一下參数的推断，然后定义一个保存前一个Value值得暂时变量。让putCount（put运行的次数）自增，让map的size大小自增。
须要注意的是这里的
previous = map.put(key, value);我们看一下这里的map.put（）的详细实现：
@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，这里推断了一下假设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);
}能够看到这里我们推断map.put方法的返回值是否为空。假设不为空的话，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须要自减；
然后以下：
if (previous != null) {
entryRemoved(false, key, previous, value);
}这里推断previous是否为空，假设不为空的话，调用了一个空的实现方法entryRemoved()，也就是说我们能够实现自己的LruCache并在加入缓存的时候若存在该缓存能够重写这种方法；
以下调用了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);
}
}该方法主要是推断该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;
}
}能够看到參数值为Key。简单的理解就是通过key值从map中取出Value值。
详细来说，推断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，则运行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。所以我们能够重写该方法，在调用get（key）的时候若没有找到value值，则自己主动创建一个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使用泛型能够设配各种类型
LruCache使用了Lru算法保存数据（最短最少使用least recent use）
LruCache仅仅用使用put和get方法压入数据和取出数据
另外对android源代码解析方法感兴趣的可參考我的：
android源代码解析之（一）–>android项目构建过程
android源代码解析之（二）–>异步消息机制
android源代码解析之（三）–>异步任务AsyncTask
android源代码解析之（四）–>HandlerThread
android源代码解析之（五）–>IntentService
android源代码解析之（六）–>Log
本文以同步至github中：https://github.com/yipianfengye/androidSource。欢迎star和follow