一、LruCache是什么？
LRU是Least Recently Used 近期最少使用算法。内存管理的一种页面置换算法，对于在内存中但又不用的数据块（内存块）叫做LRU，操作系统会根据哪些数据属于LRU而将其移出内存而腾出空间来加载另外的数据。什么是LRU算法？ LRU即最近最少使用，常用于页面置换算法，是为虚拟页式存储管理服务的。（百度详解 https://baike.baidu.com/item/LRU/1269842?fr=aladdin）
Cache是缓存的意思。从字面上我们可以了解LruCache就是一个使用近期最少使用算法的缓存类，因此，安卓在Android.util包提供了LruCache这个缓存类。
二、为什么使用LruCache？
1、LruCache已经存在于官方的API当中，无需添加任何依赖即可使用。它的主要算法原理是把最近使用的对象用强引用存储在 LinkedHashMap 中，并且把最近最少使用的对象在缓存值达到预设定值之前从内存中移除。
2、现在的APP大多数是需要联网才能使用，例如我们要做一个电子商务App，如果我们不加节制的向服务器请求大量图片，那么对于服务器来说是一个不少的负担，其次，对于用户来说，每次刷新都意味着流量的大量消耗以及长时间等待，所以缓存机制几乎是每个需要联网的App必须做的。
三、如何使用LruCache？
1、首先了解官方提供的LruCache源码
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;//当前的缓存大小
private int maxSize;//最大的缓存大小
private int putCount;
private int createCount;
private int evictionCount;
private int hitCount;
private int missCount;
public LruCache(int maxSize) {//设置最大的缓存
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) {//重新设置最大的缓存
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 || map.isEmpty()) {
break;
}
Map.Entry<K, V> toEvict = map.entrySet().iterator().next();
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);
}}
以上是官方提供的LruCache的方法，因为LruCache多用于图片的缓存，所以以下是LruCache对图片bitmap的简单使用。
public class LruCashUtil {
private static final String TAG = "LruCashUtil";
private LruCache<String, Bitmap> lruCache;
//用来初始化缓存对象
public LruCashUtil( ) {
//获取到最大可用的内存空间
long maxMemory = Runtime.getRuntime().maxMemory();
int cacheSize = (int) (maxMemory / 8);
lruCache = new LruCache<String, Bitmap>(cacheSize) {
@Override
protected int sizeOf(String key,Bitmap value) {
return value.getByteCount();
}
};
}
// 把Bitmap对象加入到缓存中
public void addBitmapToMemory(String key,Bitmap bitmap) {
if (getBitmapFromMemCache(key) == null) {
lruCache.put(key,bitmap);
}
}
// 从缓存中得到Bitmap对象
public Bitmap getBitmapFromMemCache(String key) {
Log.i(TAG,"lrucache size: " + lruCache.size());
return lruCache.get(key);
}
// 从缓存中删除指定的Bitmap
public void removeBitmapFromMemory(String key) {
lruCache.remove(key);
}
}
