从LruCache到LinkedHashMap与HashMap
LruCache
LruCache为内存缓存核心类，LRU即Least RecentlyUsed，近期最少使用算法。也就是当内存缓存达到设定的最大值时将内存缓存中近期最少使用的对象移除，有效的避免了OOM的出现。 LruCache中Lru算法的实现是通过LinkedHashMap来实现的。LinkedHashMap继承于HashMap，它使用了一个双向链表来存储Map中的Entry顺序关系，这种顺序有两种，一种是LRU顺序，一种是插入顺序，可以由其构造函数public LinkedHashMap(int initialCapacity,float loadFactor, boolean accessOrder)指定。所以，对于get、put、remove等操作，LinkedHashMap除了要做HashMap做的事情，还做些调整Entry顺序链表的工作。LruCache中将LinkedHashMap的顺序设置为LRU顺序来实现LRU缓存，每次调用get(也就是从内存缓存中取图片)，则将该对象移到链表的尾端。调用put插入新的对象也是存储在链表尾端，这样当内存缓存达到设定的最大值时，将链表头部的对象（近期最少用到的）移除。 LruCache源码如下
package android.util;
import java.util.LinkedHashMap;
import java.util.Map;
/**
* 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保存一个强引用来限制内容数量，每当Item被访问的时候，此Item就会移动到队列的头部。
* 当cache已满的时候加入新的item时，在队列尾部的item会被回收。
* <p>If your cached values hold resources that need to be explicitly released,
* override {@link #entryRemoved}.
* 如果你cache的某个值需要明确释放，重写entryRemoved()
* <p>If a cache miss should be computed on demand for the corresponding keys,
* override {@link #create}. This simplifies the calling code, allowing it to
* assume a value will always be returned, even when there's a cache miss.
* 如果key相对应的item丢掉啦，重写create().这简化了调用代码，即使丢失了也总会返回。
* <p>By default, the cache size is measured in the number of entries. Override
* {@link #sizeOf} to size the cache in different units. For example, this cache
* is limited to 4MiB of bitmaps: 默认cache大小是测量的item的数量，重写sizeof计算不同item的
* 大小。
* <pre> {@code
* int cacheSize = 4 * 1024 * 1024; // 4MiB
* LruCache<String, Bitmap> bitmapCache = new LruCache<String, Bitmap>(cacheSize) {
* protected int sizeOf(String key, Bitmap value) {
* return value.getByteCount();
* }
* }}</pre>
*
* <p>This class is thread-safe. Perform multiple cache operations atomically by
* synchronizing on the cache: <pre> {@code
* synchronized (cache) {
* if (cache.get(key) == null) {
* cache.put(key, value);
* }
* }}</pre>
*
* <p>This class does not allow null to be used as a key or value. A return
* value of null from {@link #get}, {@link #put} or {@link #remove} is
* unambiguous: the key was not in the cache.
* 不允许key或者value为null
* 当get（），put（），remove（）返回值为null时，key相应的项不在cache中
*/
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; //已经存储的大小
private int maxSize; //规定的最大存储空间
private int putCount; //put的次数
private int createCount; //create的次数
private int evictionCount; //回收的次数
private int hitCount; //命中的次数
private int missCount; //丢失的次数
/**
* @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);
}
/**
* 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. 通过key返回相应的item，或者创建返回相应的item。相应的item会移动到队列的头部，
* 如果item的value没有被cache或者不能被创建，则返回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) {
hitCount++; //命中
return mapValue;
}
missCount++; //丢失
}
/*
* 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.
* 如果丢失了就试图创建一个item
*/
V createdValue = create(key);
if (createdValue == null) {
return null;
}
synchronized (this) {
createCount++;//创建++
mapValue = map.put(key, createdValue);
if (mapValue != null) {
// There was a conflict so undo that last put
//如果前面存在oldValue，那么撤销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) { //返回的先前的value值
size -= safeSizeOf(key, previous);
}
}
if (previous != null) {
entryRemoved(false, key, previous, value);
}
trimToSize(maxSize);
return previous;
}
/**
* @param maxSize the maximum size of the cache before returning. May be -1
* to evict even 0-sized elements.
* 清空cache空间
*/
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!");
}
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.
* 删除key相应的cache项，返回相应的value
* @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.
* 当item被回收或者删掉时调用。改方法当value被回收释放存储空间时被remove调用，
* 或者替换item值时put调用，默认实现什么都没做。
* <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}.
* true---为释放空间被删除；false---put或remove导致
* @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.
* 当某Item丢失时会调用到，返回计算的相应的value或者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.
* 返回用户定义的item的大小，默认返回1代表item的数量，最大size就是最大item值
* <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.
* 清空cacke
*/
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.
* 返回被回收的数量
*/
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. 返回当前cache的副本
*/
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);
}
}
LinkedHashMap
Linked内部含有一个private transient Entry header;来记录元素插入的顺序或者是元素被访问的顺序。利用这个线性结构的对象，可以帮助记录entry加入的前后顺序或者记录entry被访问的 频率(最少被访问的entry靠前，最近访问的entry靠后)。大致的过程如下:
new LinkedHashMap(10, 0.75, true); 其中前面两个参数就是HashMap构造函数需要的参数，后面的true表明LinkedHashMap按照访问的次序来排序。 按照访问的次序来排序的含义:当调用LinkedHashMap的get(key)或者put(key, value)时，碰巧key在map中被包含，那么LinkedHashMap会将key对象的entry放在线性结构的最后。 按照插入顺序来排序的含义:调用get(key), 或者put(key, value)并不会对线性结构产生任何的影响。
正是因为LinkedHashMap提供按照访问的次序来排序的功能，所以它才需要改写HashMap的get(key)方法（HashMap不需要排序）和HashMap.Entry的recordAccess(HashMap)方法 public Object get(Object key) { Entry e = (Entry)getEntry(key); if (e == null) return null; e.recordAccess(this); return e.value; }
void recordAccess(HashMap m) { LinkedHashMap lm = (LinkedHashMap)m; if (lm.accessOrder) { lm.modCount++; remove(); addBefore(lm.header); } } 注 意addBefore(lm.header)是将该entry放在header线性表的最后。（参考LinkedHashMap.Entry extends HashMap.Entry 比起HashMap.Entry多了before, after两个域，是双向的）
至于put(key, value)方法， LinkedHashMap不需要去改写，用HashMap的就可以了，因为HashMap在其put(key, value)方法里边已经预留了e.recordAccess(this);
还有一个方法值得关注: protected boolean removeEldestEntry(Map.Entry eldest) { return false; } 当 调用put(key, value)的时候，HashMap判断是否要自动增加map的size的作法是判断是否超过threshold， LinkedHashMap则进行了扩展，如果removeEldestEntry方法return false；（默认的实现），那么LinkedHashMap跟HashMap处理扩容的方式一致；如果removeEldestEntry返回 true，那么LinkedHashMap会自动删掉最不常用的那个entry（也就是header线性表最前面的那个）。
这会造成严重的性能问题吗？答案当然是否定的。因为在这儿的链表操作是常量级的。这也是LinkedHashMap/Set在这儿比TreeMap/Set性能更高的原因。
同样，LinkedHashMap/Set也不是thread-safe的。如果在多线程下访问，是需要进行外部同步，或者使用Collections.synchronizedMap()的方法包装成一个thread-safe的Map/Set。
特别需要注意的是，在使用“访问顺序”时，读取节点操作也是“结构变化”的操作。因为，这会改变元素遍历的顺序。所以，在使用 LinkedHashMap的iterator()方法，遍历元素时，如果其它线程有读取操作，也要进行同步。否则，也会抛出同其它fail-fast一 样的由于删除或增加操作而引起的CurrentModificationException的例外。 最后，LinkedHashMap缺省是使用插入顺序的，如何构造一个访问顺序的LinkedHashMap呢？很简单： public LinkedHashMap(int initialCapacity, float loadFactor, boolean accessOrder) accessOrder = true 即可。
HashMap
HashMap是Hashtable的轻量级实现（非线程安全的实现），效率上可能高于Hashtable。他们都完成了Map接口。HashMap允许null值作为key和value，而Hashtable不可以。 最大的不同是，Hashtable的方法是Synchronize的，而HashMap不是，在多个线程访问Hashtable时，不需要自己为它的方法实现同步，而HashMap 就必须为之提供外同步(Collections.synchronizedMap)。
迭代HashMap采用快速失败机制（不是迭代完成后才告诉你出错了），而Hashtable不是。迭代器的快速失败机制会抛出一个并发修改异常 （ConcurrentModificationException） ，应该仅用于检测程序错误。 我们知道java.util.HashMap不是线程安全的，因此如果在使用迭代器的过程中有其他线程修改了map，那么将抛出ConcurrentModificationException，这就是所谓fail-fast策略。这一策略在源码中的实现是通过modCount域，modCount顾名思义就是修改次数，对HashMap内容的修改都将增加这个值，那么在迭代器初始化过程中会将这个值赋给迭代器的expectedModCount。在迭代过程中，判断modCount跟expectedModCount是否相等，如果不相等就表示已经有其他线程修改了Map。modCount声明为volatile，保证线程之间修改的可见性。
参考
http://tomyz0223.iteye.com/blog/1035686 http://blog.csdn.net/linghu_java/article/details/8574102 http://www.cnblogs.com/liuling/archive/2015/09/24/2015-9-24-1.html
正文到此结束
热门推荐
相关文章
近期评论
-
666
-
文章和留言都翻到11页了 没有OOM
-
-
朋友，翻页到11页，及以后，会出现OOM，无法访问
-
-
-
-
版本号是多少，你可以下载哪个代码仓库，jdk选1.8 直接跑就行
-
-
Loading...
![[HBLOG]公众号](https://www.liuhaihua.cn/img/qrcode_gzh.jpg)
