1. LruCache 是什么?
了解:HashMap 底层:哈希表(hashcode,equals) 线程不安全,效率高(针对key)
LinkedHashMap 底层: 链表(保证有序) 哈希表(hashcode,equals) TreeMap 底层:红黑树 (有序:1.自然排序 2.比较器排序)
要搞清楚 LruCache 是什么之前,首先要知道 Android 的缓存策略。其实缓存策略很简单,举个例子,就是用户第一次使用网络加载一张图片后,下次加载这张图片的时候,并不会从网络加载,而是会从内存或者硬盘加载这张图片。
缓存策略分为添加、获取和删除,为什么需要删除缓存呢?因为每个设备都会有一定的容量限制,当容量满了的话就需要删除。
那什么是 LruCache 呢?其实 LRU(Least Recently Used) 的意思就是近期最少使用算法,它的核心思想就是会优先淘汰那些近期最少使用的缓存对象。
LruCache原理解析
LruCache是一个泛型类,它内部采用LinkedHashMap,并以强引用的方式存储外界的缓存对象,提供get和put方法来完成缓存的获取和添加操作。当缓存满时,LruCache会移除较早的缓存对象,然后再添加新的缓存对象。对Java中四种引用类型还不是特别清楚的读者可以自行查阅相关资料,这里不再给出介绍。
介绍源码前 先介绍LinkedHashMap一些特性
LinkedHashMap实现与HashMap的不同之处在于,后者维护着一个运行于所有条目的双重链接列表。此链接列表定义了迭代顺序,该迭代顺序可以是插入顺序或者是访问顺序。
对于LinkedHashMap而言,它继承与HashMap、底层使用哈希表与双向链表来保存所有元素。其基本操作与父类HashMap相似,它通过重写父类相关的方法,来实现自己的链接列表特性
- Entry元素:
LinkedHashMap采用的hash算法和HashMap相同,但是它重新定义了数组中保存的元素Entry,该Entry除了保存当前对象的引用外,还保存了其上一个元素before和下一个元素after的引用,从而在哈希表的基础上又构成了双向链接列表。
/**
* 双向链表的表头元素。
*/
private transient Entry header;
/**
* LinkedHashMap的Entry元素。
* 继承HashMap的Entry元素,又保存了其上一个元素
before和下一个元素after的引用。
*/
private static class Entry extends
HashMap.Entry {
Entry before, after;
……
}
- 读取:
LinkedHashMap重写了父类HashMap的get方法,实际在调用父类getEntry()方法取得查找的元素后,再判断当排序模式accessOrder为true时,记录访问顺序,将最新访问的元素添加到双向链表的表头(这个特性保证了LRU最近最少使用),并从原来的位置删除。由于的链表的增加、删除操作是常量级的,故并不会带来性能的损失。
@Override public V get(Object key) {
/*
* This method is overridden to eliminate the need for a polymorphic
* invocation in superclass at the expense of code duplication.
*/
if (key == null) {
HashMapEntry e = entryForNullKey;
if (e == null)
return null;
if (accessOrder)
makeTail((LinkedEntry) e);
return e.value;
}
int hash = Collections.secondaryHash(key);
HashMapEntry[] tab = table;
for (HashMapEntry e = tab[hash & (tab.length - 1)];
e != null; e = e.next) {
K eKey = e.key;
if (eKey == key || (e.hash == hash && key.equals(eKey))) {
if (accessOrder)
makeTail((LinkedEntry) e);
return e.value;
}
}
return null;
}
/**
* Relinks the given entry to the tail of the list. Under access ordering,
* this method is invoked whenever the value of a pre-existing entry is
* read by Map.get or modified by Map.put.
*/
private void makeTail(LinkedEntry e) {
// Unlink e
e.prv.nxt = e.nxt;
e.nxt.prv = e.prv;
// Relink e as tail
LinkedEntry header = this.header;
LinkedEntry oldTail = header.prv;
e.nxt = header;
e.prv = oldTail;
oldTail.nxt = header.prv = e;
modCount++;
}
总结
LRU (Least Recently Used) 就是最近最少使用算法,LruCache当然就是依据 LRU 算法实现的缓存。简单说就是,设置好缓存大小;当缓存空间不足的时候,就把最近最少使用(也就是最长时间没有使用)的缓存项清除掉;然后提供新的缓存。
1、LruCache(HashMap+LinkedHashMap) 是基于 Lru 算法实现的一种缓存机制;
LruCache 其实使用了 LinkedHashMap 维护了强引用对象
总缓存的大小一般是可用内存的 1/8,当超过总缓存大小会删除最少使用的元
素,也就是内部 LinkedHashMap 的头部元素
当使用 get() 访问元素后,会将该元素移动到 LinkedHashMap 的尾部
2、Lru算法的原理是把近期最少使用的数据给移除掉,当然前提是当前数据的量大于设定的最大值。
3、LruCache 没有真正的释放内存,只是从 Map中移除掉数据,真正释放内存还是要用户手动释放。
归结几点
LruCache 内部使用 LinkedHashMap 实现,所以 LruCache 保存的是键值对
LruCache 本身对缓存项是强引用
LruCache 的读写是线程安全的,内部加了 synchronized。也就是 put(K key, V value) 和 get(K key) 内部有 synchronized
key 和 value 不接受 null 。所以如果 get 到了 null ,那就说明是没有缓存
Override sizeOf(K key, V value) 方法
根据需要Override entryRemoved(boolean evicted, K key, V oldValue, V newValue) 和 create(K key) 方法
源码分析
public class LruCache {
private final LinkedHashMap map;
/** Size of this cache in units. Not necessarily the number of elements. */
private int size;//当前缓存大小
private int maxSize;//缓存最大
private int putCount;//put次数
private int createCount;
private int evictionCount;//回收次数
private int hitCount;//命中次数
private int missCount;//没有命中次数
/**
* @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(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);
}
/**
* 返回缓存中key对应的value,如果不存在则创建一个并返回。
* 如果value被返回,它就会被移动到队列的头部,如果value为null或者不能被创建,方法返回nul
*/
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++;
}
/*
* 如果未被命中,则试图创建一个value.这将会消耗较长时间,创建过程中,
* 如果要添加的value值和map中已有的值冲突,则释放已经创建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 {
//判断缓存是否越界
trimToSize(maxSize);
return createdValue;
}
}
/**
* 缓存key对应的value.value 会被移动至队列头部。
* 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 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.
*
* 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.
*
*
The method is called without synchronization: other threads may
* access the cache while this method is executing.
*
*
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.
*
*
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 snapshot() {
return new LinkedHashMap(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);
}
}