我需要线程安全且高效的LRU缓存实现代码。
下面的代码不是线程安全的。是否可以使用ConcurrentHashMap增强此代码。
提前致谢。
private class LruCache<A, B> extends LinkedHashMap<A, B> {
private final int maxEntries;
public LruCache(final int maxEntries) {
super(maxEntries + 1, 1.0f, true);
this.maxEntries = maxEntries;
}
@Override
protected boolean removeEldestEntry(final Map.Entry<A, B> eldest) {
return super.size() > maxEntries;
}
}
答案 0 :(得分：5)
你可以做的最好的事情就是让它的线程安全是用Collections.synchronizedMap(map)包装它，如javadoc所述：
请注意，此实施未同步。如果有多个线程 同时访问链接的哈希映射，以及至少一个线程 从结构上修改地图，必须在外部进行同步。 这通常通过同步某个对象来完成 自然地封装了地图。如果不存在此类对象，则为地图 应该使用
Collections.synchronizedMap方法“包装”。这个 最好在创建时完成，以防止意外的不同步 访问地图：
Map m = Collections.synchronizedMap(new LinkedHashMap(...));
然而，仅仅使它完全线程安全是不够的，你需要使用包装映射的实例作为对象的监视器来保护对地图内容的任何迭代：
Map m = Collections.synchronizedMap(map);
...
Set s = m.keySet(); // Needn't be in synchronized block
...
synchronized (m) { // Synchronizing on m, not s!
Iterator i = s.iterator(); // Must be in synchronized block
while (i.hasNext())
foo(i.next());
}
这几乎可以轻松对我们在JDK中开箱即用的内容做一切，如果你想要一些线程安全且更有效的东西，你应该看看来自 Google Guava 的Cache。
以下是使用LRU构建的最大2 guava个缓存的示例：
ConcurrentMap<String, String> cache =
CacheBuilder.newBuilder()
.maximumSize(2L)
.<String, String>build().asMap();
cache.put("a", "b");
cache.put("b", "c");
System.out.println(cache);
cache.put("a", "d");
System.out.println(cache);
cache.put("c", "d");
System.out.println(cache);
<强>输出：
{b=c, a=b}
{b=c, a=d}
{c=d, a=d}
答案 1 :(得分：0)
与使用Collections.synchronozedMap()作为包装器相比，我认为最好同时使用ConcurrentHashMap和ConcurrentLinkedList并实现java.util.Map接口并且可能List 1}}如果你需要接口。但是，您需要在内部映射和列表上的操作之间使用一些自定义逻辑，以确保并发成立。但是，性能仍然比完全synchronized地图好。
答案 2 :(得分：0)
找到了番石榴的Cache。 Haven没有自己使用它。
缓存类似于ConcurrentMap，但不完全相同。
来源：https://github.com/google/guava/wiki/CachesExplained
示例：
LoadingCache<Key, Graph> graphs = CacheBuilder.newBuilder()
.expireAfterAccess(10, TimeUnit.MINUTES)
.maximumSize(1000)
.build(
new CacheLoader<Key, Graph>() {
public Graph load(Key key) { // no checked exception
return createExpensiveGraph(key);
}
});
...
return graphs.getUnchecked(key);
答案 3 :(得分：0)
您可以使用Android的解决方案，该解决方案是线程安全的（它说“此类是线程安全的”）：
https://developer.android.com/reference/android/util/LruCache
可惜的是，它似乎没有提供并发性。只是同步内容...
当前代码：
/*
* Copyright (C) 2011 The Android Open Source Project
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package android.util;
import java.util.LinkedHashMap;
import java.util.Map;
/**
* BEGIN LAYOUTLIB CHANGE
* This is a custom version that doesn't use the non standard LinkedHashMap#eldest.
* END LAYOUTLIB CHANGE
*
* 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.
*
* <p>If your cached values hold resources that need to be explicitly released,
* override {@link #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.
*
* <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:
* <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.
*
* <p>This class appeared in Android 3.1 (Honeycomb MR1); it's available as part
* of <a href="http://developer.android.com/sdk/compatibility-library.html">Android's
* Support Package</a> for earlier releases.
*/
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.
*
* @hide
*/
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;
}
/**
* @param maxSize the maximum size of the cache before returning. May be -1
* to evict even 0-sized elements.
*/
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;
}
// BEGIN LAYOUTLIB CHANGE
// get the last item in the linked list.
// This is not efficient, the goal here is to minimize the changes
// compared to the platform version.
Map.Entry<K, V> toEvict = null;
for (Map.Entry<K, V> entry : map.entrySet()) {
toEvict = entry;
}
// END LAYOUTLIB CHANGE
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);
}
}
答案 4 :(得分：0)
因此，我认为，如果要在LRU Cache中维护的数据量很大，那么同步的LinkedHashMap将是理想的解决方案，而方法2仅在保留的数据量较小的情况下才有帮助。 另外，为了在同步的LinkedHashMap中保留大量数据的同时获得更好的性能，最好使用哈希算法将数据划分为多个LinkedHashMap，以确定哪个LinkedHashMap将拥有数据，以便可以在不同分区的LinkedHashMaps上进行并行读取。