dubbo提供了三种结果缓存机制：
- lru：基于最近最少使用原则删除多余缓存，保持最热的数据被缓存
- threadlocal：当前线程缓存
- jcache：可以桥接各种缓存实现
一、使用方式
<dubbo:reference id="demoService" check="false" interface="com.alibaba.dubbo.demo.DemoService">
<dubbo:method name="sayHello" timeout="60000" cache="lru"/>
</dubbo:reference>
添加cache配置。
注意：dubbo结果缓存有一个bug，https://github.com/alibaba/dubbo/issues/1362，当cache="xxx"配置在服务级别时，没有问题，当配置成方法级别的时候，不管怎么配置，都睡使用LruCache。
二、LRU缓存源码解析
/**
* CacheFilter
* 配置了cache配置才会加载CacheFilter
*/
@Activate(group = {Constants.CONSUMER, Constants.PROVIDER}, value = Constants.CACHE_KEY)
public class CacheFilter implements Filter {
private CacheFactory cacheFactory; public void setCacheFactory(CacheFactory cacheFactory) {
this.cacheFactory = cacheFactory;
} public Result invoke(Invoker<?> invoker, Invocation invocation) throws RpcException {
if (cacheFactory != null && ConfigUtils.isNotEmpty(invoker.getUrl().getMethodParameter(invocation.getMethodName(), Constants.CACHE_KEY))) {
// 使用CacheFactory$Adaptive获取具体的CacheFactory，然后再使用具体的CacheFactory获取具体的Cache对象
Cache cache = cacheFactory.getCache(invoker.getUrl().addParameter(Constants.METHOD_KEY, invocation.getMethodName()));
if (cache != null) {
// 缓存对象的key为arg1,arg2,arg3,...,arg4
String key = StringUtils.toArgumentString(invocation.getArguments());
// 获取缓存value
Object value = cache.get(key);
if (value != null) {
return new RpcResult(value);
}
Result result = invoker.invoke(invocation);
// 响应结果没有exception信息，则将相应结果的值塞入缓存
if (!result.hasException()) {
cache.put(key, result.getValue());
}
return result;
}
}
return invoker.invoke(invocation);
}
}
从@Activate(group = {Constants.CONSUMER, Constants.PROVIDER}, value = Constants.CACHE_KEY)中我们可以看出，consumer端或provider端配置了cache="xxx"，则会走该CacheFilter。
首先获取具体Cache实例：CacheFilter中的cacheFactory属性是CacheFactory$Adaptive实例。
public class CacheFactory$Adaptive implements com.alibaba.dubbo.cache.CacheFactory {
public com.alibaba.dubbo.cache.Cache getCache(com.alibaba.dubbo.common.URL arg0) {
if (arg0 == null) throw new IllegalArgumentException("url == null");
com.alibaba.dubbo.common.URL url = arg0;
String extName = url.getParameter("cache", "lru");
if (extName == null)
throw new IllegalStateException("Fail to get extension(com.alibaba.dubbo.cache.CacheFactory) name from url(" + url.toString() + ") use keys([cache])");
// 获取具体的CacheFactory
com.alibaba.dubbo.cache.CacheFactory extension = (com.alibaba.dubbo.cache.CacheFactory) ExtensionLoader.getExtensionLoader(com.alibaba.dubbo.cache.CacheFactory.class).getExtension(extName);
// 使用具体的CacheFactory获取具体的Cache
return extension.getCache(arg0);
}
}
这里extName使我们配置的lru，如果不配置，默认也是lru。这里获取到的具体的CacheFactory是LruCacheFactory。
@SPI("lru")
public interface CacheFactory {
@Adaptive("cache")
Cache getCache(URL url);
}
public abstract class AbstractCacheFactory implements CacheFactory {
private final ConcurrentMap<String, Cache> caches = new ConcurrentHashMap<String, Cache>();
public Cache getCache(URL url) {
String key = url.toFullString();
Cache cache = caches.get(key);
if (cache == null) {
caches.put(key, createCache(url));
cache = caches.get(key);
}
return cache;
}
protected abstract Cache createCache(URL url);
}
public class LruCacheFactory extends AbstractCacheFactory {
protected Cache createCache(URL url) {
return new LruCache(url);
}
}
调用LruCacheFactory.getCache(URL url)方法，实际上调用的是其父类AbstractCacheFactory的方法。逻辑是：创建一个LruCache实例，之后存储在ConcurrentMap<String, Cache> caches中，key为url.toFullString()。
再来看LruCache的创建：
public interface Cache {
void put(Object key, Object value);
Object get(Object key);
}
public class LruCache implements Cache {
private final Map<Object, Object> store;
public LruCache(URL url) {
final int max = url.getParameter("cache.size", 1000);
this.store = new LRUCache<Object, Object>(max);
}
public void put(Object key, Object value) {
store.put(key, value);
}
public Object get(Object key) {
return store.get(key);
}
}
默认缓存存储的最大个数为1000个。之后创建了一个LRUCache对象。
public class LRUCache<K, V> extends LinkedHashMap<K, V> {
private static final long serialVersionUID = -5167631809472116969L;
private static final float DEFAULT_LOAD_FACTOR = 0.75f;
private static final int DEFAULT_MAX_CAPACITY = 1000;
private final Lock lock = new ReentrantLock();
private volatile int maxCapacity;
public LRUCache(int maxCapacity) {
/**
* 注意：
* LinkedHashMap 维护着一个运行于所有Entry的双向链表：此链表定义了迭代顺序，该迭代顺序可以是插入顺序或者是访问顺序
* 而真正存储的数据结构还是其父类HashMap的那个Entry[]数组，上述的双向链表仅用于维护迭代顺序（帮助实现lru算法等）
*
* LinkedHashMap(int initialCapacity, float loadFactor, boolean accessOrder)
* 第三个参数accessOrder：false（插入顺序），true（访问顺序）
*/
super(16, DEFAULT_LOAD_FACTOR, true);
this.maxCapacity = maxCapacity;
}
/**
* 是否需要删除最老的数据（即最近没有被访问的数据）
* @param eldest
* @return
*/
@Override
protected boolean removeEldestEntry(java.util.Map.Entry<K, V> eldest) {
return size() > maxCapacity;
}
@Override
public V get(Object key) {
try {
lock.lock();
return super.get(key);
} finally {
lock.unlock();
}
}
@Override
public V put(K key, V value) {
try {
lock.lock();
return super.put(key, value);
} finally {
lock.unlock();
}
}
@Override
public V remove(Object key) {
try {
lock.lock();
return super.remove(key);
} finally {
lock.unlock();
}
}
@Override
public int size() {
try {
lock.lock();
return super.size();
} finally {
lock.unlock();
}
}
...
}
注意：
- LinkedHashMap维护着一个运行于所有Entry的双向链表：此链表定义了迭代顺序，该迭代顺序可以是插入顺序或者是访问顺序（真正存储的数据结构还是其父类HashMap的那个Entry[]数组，上述的双向链表仅用于维护迭代顺序）
- 当指定了LinkedHashMap(int initialCapacity, float loadFactor, boolean accessOrder)第三个参数accessOrder=true时，每次执行get(Object key)时，获取出来的Entry都会被放到尾节点，也就是说双向链表的header节点是最久以前访问的，当执行put(Object key, Object value)的时候，就执行removeEldestEntry(java.util.Map.Entry<K, V> eldest)来判断是否需要删除这个header节点。（这些是LinkedHashMap实现的，具体源码分析见 https://yikun.github.io/2015/04/02/Java-LinkedHashMap%E5%B7%A5%E4%BD%9C%E5%8E%9F%E7%90%86%E5%8F%8A%E5%AE%9E%E7%8E%B0/ http://wiki.jikexueyuan.com/project/java-collection/linkedhashmap.html）
三、ThreadLocal缓存源码解析
根据文章开头提到的bug，cache=""只能配置在服务级别。
<dubbo:reference id="demoService" check="false" interface="com.alibaba.dubbo.demo.DemoService" cache="threadlocal"/>
public class ThreadLocalCacheFactory extends AbstractCacheFactory {
protected Cache createCache(URL url) {
return new ThreadLocalCache(url);
}
}
public class ThreadLocalCache implements Cache {
private final ThreadLocal<Map<Object, Object>> store;
public ThreadLocalCache(URL url) {
this.store = new ThreadLocal<Map<Object, Object>>() {
@Override
protected Map<Object, Object> initialValue() {
return new HashMap<Object, Object>();
}
};
}
public void put(Object key, Object value) {
store.get().put(key, value);
}
public Object get(Object key) {
return store.get().get(key);
}
}
ThreadLocalCache的实现是HashMap。
四、JCache缓存源码解析
//TODO