缓存系统的用来代替直接访问数据库，用来提升系统性能，减小数据库复杂。早期缓存跟系统在一个虚拟机里，这样内存访问，速度最快。 后来应用系统水平扩展，缓存作为一个独立系统存在，如redis，但是每次从缓存获取数据，都还是要通过网络访问才能获取，效率相对于早先从内存里获取，还是差了点。如果一个应用，比如传统的企业应用，一次页面显示，要访问数次redis，那效果就不是特别好，因此，现在有人提出了一二级缓存。即一级缓存跟系统在一个虚拟机内，这样速度最快。二级缓存位于redis里，当一级缓存没有数据的时候，再从redis里获取，并同步到一级缓存里。

现在实现这种一二级缓存的也挺多的，比如 hazelcast,新版的Ehcache..不过，实际上，如果你用spring boot，手里又一个Redis，则不需要搞hazelcastEhcache，只需要200行代码，就能在spring boot基础上，提供一个一二级缓存，代码如下：

import java.io.UnsupportedEncodingException;import java.util.concurrent.ConcurrentHashMap;import org.springframework.beans.factory.annotation.Value;import org.springframework.boot.autoconfigure.AutoConfigureBefore;import org.springframework.boot.bind.RelaxedPropertyResolver;import org.springframework.context.annotation.Bean;import org.springframework.context.annotation.Condition;import org.springframework.context.annotation.ConditionContext;import org.springframework.context.annotation.Conditional;import org.springframework.context.annotation.Configuration;import org.springframework.core.type.AnnotatedTypeMetadata;import org.springframework.data.redis.cache.RedisCache;import org.springframework.data.redis.cache.RedisCacheManager;import org.springframework.data.redis.cache.RedisCachePrefix;import org.springframework.data.redis.connection.Message;import org.springframework.data.redis.connection.MessageListener;import org.springframework.data.redis.connection.RedisConnectionFactory;import org.springframework.data.redis.core.RedisOperations;import org.springframework.data.redis.core.RedisTemplate;import org.springframework.data.redis.listener.PatternTopic;import org.springframework.data.redis.listener.RedisMessageListenerContainer;import org.springframework.data.redis.listener.adapter.MessageListenerAdapter;@Configuration@Conditional(StarterCacheCondition.class)public class CacheConfig {		@Value("${springext.cache.redis.topic:cache}")	String topicName ;				@Bean	public MyRedisCacheManager cacheManager(RedisTemplate
    
      redisTemplate) {		MyRedisCacheManager cacheManager = new MyRedisCacheManager(redisTemplate);		cacheManager.setUsePrefix(true);		return cacheManager;	}@Bean    RedisMessageListenerContainer container(RedisConnectionFactory connectionFactory,            MessageListenerAdapter listenerAdapter) {        RedisMessageListenerContainer container = new RedisMessageListenerContainer();        container.setConnectionFactory(connectionFactory);        container.addMessageListener(listenerAdapter, new PatternTopic(topicName));        return container;    }    @Bean    MessageListenerAdapter listenerAdapter(MyRedisCacheManager cacheManager ) {        return new MessageListenerAdapter(new MessageListener(){			@Override			public void onMessage(Message message, byte[] pattern) {				byte[] bs = message.getChannel();				try {					String type = new String(bs,"UTF-8");					cacheManager.receiver(type);				} catch (UnsupportedEncodingException e) {					e.printStackTrace();					// 不可能出错				}														}        	        });    }				class MyRedisCacheManager extends RedisCacheManager{						public MyRedisCacheManager(RedisOperations redisOperations) {			super(redisOperations);					}						@SuppressWarnings("unchecked")		@Override		protected RedisCache createCache(String cacheName) {			long expiration = computeExpiration(cacheName);			return new MyRedisCache(this,cacheName, (this.isUsePrefix()? this.getCachePrefix().prefix(cacheName) : null), this.getRedisOperations(), expiration);		}				/**		 * get a messsage for update cache		 * @param cacheName		 */		public void receiver(String cacheName){			MyRedisCache cache = (MyRedisCache)this.getCache(cacheName);			if(cache==null){				return ;			}			cache.cacheUpdate();					}				//notify other redis clent to update cache( clear local cache in fact)		public void publishMessage(String cacheName){			this.getRedisOperations().convertAndSend(topicName, cacheName);		}			}		class MyRedisCache extends RedisCache{		//local cache for performace		ConcurrentHashMap
     
       local = new ConcurrentHashMap<>();		MyRedisCacheManager cacheManager;		public MyRedisCache(MyRedisCacheManager cacheManager,String name, byte[] prefix,				RedisOperations
       redisOperations, long expiration) {			super(name, prefix, redisOperations, expiration);			this.cacheManager = cacheManager;		}		@Override		public ValueWrapper get(Object key) {			ValueWrapper wrapper = local.get(key);			if(wrapper!=null){				return wrapper;			}else{				wrapper =   super.get(key);				if(wrapper!=null){					local.put(key, wrapper);				}								return wrapper;			}					}				@Override		public void put(final Object key, final Object value) {			super.put(key, value);			cacheManager.publishMessage(super.getName());		}				@Override		public void evict(Object key) {			super.evict(key);			cacheManager.publishMessage(super.getName());		}						@Override		public ValueWrapper putIfAbsent(Object key, final Object value){			ValueWrapper wrapper = super.putIfAbsent(key, value);			cacheManager.publishMessage(super.getName());			return wrapper;		}				public void cacheUpdate(){			//clear all cache for simplification 			local.clear();		}			}	}class StarterCacheCondition implements Condition {		@Override	public boolean matches(ConditionContext context, AnnotatedTypeMetadata metadata) {		RelaxedPropertyResolver resolver = new RelaxedPropertyResolver(				context.getEnvironment(), "springext.cache.");				String env = resolver.getProperty("type");		if(env==null){			return false;		}		return "local2redis".equalsIgnoreCase(env.toLowerCase());		}}
     
    

代码的核心在于spring boot提供一个概念CacheManager&Cache用来表示缓存，并提供了多达8种实现，但由于缺少一二级缓存，因此，需要在Redis基础上扩展，因此实现了MyRedisCacheManger,以及MyRedisCache，增加一个本地缓存。

一二级缓存需要解决的的一个问题是缓存更新的时候，必须通知其他节点的springboot应用缓存更新。这里可以用Redis的 Pub/Sub 功能来实现，具体可以参考listenerAdapter方法实现。

使用的时候，需要配置如下，这样，就可以使用缓存了，性能杠杠的好

springext.cache.type=local2redis# Redis服务器连接端口spring.redis.host=172.16.86.56spring.redis.port=6379