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<Object, Object> 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<Object,ValueWrapper> local = new ConcurrentHashMap<>(); MyRedisCacheManager cacheManager; public MyRedisCache(MyRedisCacheManager cacheManager,String name, byte[] prefix, RedisOperations<? extends Object, ? extends Object> 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=172.16.86.56
spring.redis.port=6379