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
