前世今生
java开发中，针对主流网站，流量大的网站都会使用缓存,目前流行的缓存框架很多，其中表现的最优秀的redis,算是佼佼者。
cacheChen 是什么
框架基于spring cache 重构，由国内资深人气工程师allen.chen，亲历打造轻量级redis缓存框架，旨在增加开发效率，和redis完美集合.
cacheChen的问世解决了spring 注解不具备的功能，解决缓存雪崩 穿透 问题，支持配置失效时间等强大功能难以想象。
用到了什么
- lombok https://projectlombok.org/
- spring boot
- jedis
<dependency>
<groupId>redis.clients</groupId>
<artifactId>jedis</artifactId>
<version>2.9.0</version>
</dependency>
功能说明
- 缓存批量命中，批量处理
- 解决缓存穿透问题
- 解决缓存雪崩问题
- 支持配置缓存失效时间
- 实现缓存的读写分离，不同cacheName 配置不同的读写库
- 支持spring 4.0+ cache 注解功能
新增功能(20170813更新)
- cacheName 同步key分布式锁功能
- 配置
/**
* 是否开启缓存key分布式锁
*/
redisConfig.setDistributedLock(true);
基本配置
@Configuration
public class Config {
@Bean
public BeanFactoryCacheOperationAdvisor cacheAdvisor(){
BeanFactoryCacheOperationAdvisor advisor = new BeanFactoryCacheOperationAdvisor();
advisor.setAdvice(cacheInterceptor());
return advisor;
}
@Bean
public CacheInterceptor cacheInterceptor(){
return new CacheInterceptor();
}
}
/**
* 创建cache manager
* @return
*/
@Bean
public CacheManager createCacheManager(){
RedisConfig redisConfig = new RedisConfig();
redisConfig.setDefaultReadSourceName("read");
redisConfig.setDefaultWriteSourceName("write");
JedisPoolConfig config = new JedisPoolConfig();
//连接耗尽时是否阻塞, false报异常,true 阻塞直到超时, 默认true
config.setBlockWhenExhausted(true);
//设置的逐出策略类名, 默认DefaultEvictionPolicy(当连接超过最大空闲时间,或连接数超过最大空闲连接数)
config.setEvictionPolicyClassName("org.apache.commons.pool2.impl.DefaultEvictionPolicy");
//是否启用pool的jmx管理功能, 默认true
config.setJmxEnabled(true);
//MBean ObjectName = new ObjectName("org.apache.commons.pool2:type=GenericObjectPool,name=" + "poolConfig" + i); 默认为"poolConfig", JMX不熟,具体不知道是干啥的...默认就好.
config.setJmxNamePrefix("poolConfig");
//是否启用后进先出, 默认true
config.setLifo(true);
//最大空闲连接数, 默认8个
config.setMaxIdle(8);
//最大连接数, 默认8个
config.setMaxTotal(8);
//获取连接时的最大等待毫秒数(如果设置为阻塞时BlockWhenExhausted),如果超时就抛异常, 小于零:阻塞不确定的时间, 默认-1
config.setMaxWaitMillis(-1);
//逐出连接的最小空闲时间 默认1800000毫秒(30分钟)
config.setMinEvictableIdleTimeMillis(1800000);
//最小空闲连接数, 默认0
config.setMinIdle(0);
//每次逐出检查时 逐出的最大数目 如果为负数就是 : 1/abs(n), 默认3
config.setNumTestsPerEvictionRun(3);
//对象空闲多久后逐出, 当空闲时间>该值 且 空闲连接>最大空闲数 时直接逐出,不再根据MinEvictableIdleTimeMillis判断 (默认逐出策略)
config.setSoftMinEvictableIdleTimeMillis(1800000);
//在获取连接的时候检查有效性, 默认false
config.setTestOnBorrow(false);
//在空闲时检查有效性, 默认false
config.setTestWhileIdle(false);
//逐出扫描的时间间隔(毫秒) 如果为负数,则不运行逐出线程, 默认-1
config.setTimeBetweenEvictionRunsMillis(-1);
// poolConfig.setTestWhileIdle(true);
// poolConfig.setTestOnBorrow(true);
RedisSource[] sources = new RedisSource[2];
RedisSource readRedisSource = new RedisSource();
readRedisSource.setSourceName("read");
readRedisSource.setIp("192.168.0.118");
readRedisSource.setPort(6379);
readRedisSource.setPassword("chen");
readRedisSource.setPoolConfig(config);
RedisSource writeRedisSource = new RedisSource();
writeRedisSource.setSourceName("write");
writeRedisSource.setIp("192.168.0.118");
writeRedisSource.setPort(6379);
writeRedisSource.setPassword("chen");
writeRedisSource.setPoolConfig(config);
sources[0] = readRedisSource;
sources[1] = writeRedisSource;
redisConfig.setSources(sources);
redisConfig.setUseLocalCache(true);
/*
* 分布式多服务 订阅本地缓存,配置此属性,必须开启本地缓存useLocalCache=true
*/
redisConfig.setSubscribeLocalCacheChannel(true);
/**
* 是否开启缓存key分布式锁
*/
redisConfig.setDistributedLock(true);
CacheManager cacheManager = new CacheManager(redisConfig);
return cacheManager;
}
使用说明
使用案例
//-------- Cacheable demo 开始 -------------------------------------------------------------
@Cacheable(key = "#userId",cacheTime = 1000 * 50)
public User get(Integer userId){
return get(userId, null);
}
@Cacheable(key = "#userId",readSourceName = "test1",writeSourceName = "test2")
public User getBySourceName(Integer userId){
return get(userId, null);
}
@Cacheable(key = "#userId",sync = true)
public User getSync(Integer userId){
return get(userId, null);
}
@Caching(cacheable={@Cacheable(key = "#userId"),@Cacheable(key = "#email")})
public User get(Integer userId, String email){
User user = new User();
user.setId(userId);
user.setEmail(email);
user.setName("测试");
user.setCreateTime(new Date());
return user;
}
@Cacheable(resultCacheKey = "id",batch = true)
public ArrayList<User> batchGet(Collection<Integer> userIds){
ArrayList<User> list = new ArrayList<>();
for (Integer userId : userIds) {
User user = new User();
user.setId(userId);
user.setName("批量测试");
user.setCreateTime(new Date());
list.add(user);
}
return list;
}
@Cacheable(resultCacheKey = "id",cacheNull = true,batch = true)
public ArrayList<User> batchGetCacheNull(Collection<Integer> userIds){
return batchGet(userIds);
}
@Cacheable(resultCacheKey = "id",slide = true,batch = true)
public List<User> batchSlide(Collection<Integer> userIds){
return batchGet(userIds);
}
//-------- Cacheable demo 结束 -------------------------------------------------------------
//-------- CachePut demo 开始 -------------------------------------------------------------
@CachePut(cacheNames = "test",resultCacheKey = "id",batch = true)
public List<User> batchPut(Collection<Integer> userIds){
ArrayList<User> list = new ArrayList<>();
for (Integer userId : userIds) {
User user = new User();
user.setId(userId);
user.setName("批量put测试");
user.setCreateTime(new Date());
list.add(user);
}
return list;
}
@Caching(put={@CachePut(resultCacheKey = "userId"),@CachePut(resultCacheKey = "email")})
public List<User> batchPutMuiltResultCacheKey(Collection<Integer> userIds){
return batchPut(userIds);
}
//-------- CachePut demo 结束 -------------------------------------------------------------
//-------- CacheEvict demo 开始 -------------------------------------------------------------
@CacheEvict(key="#userId")
public void remove(Integer userId){
}
@Caching(evict={@CacheEvict(key="#userId"),@CacheEvict(key="#email")})
public void batchRemove(Integer userId,String email){
}
//-------- CacheEvict demo 结束 -------------------------------------------------------------
