一、什么是两级缓存
在项目中。一级缓存用Caffeine,二级缓存用Redis,查询数据时首先查本地的Caffeine缓存,没有命中再通过网络去访问Redis缓存,还是没有命中再查数据库。具体流程如下
二、简单的二级缓存实现-v1
目录结构
2.1 double-cache模块主要文件
pom文件
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>org.example</groupId>
<artifactId>double-cache</artifactId>
<version>1.0-SNAPSHOT</version>
<parent>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-parent</artifactId>
<version>2.7.2</version>
<relativePath/>
</parent>
<properties>
<maven.compiler.source>8</maven.compiler.source>
<maven.compiler.target>8</maven.compiler.target>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
</properties>
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
</dependency>
<dependency>
<groupId>com.github.ben-manes.caffeine</groupId>
<artifactId>caffeine</artifactId>
<version>2.9.2</version>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-redis</artifactId>
</dependency>
</dependencies>
</project>
2.2 测试模块的主要文件
OrderServiceImpl
@Slf4j
@Service
@RequiredArgsConstructor
public class OrderServiceImpl extends ServiceImpl<OrderMapper, Order> implements OrderService {
private final OrderMapper orderMapper;
private final Cache cache;
private final RedisTemplate redisTemplate;
@Override
public Order getOrderById(Long id) {
String key = CacheConstant.ORDER + id;
Order order = (Order) cache.get(key,
k -> {
//先查询 Redis
Object obj = redisTemplate.opsForValue().get(k);
if (Objects.nonNull(obj)) {
log.info("get data from redis");
return obj;
}
// Redis没有则查询 DB
log.info("get data from database");
Order myOrder = orderMapper.selectOne(new LambdaQueryWrapper<Order>()
.eq(Order::getId, id));
redisTemplate.opsForValue().set(k, myOrder, 120, TimeUnit.SECONDS);
return myOrder;
});
return order;
}
@Override
public void updateOrder(Order order) {
log.info("update order data");
String key = CacheConstant.ORDER + order.getId();
orderMapper.updateById(order);
//修改 Redis
redisTemplate.opsForValue().set(key, order, 120, TimeUnit.SECONDS);
// 修改本地缓存
cache.put(key, order);
}
@Override
public void deleteOrder(Long id) {
log.info("delete order");
orderMapper.deleteById(id);
String key = CacheConstant.ORDER + id;
redisTemplate.delete(key);
cache.invalidate(key);
}
}
application.yml
server:
port: 8090
spring:
application:
name: test-demo
datasource:
url: jdbc:mysql://localhost:3306/ktl?useUnicode=true&characterEncoding=UTF-8&serverTimezone=UTC
username: root
password: root
driver-class-name: com.mysql.cj.jdbc.Driver
redis:
host: 192.168.200.131
port: 6379
database: 0
timeout: 10000ms
lettuce:
pool:
max-active: 8
max-wait: -1ms
max-idle: 8
min-idle: 0
password: root
logging:
level:
com.cn.dc: debug
org.springframework: warn
pom文件
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>org.example</groupId>
<artifactId>testcache</artifactId>
<version>1.0-SNAPSHOT</version>
<parent>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-parent</artifactId>
<version>2.7.2</version>
<relativePath/>
</parent>
<properties>
<maven.compiler.source>8</maven.compiler.source>
<maven.compiler.target>8</maven.compiler.target>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<mybatis-plus.version>3.3.2</mybatis-plus.version>
</properties>
<dependencies>
<dependency>
<groupId>org.example</groupId>
<artifactId>double-cache</artifactId>
<version>1.0-SNAPSHOT</version>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
</dependency>
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<scope>runtime</scope>
</dependency>
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-pool2</artifactId>
<version>2.8.1</version>
</dependency>
<dependency>
<groupId>com.baomidou</groupId>
<artifactId>mybatis-plus-boot-starter</artifactId>
<version>${mybatis-plus.version}</version>
</dependency>
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<version>1.18.12</version>
<scope>provided</scope>
</dependency>
</dependencies>
</project>
2.3 测试
测试get/{id}接口的时候,会把从db查出来的数据放入到redis和Caffeine中,在有效期内不需要再次从数据库查询
三、二级缓存实现-v2
v1的代码入侵性很强,因此加入了注解@Cacheable
,@CachePut
,@CacheEvict
3.1 double-cache模块
3.2 测试模块
OrderServiceImpl
@Slf4j
@Service
@RequiredArgsConstructor
public class OrderServiceImpl extends ServiceImpl<OrderMapper, Order> implements OrderService {
private final OrderMapper orderMapper;
private final RedisTemplate redisTemplate;
@Override
@Cacheable(value = "order",key = "#id")
//@Cacheable(cacheNames = "order",key = "#p0")
public Order getOrderById(Long id) {
String key= CacheConstant.ORDER + id;
//先查询 Redis
Object obj = redisTemplate.opsForValue().get(key);
if (Objects.nonNull(obj)){
log.info("get data from redis");
return (Order) obj;
}
// Redis没有则查询 DB
log.info("get data from database");
Order myOrder = orderMapper.selectOne(new LambdaQueryWrapper<Order>()
.eq(Order::getId, id));
redisTemplate.opsForValue().set(key,myOrder,120, TimeUnit.SECONDS);
return myOrder;
}
@Override
@CachePut(cacheNames = "order",key = "#order.id")
public Order updateOrder(Order order) {
log.info("update order data");
orderMapper.updateById(order);
//修改 Redis
redisTemplate.opsForValue().set(CacheConstant.ORDER + order.getId(),
order, 120, TimeUnit.SECONDS);
return order;
}
@Override
@CacheEvict(cacheNames = "order",key = "#id")
public void deleteOrder(Long id) {
log.info("delete order");
orderMapper.deleteById(id);
redisTemplate.delete(CacheConstant.ORDER + id);
}
}
四、二级缓存实现-v3
模仿spring通过注解管理缓存的方式,我们也可以选择自定义注解,然后在切面中处理缓存,从而将对业务代码的入侵降到最低。
首先定义一个注解,用于添加在需要操作缓存的方法上:
@Target(ElementType.METHOD)
@Retention(RetentionPolicy.RUNTIME)
@Documented
public @interface DoubleCache {
String cacheName();
String key(); //支持springEl表达式
long l2TimeOut() default 120;
CacheType type() default CacheType.FULL;
}
我们使用cacheName + key
作为缓存的真正key
(仅存在一个Cache中,不做CacheName隔离),l2TimeOut
为可以设置的二级缓存Redis的过期时间,type
是一个枚举类型的变量,表示操作缓存的类型,枚举类型定义如下:
public enum CacheType {
FULL, //存取
PUT, //只存
DELETE //删除
}
因为要使key
支持springEl
表达式,所以需要写一个方法,使用表达式解析器解析参数:
public class ElParser {
public static String parse(String elString, TreeMap<String,Object> map){
elString=String.format("#{%s}",elString);
//创建表达式解析器
ExpressionParser parser = new SpelExpressionParser();
//通过evaluationContext.setVariable可以在上下文中设定变量。
EvaluationContext context = new StandardEvaluationContext();
map.entrySet().forEach(entry->
context.setVariable(entry.getKey(),entry.getValue())
);
//解析表达式
Expression expression = parser.parseExpression(elString, new TemplateParserContext());
//使用Expression.getValue()获取表达式的值,这里传入了Evaluation上下文
String value = expression.getValue(context, String.class);
return value;
}
}
至于Cache
相关参数的配置,我们沿用V1版本中的配置即可。准备工作做完了,下面我们定义切面,在切面中操作Cache
来读写Caffeine
的缓存,操作RedisTemplate
读写Redis
缓存。
@Slf4j
@Component
@Aspect
@AllArgsConstructor
public class CacheAspect {
private final Cache cache;
private final RedisTemplate redisTemplate;
private final String COLON = ":";
@Pointcut("@annotation(org.example.doublecache.annotation.DoubleCache)")
public void cacheAspect() {
}
@Around("cacheAspect()")
public Object doAround(ProceedingJoinPoint point) throws Throwable {
MethodSignature signature = (MethodSignature) point.getSignature();
Method method = signature.getMethod();
// if (!method.isAnnotationPresent(DoubleCache.class))
// return null;
//拼接解析springEl表达式的map
String[] paramNames = signature.getParameterNames();
Object[] args = point.getArgs();
TreeMap<String, Object> treeMap = new TreeMap<>();
for (int i = 0; i < paramNames.length; i++) {
treeMap.put(paramNames[i],args[i]);
}
DoubleCache annotation = method.getAnnotation(DoubleCache.class);
String elResult = ElParser.parse(annotation.key(), treeMap);
String realKey = annotation.cacheName() + COLON + elResult;
//强制更新
if (annotation.type()== CacheType.PUT){
Object object = point.proceed();
redisTemplate.opsForValue().set(realKey, object,annotation.l2TimeOut(), TimeUnit.SECONDS);
cache.put(realKey, object);
return object;
}
//删除
else if (annotation.type()== CacheType.DELETE){
redisTemplate.delete(realKey);
cache.invalidate(realKey);
return point.proceed();
}
//读写,查询Caffeine
Object caffeineCache = cache.getIfPresent(realKey);
if (Objects.nonNull(caffeineCache)) {
log.info("get data from caffeine");
return caffeineCache;
}
//查询Redis
Object redisCache = redisTemplate.opsForValue().get(realKey);
if (Objects.nonNull(redisCache)) {
log.info("get data from redis");
cache.put(realKey, redisCache);
return redisCache;
}
log.info("get data from database");
Object object = point.proceed();
if (Objects.nonNull(object)){
//写回Redis
redisTemplate.opsForValue().set(realKey, object,annotation.l2TimeOut(), TimeUnit.SECONDS);
//写入Caffeine
cache.put(realKey, object);
}
return object;
}
}
4.1 double-cache模块
4.2 测试模块
OrderServiceImpl
修改如下
@Slf4j
@Service
@RequiredArgsConstructor
public class OrderServiceImpl extends ServiceImpl<OrderMapper, Order> implements OrderService {
private final OrderMapper orderMapper;
@Override
@DoubleCache(cacheName = "order", key = "#id",
type = CacheType.FULL)
public Order getOrderById(Long id) {
Order myOrder = orderMapper.selectOne(new LambdaQueryWrapper<Order>()
.eq(Order::getId, id));
return myOrder;
}
@Override
@DoubleCache(cacheName = "order",key = "#order.id",
type = CacheType.PUT)
public Order updateOrder(Order order) {
orderMapper.updateById(order);
return order;
}
@Override
@DoubleCache(cacheName = "order",key = "#id",
type = CacheType.DELETE)
public void deleteOrder(Long id) {
orderMapper.deleteById(id);
}
@Override
@DoubleCache(cacheName = "order",key = "#id")
public Order getOrderByIdAndStatus(Long id,Integer status) {
Order myOrder = orderMapper.selectOne(new LambdaQueryWrapper<Order>()
.eq(Order::getId, id)
.eq(Order::getStatus,status));
return myOrder;
}
在TestApplication
上加@EnableCaching
4.3 测试
从数据库10ms+,生产中会走网络通信会更长。
从Caffeine平均4ms