Repository: TaXueWWL/shield-ratelimter
Branch: master
Commit: 117fc7f269cc
Files: 29
Total size: 154.4 KB
Directory structure:
gitextract_xsb3h930/
├── .gitignore
├── .idea/
│ ├── .name
│ ├── codeStyles/
│ │ └── codeStyleConfig.xml
│ ├── compiler.xml
│ ├── dataSources.local.xml
│ ├── dataSources.xml
│ ├── encodings.xml
│ ├── inspectionProfiles/
│ │ └── Project_Default.xml
│ ├── misc.xml
│ ├── vcs.xml
│ └── workspace.xml
├── CHANGELOG
├── LICENSE
├── README.md
├── pom.xml
├── shield-ratelimiter-core/
│ ├── pom.xml
│ ├── src/
│ │ └── main/
│ │ ├── java/
│ │ │ └── com/
│ │ │ └── snowalker/
│ │ │ └── shield/
│ │ │ └── ratelimiter/
│ │ │ └── core/
│ │ │ ├── annotation/
│ │ │ │ └── RateLimiter.java
│ │ │ ├── handler/
│ │ │ │ └── RateLimterHandler.java
│ │ │ └── redis/
│ │ │ └── RedisCacheConfig.java
│ │ └── resources/
│ │ ├── application.properties
│ │ └── rateLimter.lua
│ └── target/
│ └── classes/
│ ├── application.properties
│ └── rateLimter.lua
├── shield-ratelimiter.iml
└── shleld-ratelimter-demo/
├── pom.xml
├── src/
│ └── main/
│ ├── java/
│ │ └── com/
│ │ └── snowalker/
│ │ └── ratelimiter/
│ │ └── demo/
│ │ ├── Application.java
│ │ └── controller/
│ │ └── TestController.java
│ └── resources/
│ └── application.properties
└── target/
└── classes/
└── application.properties
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FILE CONTENTS
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FILE: .gitignore
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# Compiled class file
*.class
# Log file
*.log
# BlueJ files
*.ctxt
# Mobile Tools for Java (J2ME)
.mtj.tmp/
# Package Files #
*.jar
*.war
*.nar
*.ear
*.zip
*.tar.gz
*.rar
# virtual machine crash logs, see http://www.java.com/en/download/help/error_hotspot.xml
hs_err_pid*
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FILE: .idea/.name
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shieldratelimiter
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FILE: .idea/codeStyles/codeStyleConfig.xml
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FILE: .idea/compiler.xml
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FILE: .idea/dataSources.local.xml
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master_keytruemarketing
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FILE: .idea/dataSources.xml
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mysqltruecom.mysql.jdbc.Driverjdbc:mysql://172.30.61.15:3306
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FILE: .idea/encodings.xml
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FILE: .idea/inspectionProfiles/Project_Default.xml
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FILE: .idea/misc.xml
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FILE: .idea/vcs.xml
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com.gaoyang.marketing.maccbasecore.*用户账户信息查询失败queryWebNoticeCrouselBannerListqueryWebNoticePopupBoxesListQueryNoticeInfoListDOqueryNoticeInfoListinsertPrizeInfoqueryPrizeInfoListbalanceCurTotalqueryChargedAccBalanceRecorde.printStackTrace()createNoticeInfoaddChargeAccountBalanceaccCurrBalanceupdateSpecialChargeAccount冲正needRollbackTradeAmountbalanceLasttradeAmountRealProductTypeInfoModelProductInfoBizServiceImplqueryAllBalanceRecordList清零versionchargeAccountData.getExtMsg()extMsgqueryAccountBalanceListDataChargeNotifyLocalModelSpecialChargeLocalModelrulerChargeUtilschargeExtMsgisBlankqueryNoticeInfoListDataOutQueryNoticeInfoModelCreateNoticeInfoDataUpdateNoticeInfoDataOutCreateNoticeInfoModelOutUpdateNoticeInfoModelCreateNoticeInfoDOCreateNoticeInfoDobjQueryNoticeInfoListDOQueryNoticeInfoDobjgetNextValueByAscLongChargeNotifyAcmConfigSpecialChargeAcmConfigD:\snowalker-workspace\0mkt-workspace\maccbasecore\maccbasecore-serviceD:\snowalker-workspace\0mkt-workspace\mfbizcoreD:\snowalker-workspace\0mkt-workspace\maccbasecoretrueDEFINITION_ORDERAbstraction issuesJavaAli-CheckAndroidCode style issuesJavaCompiler issuesJavaCorrectnessLintAndroidFinalizationJavaGeneralJavaScriptGoogle Web ToolkitGroovyIconsUsabilityLintAndroidInheritance issuesJavaInternationalizationInternationalizationJavaInternationalizationLintAndroidJ2ME issuesJavaJSPJavaJava 5Java language level migration aidsJavaJava 9Java language level migration aidsJavaJava interop issuesKotlinJava language level migration aidsJavaJavaBeans issuesJavaJavaScriptKotlinLintAndroidNumeric issuesJavaOtherGroovyPerformanceJavaPerformanceLintAndroidProbable bugsJavaProbable bugsKotlinSecurityJavaSecurityLintAndroidSerialization issuesJavaUsabilityLintAndroidVerbose or redundant code constructsJavaWebSocketJSP154057234605715405723460571540814643793154081464379315419881619971541988161997permission:warSpring (maccbasecore-service)|Spring1.8maccbasecore-service1.8Maven: aopalliance:aopalliance:1.0
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FILE: CHANGELOG
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2018-10-29
1. 增加限流提示自定义属性,message(),不填默认为“false”
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FILE: LICENSE
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================================================
FILE: README.md
================================================
# shield-ratelimiter
> 基于Redis的分布式限流工具包
在分布式领域，我们难免会遇到并发量突增，对后端服务造成高压力，严重甚至会导致系统宕机。为避免这种问题，我们通常会为接口添加限流、降级、熔断等能力，从而使接口更为健壮。Java领域常见的开源组件有Netflix的hystrix，阿里系开源的sentinel等，都是蛮不错的限流熔断框架。
今天我们就基于Redis组件的特性，实现一个分布式限流组件，名字就定为shield-ratelimiter。
## 原理
首先解释下为何采用Redis作为限流组件的核心。
通俗地讲，假设一个用户（用IP判断）每秒访问某服务接口的次数不能超过10次，那么我们可以在Redis中创建一个键，并设置键的过期时间为60秒。
当一个用户对此服务接口发起一次访问就把键值加1，在单位时间（此处为1s）内当键值增加到10的时候，就禁止访问服务接口。PS:在某种场景中添加访问时间间隔还是很有必要的。我们本次不考虑间隔时间，只关注单位时间内的访问次数。
## 需求
原理已经讲过了，说下需求。
1. 基于Redis的incr及过期机制开发
2. 调用方便，声明式
3. Spring支持
基于上述需求，我们决定基于注解方式进行核心功能开发，基于Spring-boot-starter作为基础环境，从而能够很好的适配Spring环境。
另外，在本次开发中，我们不通过简单的调用Redis的java类库API实现对Redis的incr操作。
原因在于，我们要保证整个限流的操作是原子性的，如果用Java代码去做操作及判断，会有并发问题。这里我决定采用Lua脚本进行核心逻辑的定义。
## 为何使用Lua
在正式开发前，我简单介绍下对Redis的操作中，为何推荐使用Lua脚本。
1. 减少网络开销: 不使用 Lua 的代码需要向 Redis 发送多次请求, 而脚本只需一次即可, 减少网络传输;
2. 原子操作: Redis 将整个脚本作为一个原子执行, 无需担心并发, 也就无需事务;
3. 复用: 脚本会永久保存 Redis 中, 其他客户端可继续使用.
Redis添加了对Lua的支持，能够很好的满足原子性、事务性的支持，让我们免去了很多的异常逻辑处理。对于Lua的语法不是本文的主要内容，感兴趣的可以自行查找资料。
## 正式开发
到这里，我们正式开始手写限流组件的进程。
### 1. 工程定义
项目基于maven构建，主要依赖Spring-boot-starter，我们主要在springboot上进行开发，因此自定义的开发包可以直接依赖下面这个坐标，方便进行包管理。版本号自行选择稳定版。
org.springframework.bootspring-boot-starter1.4.2.RELEASE
### 2. Redis整合
由于我们是基于Redis进行的限流操作，因此需要整合Redis的类库，上面已经讲到，我们是基于Springboot进行的开发，因此这里可以直接整合RedisTemplate。
#### 2.1 坐标引入
这里我们引入spring-boot-starter-redis的依赖。
org.springframework.bootspring-boot-starter-redis1.4.2.RELEASE
#### 2.2 注入CacheManager及RedisTemplate
新建一个Redis的配置类，命名为RedisCacheConfig，使用javaconfig形式注入CacheManager及RedisTemplate。为了操作方便，我们采用了Jackson进行序列化。代码如下
@Configuration
@EnableCaching
public class RedisCacheConfig {
private static final Logger LOGGER = LoggerFactory.getLogger(RedisCacheConfig.class);
@Bean
public CacheManager cacheManager(RedisTemplate redisTemplate) {
CacheManager cacheManager = new RedisCacheManager(redisTemplate);
if (LOGGER.isDebugEnabled()) {
LOGGER.debug("Springboot Redis cacheManager 加载完成");
}
return cacheManager;
}
@Bean
public RedisTemplate redisTemplate(RedisConnectionFactory factory) {
RedisTemplate template = new RedisTemplate<>();
template.setConnectionFactory(factory);
//使用Jackson2JsonRedisSerializer来序列化和反序列化redis的value值（默认使用JDK的序列化方式）
Jackson2JsonRedisSerializer serializer = new Jackson2JsonRedisSerializer(Object.class);
ObjectMapper mapper = new ObjectMapper();
mapper.setVisibility(PropertyAccessor.ALL, JsonAutoDetect.Visibility.ANY);
mapper.enableDefaultTyping(ObjectMapper.DefaultTyping.NON_FINAL);
serializer.setObjectMapper(mapper);
template.setValueSerializer(serializer);
//使用StringRedisSerializer来序列化和反序列化redis的key值
template.setKeySerializer(new StringRedisSerializer());
template.afterPropertiesSet();
LOGGER.info("Springboot RedisTemplate 加载完成");
return template;
}
}
**注意** 要使用 **@Configuration** 标注此类为一个配置类，当然你可以使用 **@Component**， 但是不推荐，原因在于 **@Component** 注解虽然也可以当作配置类，但是并不会为其生成CGLIB代理Class，而使用**@Configuration**，CGLIB会为其生成代理类，进行性能的提升。
#### 2.3 调用方application.propertie需要增加Redis配置
我们的包开发完毕之后，调用方的application.properties需要进行相关配置如下：
#单机模式redis
spring.redis.host=127.0.0.1
spring.redis.port=6379
spring.redis.pool.maxActive=8
spring.redis.pool.maxWait=-1
spring.redis.pool.maxIdle=8
spring.redis.pool.minIdle=0
spring.redis.timeout=10000
spring.redis.password=
如果有密码的话，配置password即可。
这里为单机配置，如果需要支持哨兵集群，则配置如下，Java代码不需要改动，只需要变动配置即可。**注意** 两种配置不能共存！
#哨兵集群模式
# database name
spring.redis.database=0
# server password 密码，如果没有设置可不配
spring.redis.password=
# pool settings ...池配置
spring.redis.pool.max-idle=8
spring.redis.pool.min-idle=0
spring.redis.pool.max-active=8
spring.redis.pool.max-wait=-1
# name of Redis server 哨兵监听的Redis server的名称
spring.redis.sentinel.master=mymaster
# comma-separated list of host:port pairs 哨兵的配置列表
spring.redis.sentinel.nodes=127.0.0.1:26379,127.0.0.1:26479,127.0.0.1:26579
### 3. 定义注解
为了调用方便，我们定义一个名为**RateLimiter** 的注解，内容如下
/**
* @author snowalker
* @version 1.0
* @date 2018/10/27 1:25
* @className RateLimiter
* @desc 限流注解
*/
@Target(ElementType.METHOD)
@Retention(RetentionPolicy.RUNTIME)
@Documented
public @interface RateLimiter {
/**
* 限流key
* @return
*/
String key() default "rate:limiter";
/**
* 单位时间限制通过请求数
* @return
*/
long limit() default 10;
/**
* 过期时间，单位秒
* @return
*/
long expire() default 1;
}
该注解明确只用于方法，主要有三个属性。
1. key--表示限流模块名，指定该值用于区分不同应用，不同场景，推荐格式为：应用名:模块名:ip:接口名:方法名
2. limit--表示单位时间允许通过的请求数
3. expire--incr的值的过期时间，业务中表示限流的单位时间。
### 4. 解析注解
定义好注解后，需要开发注解使用的切面，这里我们直接使用aspectj进行切面的开发。先看代码
@Aspect
@Component
public class RateLimterHandler {
private static final Logger LOGGER = LoggerFactory.getLogger(RateLimterHandler.class);
@Autowired
RedisTemplate redisTemplate;
private DefaultRedisScript getRedisScript;
@PostConstruct
public void init() {
getRedisScript = new DefaultRedisScript<>();
getRedisScript.setResultType(Long.class);
getRedisScript.setScriptSource(new ResourceScriptSource(new ClassPathResource("rateLimter.lua")));
LOGGER.info("RateLimterHandler[分布式限流处理器]脚本加载完成");
}
这里是注入了RedisTemplate，使用其API进行Lua脚本的调用。
init() 方法在应用启动时会初始化DefaultRedisScript，并加载Lua脚本，方便进行调用。
PS: Lua脚本放置在classpath下，通过ClassPathResource进行加载。
@Pointcut("@annotation(com.snowalker.shield.ratelimiter.core.annotation.RateLimiter)")
public void rateLimiter() {}
这里我们定义了一个切点，表示只要注解了 **@RateLimiter** 的方法，均可以触发限流操作。
@Around("@annotation(rateLimiter)")
public Object around(ProceedingJoinPoint proceedingJoinPoint, RateLimiter rateLimiter) throws Throwable {
if (LOGGER.isDebugEnabled()) {
LOGGER.debug("RateLimterHandler[分布式限流处理器]开始执行限流操作");
}
Signature signature = proceedingJoinPoint.getSignature();
if (!(signature instanceof MethodSignature)) {
throw new IllegalArgumentException("the Annotation @RateLimter must used on method!");
}
/**
* 获取注解参数
*/
// 限流模块key
String limitKey = rateLimiter.key();
Preconditions.checkNotNull(limitKey);
// 限流阈值
long limitTimes = rateLimiter.limit();
// 限流超时时间
long expireTime = rateLimiter.expire();
if (LOGGER.isDebugEnabled()) {
LOGGER.debug("RateLimterHandler[分布式限流处理器]参数值为-limitTimes={},limitTimeout={}", limitTimes, expireTime);
}
/**
* 执行Lua脚本
*/
List keyList = new ArrayList();
// 设置key值为注解中的值
keyList.add(limitKey);
/**
* 调用脚本并执行
*/
Long result = (Long) redisTemplate.execute(getRedisScript, keyList, expireTime, limitTimes);
if (result == 0) {
String msg = "由于超过单位时间=" + expireTime + "-允许的请求次数=" + limitTimes + "[触发限流]";
LOGGER.debug(msg);
return "false";
}
if (LOGGER.isDebugEnabled()) {
LOGGER.debug("RateLimterHandler[分布式限流处理器]限流执行结果-result={},请求[正常]响应", result);
}
return proceedingJoinPoint.proceed();
}
}
这段代码的逻辑为，获取 **@RateLimiter** 注解配置的属性：key、limit、expire，并通过 **redisTemplate.execute(RedisScript script, List keys, Object... args)** 方法传递给Lua脚本进行限流相关操作，逻辑很清晰。
这里我们定义如果脚本返回状态为0则为触发限流，1表示正常请求。
### 5. Lua脚本
这里是我们整个限流操作的核心，通过执行一个Lua脚本进行限流的操作。脚本内容如下
--获取KEY
local key1 = KEYS[1]
local val = redis.call('incr', key1)
local ttl = redis.call('ttl', key1)
--获取ARGV内的参数并打印
local expire = ARGV[1]
local times = ARGV[2]
redis.log(redis.LOG_DEBUG,tostring(times))
redis.log(redis.LOG_DEBUG,tostring(expire))
redis.log(redis.LOG_NOTICE, "incr "..key1.." "..val);
if val == 1 then
redis.call('expire', key1, tonumber(expire))
else
if ttl == -1 then
redis.call('expire', key1, tonumber(expire))
end
end
if val > tonumber(times) then
return 0
end
return 1
逻辑很通俗，我简单介绍下。
1. 首先脚本获取Java代码中传递而来的要限流的模块的key，不同的模块key值一定不能相同，否则会覆盖！
2. redis.call('incr', key1)对传入的key做incr操作，如果key首次生成，设置超时时间ARGV[1]；（初始值为1）
3. ttl是为防止某些key在未设置超时时间并长时间已经存在的情况下做的保护的判断；
4. 每次请求都会做+1操作，当限流的值val大于我们注解的阈值，则返回0表示已经超过请求限制，触发限流。否则为正常请求。
当过期后，又是新的一轮循环，整个过程是一个原子性的操作，能够保证单位时间不会超过我们预设的请求阈值。
到这里我们便可以在项目中进行测试。
## 测试
[demo地址](https://github.com/TaXueWWL/shleld-ratelimter/tree/master/shleld-ratelimter-demo)
这里我贴一下核心代码，我们定义一个接口，并注解 **@RateLimiter(key = "ratedemo:1.0.0", limit = 5, expire = 100)** 表示模块ratedemo:sendPayment:1.0.0
在100s内允许通过5个请求，这里的参数设置是为了方便看结果。实际中，我们通常会设置1s内允许通过的次数。
@Controller
public class TestController {
private static final Logger LOGGER = LoggerFactory.getLogger(TestController.class);
@ResponseBody
@RequestMapping("ratelimiter")
@RateLimiter(key = "ratedemo:1.0.0", limit = 5, expire = 100)
public String sendPayment(HttpServletRequest request) throws Exception {
return "正常请求";
}
}
我们通过RestClient请求接口，日志返回如下：
2018-10-28 00:00:00.602 DEBUG 17364 --- [nio-8888-exec-1] c.s.s.r.core.handler.RateLimterHandler :
RateLimterHandler[分布式限流处理器]开始执行限流操作
2018-10-28 00:00:00.688 DEBUG 17364 --- [nio-8888-exec-1] c.s.s.r.core.handler.RateLimterHandler :
RateLimterHandler[分布式限流处理器]限流执行结果-result=1,请求[正常]响应
2018-10-28 00:00:00.860 DEBUG 17364 --- [nio-8888-exec-3] c.s.s.r.core.handler.RateLimterHandler :
RateLimterHandler[分布式限流处理器]开始执行限流操作
2018-10-28 00:00:01.183 DEBUG 17364 --- [nio-8888-exec-4] c.s.s.r.core.handler.RateLimterHandler :
RateLimterHandler[分布式限流处理器]开始执行限流操作
2018-10-28 00:00:01.520 DEBUG 17364 --- [nio-8888-exec-3] c.s.s.r.core.handler.RateLimterHandler :
RateLimterHandler[分布式限流处理器]限流执行结果-result=1,请求[正常]响应
2018-10-28 00:00:01.521 DEBUG 17364 --- [nio-8888-exec-4] c.s.s.r.core.handler.RateLimterHandler :
RateLimterHandler[分布式限流处理器]限流执行结果-result=1,请求[正常]响应
2018-10-28 00:00:01.557 DEBUG 17364 --- [nio-8888-exec-5] c.s.s.r.core.handler.RateLimterHandler :
RateLimterHandler[分布式限流处理器]开始执行限流操作
2018-10-28 00:00:01.558 DEBUG 17364 --- [nio-8888-exec-5] c.s.s.r.core.handler.RateLimterHandler :
RateLimterHandler[分布式限流处理器]限流执行结果-result=1,请求[正常]响应
2018-10-28 00:00:01.774 DEBUG 17364 --- [nio-8888-exec-7] c.s.s.r.core.handler.RateLimterHandler :
RateLimterHandler[分布式限流处理器]开始执行限流操作
2018-10-28 00:00:02.111 DEBUG 17364 --- [nio-8888-exec-8] c.s.s.r.core.handler.RateLimterHandler :
RateLimterHandler[分布式限流处理器]开始
2018-10-28 00:00:02.169 DEBUG 17364 --- [nio-8888-exec-7] c.s.s.r.core.handler.RateLimterHandler :
RateLimterHandler[分布式限流处理器]限流执行结果-result=1,请求[正常]响应
2018-10-28 00:00:02.169 DEBUG 17364 --- [nio-8888-exec-8] c.s.s.r.core.handler.RateLimterHandler :
由于超过单位时间=100-允许的请求次数=5[触发限流]
2018-10-28 00:00:02.276 DEBUG 17364 --- [io-8888-exec-10] c.s.s.r.core.handler.RateLimterHandler :
RateLimterHandler[分布式限流处理器]开始执行限流操作
2018-10-28 00:00:02.276 DEBUG 17364 --- [io-8888-exec-10] c.s.s.r.core.handler.RateLimterHandler :
RateLimterHandler[分布式限流处理器]参数值为-limitTimes=5,limitTimeout=100
2018-10-28 00:00:02.278 DEBUG 17364 --- [io-8888-exec-10] c.s.s.r.core.handler.RateLimterHandler :
由于超过单位时间=100-允许的请求次数=5[触发限流]
2018-10-28 00:00:02.445 DEBUG 17364 --- [nio-8888-exec-2] c.s.s.r.core.handler.RateLimterHandler :
RateLimterHandler[分布式限流处理器]开始执行限流操作
2018-10-28 00:00:02.445 DEBUG 17364 --- [nio-8888-exec-2] c.s.s.r.core.handler.RateLimterHandler :
RateLimterHandler[分布式限流处理器]参数值为-limitTimes=5,limitTimeout=100
2018-10-28 00:00:02.446 DEBUG 17364 --- [nio-8888-exec-2] c.s.s.r.core.handler.RateLimterHandler :
由于超过单位时间=100-允许的请求次数=5[触发限流]
2018-10-28 00:00:02.628 DEBUG 17364 --- [nio-8888-exec-4] c.s.s.r.core.handler.RateLimterHandler :
RateLimterHandler[分布式限流处理器]开始执行限流操作
2018-10-28 00:00:02.628 DEBUG 17364 --- [nio-8888-exec-4] c.s.s.r.core.handler.RateLimterHandler :
RateLimterHandler[分布式限流处理器]参数值为-limitTimes=5,limitTimeout=100
2018-10-28 00:00:02.629 DEBUG 17364 --- [nio-8888-exec-4] c.s.s.r.core.handler.RateLimterHandler :
由于超过单位时间=100-允许的请求次数=5[触发限流]
根据日志能够看到，正常请求5次后，返回限流触发，说明我们的逻辑生效，对前端而言也是可以看到false标记，表明我们的Lua脚本限流逻辑是正确的，这里具体返回什么标记需要调用方进行明确的定义。
## 总结
我们通过Redis的incr及expire功能特性，开发定义了一套基于注解的分布式限流操作，核心逻辑基于Lua保证了原子性。达到了很好的限流的目的，生产上，可以基于该特点进行定制自己的限流组件，当然你可以参考本文的代码，相信你写的一定比我的demo更好！
================================================
FILE: pom.xml
================================================
4.0.0com.snowalkershield-ratelimiter1.0-SNAPSHOTshield-ratelimiter-coreshleld-ratelimter-demopom
================================================
FILE: shield-ratelimiter-core/pom.xml
================================================
shield-ratelimitercom.snowalker1.0-SNAPSHOT4.0.0shield-ratelimiter-coreshield-ratelimiter-corecom.snowalker1.0-SNAPSHOT1.81.81.81.4.2.RELEASEorg.springframework.bootspring-boot-starter${spring.boot.version}org.springframework.bootspring-boot-starter-data-redis${spring.boot.version}org.springframework.bootspring-boot-starter-aop${spring.boot.version}org.apache.commonscommons-lang33.7com.google.guavaguava26.0-jrejunitjunit4.12testcom.fasterxml.jackson.corejackson-databind2.9.6
================================================
FILE: shield-ratelimiter-core/src/main/java/com/snowalker/shield/ratelimiter/core/annotation/RateLimiter.java
================================================
package com.snowalker.shield.ratelimiter.core.annotation;
import java.lang.annotation.*;
/**
* @author snowalker
* @version 1.0
* @date 2018/10/27 1:25
* @className RateLimiter
* @desc 限流注解
*/
@Target(ElementType.METHOD)
@Retention(RetentionPolicy.RUNTIME)
@Documented
public @interface RateLimiter {
/**
* 限流key
* @return
*/
String key() default "rate:limiter";
/**
* 单位时间限制通过请求数
* @return
*/
long limit() default 10;
/**
* 过期时间，单位秒
* @return
*/
long expire() default 1;
/**
* 限流提示语
* @return
*/
String message() default "false";
}
================================================
FILE: shield-ratelimiter-core/src/main/java/com/snowalker/shield/ratelimiter/core/handler/RateLimterHandler.java
================================================
package com.snowalker.shield.ratelimiter.core.handler;
import com.google.common.base.Preconditions;
import com.snowalker.shield.ratelimiter.core.annotation.RateLimiter;
import org.apache.commons.lang3.StringUtils;
import org.aspectj.lang.ProceedingJoinPoint;
import org.aspectj.lang.Signature;
import org.aspectj.lang.annotation.Around;
import org.aspectj.lang.annotation.Aspect;
import org.aspectj.lang.annotation.Pointcut;
import org.aspectj.lang.reflect.MethodSignature;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.core.io.ClassPathResource;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.core.script.DefaultRedisScript;
import org.springframework.scripting.support.ResourceScriptSource;
import org.springframework.stereotype.Component;
import javax.annotation.PostConstruct;
import java.util.ArrayList;
import java.util.List;
/**
* @author snowalker
* @version 1.0
* @date 2018/10/27 1:17
* @className RateLimterHandler
* @desc 限流处理器
*/
@Aspect
@Component
public class RateLimterHandler {
private static final Logger LOGGER = LoggerFactory.getLogger(RateLimterHandler.class);
@Autowired
RedisTemplate redisTemplate;
private DefaultRedisScript getRedisScript;
@PostConstruct
public void init() {
getRedisScript = new DefaultRedisScript<>();
getRedisScript.setResultType(Long.class);
getRedisScript.setScriptSource(new ResourceScriptSource(new ClassPathResource("rateLimter.lua")));
LOGGER.info("RateLimterHandler[分布式限流处理器]脚本加载完成");
}
@Pointcut("@annotation(com.snowalker.shield.ratelimiter.core.annotation.RateLimiter)")
public void rateLimiter() {}
@Around("@annotation(rateLimiter)")
public Object around(ProceedingJoinPoint proceedingJoinPoint, RateLimiter rateLimiter) throws Throwable {
if (LOGGER.isDebugEnabled()) {
LOGGER.debug("RateLimterHandler[分布式限流处理器]开始执行限流操作");
}
Signature signature = proceedingJoinPoint.getSignature();
if (!(signature instanceof MethodSignature)) {
throw new IllegalArgumentException("the Annotation @RateLimter must used on method!");
}
/**
* 获取注解参数
*/
// 限流模块key
String limitKey = rateLimiter.key();
Preconditions.checkNotNull(limitKey);
// 限流阈值
long limitTimes = rateLimiter.limit();
// 限流超时时间
long expireTime = rateLimiter.expire();
if (LOGGER.isDebugEnabled()) {
LOGGER.debug("RateLimterHandler[分布式限流处理器]参数值为-limitTimes={},limitTimeout={}", limitTimes, expireTime);
}
// 限流提示语
String message = rateLimiter.message();
if (StringUtils.isBlank(message)) {
message = "false";
}
/**
* 执行Lua脚本
*/
List keyList = new ArrayList();
// 设置key值为注解中的值
keyList.add(limitKey);
/**
* 调用脚本并执行
*/
Long result = (Long) redisTemplate.execute(getRedisScript, keyList, expireTime, limitTimes);
if (result == 0) {
String msg = "由于超过单位时间=" + expireTime + "-允许的请求次数=" + limitTimes + "[触发限流]";
LOGGER.debug(msg);
return message;
}
if (LOGGER.isDebugEnabled()) {
LOGGER.debug("RateLimterHandler[分布式限流处理器]限流执行结果-result={},请求[正常]响应", result);
}
return proceedingJoinPoint.proceed();
}
}
================================================
FILE: shield-ratelimiter-core/src/main/java/com/snowalker/shield/ratelimiter/core/redis/RedisCacheConfig.java
================================================
package com.snowalker.shield.ratelimiter.core.redis;
import com.fasterxml.jackson.annotation.JsonAutoDetect;
import com.fasterxml.jackson.annotation.PropertyAccessor;
import com.fasterxml.jackson.databind.ObjectMapper;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.cache.CacheManager;
import org.springframework.cache.annotation.EnableCaching;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.redis.cache.RedisCacheManager;
import org.springframework.data.redis.connection.RedisConnectionFactory;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.serializer.Jackson2JsonRedisSerializer;
import org.springframework.data.redis.serializer.StringRedisSerializer;
/**
* @author snowalker
* @version 1.0
* @date 2018/10/27 1:15
* @className RedisCacheConfig
* @desc Redis配置
*/
@Configuration
@EnableCaching
public class RedisCacheConfig {
private static final Logger LOGGER = LoggerFactory.getLogger(RedisCacheConfig.class);
@Bean
public CacheManager cacheManager(RedisTemplate redisTemplate) {
CacheManager cacheManager = new RedisCacheManager(redisTemplate);
if (LOGGER.isDebugEnabled()) {
LOGGER.debug("Springboot Redis cacheManager 加载完成");
}
return cacheManager;
}
@Bean
public RedisTemplate redisTemplate(RedisConnectionFactory factory) {
RedisTemplate template = new RedisTemplate<>();
template.setConnectionFactory(factory);
//使用Jackson2JsonRedisSerializer来序列化和反序列化redis的value值（默认使用JDK的序列化方式）
Jackson2JsonRedisSerializer serializer = new Jackson2JsonRedisSerializer(Object.class);
ObjectMapper mapper = new ObjectMapper();
mapper.setVisibility(PropertyAccessor.ALL, JsonAutoDetect.Visibility.ANY);
mapper.enableDefaultTyping(ObjectMapper.DefaultTyping.NON_FINAL);
serializer.setObjectMapper(mapper);
template.setValueSerializer(serializer);
//使用StringRedisSerializer来序列化和反序列化redis的key值
template.setKeySerializer(new StringRedisSerializer());
template.afterPropertiesSet();
LOGGER.info("Springboot RedisTemplate 加载完成");
return template;
}
}
================================================
FILE: shield-ratelimiter-core/src/main/resources/application.properties
================================================
#redis
spring.redis.hostName=127.0.0.1
spring.redis.host=127.0.0.1
spring.redis.port=6379
spring.redis.pool.maxActive=8
spring.redis.pool.maxWait=-1
spring.redis.pool.maxIdle=8
spring.redis.pool.minIdle=0
spring.redis.timeout=10000
spring.redis.password=
logging.path=D:/log/maccbasecore
================================================
FILE: shield-ratelimiter-core/src/main/resources/rateLimter.lua
================================================
--获取KEY
local key1 = KEYS[1]
local val = redis.call('incr', key1)
local ttl = redis.call('ttl', key1)
--获取ARGV内的参数并打印
local expire = ARGV[1]
local times = ARGV[2]
redis.log(redis.LOG_DEBUG,tostring(times))
redis.log(redis.LOG_DEBUG,tostring(expire))
redis.log(redis.LOG_NOTICE, "incr "..key1.." "..val);
if val == 1 then
redis.call('expire', key1, tonumber(expire))
else
if ttl == -1 then
redis.call('expire', key1, tonumber(expire))
end
end
if val > tonumber(times) then
return 0
end
return 1
================================================
FILE: shield-ratelimiter-core/target/classes/application.properties
================================================
#redis
spring.redis.hostName=127.0.0.1
spring.redis.host=127.0.0.1
spring.redis.port=6379
spring.redis.pool.maxActive=8
spring.redis.pool.maxWait=-1
spring.redis.pool.maxIdle=8
spring.redis.pool.minIdle=0
spring.redis.timeout=10000
spring.redis.password=
logging.path=D:/log/maccbasecore
================================================
FILE: shield-ratelimiter-core/target/classes/rateLimter.lua
================================================
--获取KEY
local key1 = KEYS[1]
local val = redis.call('incr', key1)
local ttl = redis.call('ttl', key1)
--获取ARGV内的参数并打印
local expire = ARGV[1]
local times = ARGV[2]
redis.log(redis.LOG_DEBUG,tostring(times))
redis.log(redis.LOG_DEBUG,tostring(expire))
redis.log(redis.LOG_NOTICE, "incr "..key1.." "..val);
if val == 1 then
redis.call('expire', key1, tonumber(expire))
else
if ttl == -1 then
redis.call('expire', key1, tonumber(expire))
end
end
if val > tonumber(times) then
return 0
end
return 1
================================================
FILE: shield-ratelimiter.iml
================================================
================================================
FILE: shleld-ratelimter-demo/pom.xml
================================================
4.0.0shleld-ratelimter-demoorg.springframework.bootspring-boot-starter-parent1.4.2.RELEASEUTF-8UTF-81.8org.springframework.bootspring-boot-starter-weborg.springframework.bootspring-boot-starter-testtestshield-ratelimiter-corecom.snowalker1.0-SNAPSHOT
================================================
FILE: shleld-ratelimter-demo/src/main/java/com/snowalker/ratelimiter/demo/Application.java
================================================
package com.snowalker.ratelimiter.demo;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.context.ConfigurableApplicationContext;
import org.springframework.context.annotation.ComponentScan;
import org.springframework.scheduling.annotation.EnableScheduling;
@EnableScheduling
@SpringBootApplication
@ComponentScan(basePackages = {"com.snowalker"})
public class Application {
private static final Logger LOGGER = LoggerFactory.getLogger(Application.class);
public static void main(String[] args) throws Exception {
ConfigurableApplicationContext context = SpringApplication.run(Application.class, args);
}
}
================================================
FILE: shleld-ratelimter-demo/src/main/java/com/snowalker/ratelimiter/demo/controller/TestController.java
================================================
package com.snowalker.ratelimiter.demo.controller;
import com.snowalker.shield.ratelimiter.core.annotation.RateLimiter;
import org.apache.catalina.servlet4preview.http.HttpServletRequest;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.stereotype.Controller;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.ResponseBody;
/**
* @author snowalker
* @version 1.0
* @date 2018/10/27 2:13
* @className
* @desc
*/
@Controller
public class TestController {
private static final Logger LOGGER = LoggerFactory.getLogger(TestController.class);
private static final String MESSAGE = "{\"code\":\"400\",\"msg\":\"FAIL\",\"desc\":\"触发限流\"}";
@ResponseBody
@RequestMapping("ratelimiter")
@RateLimiter(key = "ratedemo:1.0.0", limit = 5, expire = 10, message = MESSAGE)
public String sendPayment(HttpServletRequest request) throws Exception {
return "正常请求";
}
@ResponseBody
@RequestMapping("ratelimiter1")
@RateLimiter(key = "ratedemo:1.0.1", limit = 5, expire = 10, message = MESSAGE)
public String sendPayment1(HttpServletRequest request) throws Exception {
return "正常请求";
}
}
================================================
FILE: shleld-ratelimter-demo/src/main/resources/application.properties
================================================
#redis
spring.redis.hostName=127.0.0.1
spring.redis.host=127.0.0.1
spring.redis.port=6379
spring.redis.pool.maxActive=8
spring.redis.pool.maxWait=-1
spring.redis.pool.maxIdle=8
spring.redis.pool.minIdle=0
spring.redis.timeout=10000
spring.redis.password=
logging.path=D:/log/ratelimiter
logging.level.com.snowalker=DEBUG
server.port=8888
================================================
FILE: shleld-ratelimter-demo/target/classes/application.properties
================================================
#redis
spring.redis.hostName=127.0.0.1
spring.redis.host=127.0.0.1
spring.redis.port=6379
spring.redis.pool.maxActive=8
spring.redis.pool.maxWait=-1
spring.redis.pool.maxIdle=8
spring.redis.pool.minIdle=0
spring.redis.timeout=10000
spring.redis.password=
logging.path=D:/log/ratelimiter
logging.level.com.snowalker=DEBUG
server.port=8888