1.首先接口限流算法：
1.計數器方式（傳統計數器缺點：臨界問題 可能違背定義固定速率原則）
2.令牌桶方式
https://www.weibo.com/u/3932251136
3.漏桶方式
4.應用層限流（Nginx）
2.限流實現：
2.1. RateLimiter是guava提供的基於令牌桶算法的實現類，可以非常簡單的完成限流特技，並且根據系統的實際情況來調整生成token的速率。
2.2.導入相關依賴包
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.aspectj</groupId>
<artifactId>aspectjweaver</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>com.google.guava</groupId>
<artifactId>guava</artifactId>
<version>20.0</version>
</dependency>
2.3.代碼實現不多說每一步都有注解
2.3.1 定義注解
@Inherited
@Documented
@Target(ElementType.METHOD)
@Retention(RetentionPolicy.RUNTIME)
public @interface RateLimit {
double limitNum() default 20; //默認每秒放入桶中的token
}
2.3.2 封裝定義返回結果
public class MyResult {
private Integer status;
private String msg;
private List<Object> data;
public MyResult(Integer status, String msg, List<Object> data) {
this.status = status;
this.msg = msg;
this.data = data;
}
public static MyResult OK(String msg, List<Object> data) {
return new MyResult(200, msg, data);
}
public static MyResult Error(Integer status, String msg) {
return new MyResult(status, msg, null);
}
2.3.3 aop實現
@Component
@Scope
@Aspect
public class RateLimitAspect {
private Logger log = LoggerFactory.getLogger(this.getClass());
//用來存放不同接口的RateLimiter(key為接口名稱，value為RateLimiter)
private ConcurrentHashMap<String, RateLimiter> map = new ConcurrentHashMap<>();
private static ObjectMapper objectMapper = new ObjectMapper();
private RateLimiter rateLimiter;
@Autowired
private HttpServletResponse response;
@Pointcut("@annotation(com.icat.retalimitaop.annotation.RateLimit)")
public void serviceLimit() {
}
@Around("serviceLimit()")
public Object around(ProceedingJoinPoint joinPoint) throws NoSuchMethodException {
Object obj = null;
//獲取攔截的方法名
Signature sig = joinPoint.getSignature();
//獲取攔截的方法名
MethodSignature msig = (MethodSignature) sig;
//返回被織入增加處理目標對象
Object target = joinPoint.getTarget();
//為了獲取注解信息
Method currentMethod = target.getClass().getMethod(msig.getName(), msig.getParameterTypes());
//獲取注解信息
RateLimit annotation = currentMethod.getAnnotation(RateLimit.class);
double limitNum = annotation.limitNum(); //獲取注解每秒加入桶中的token
String functionName = msig.getName(); // 注解所在方法名區分不同的限流策略
//獲取rateLimiter
if(map.containsKey(functionName)){
rateLimiter = map.get(functionName);
}else {
map.put(functionName, RateLimiter.create(limitNum));
rateLimiter = map.get(functionName);
}
try {
if (rateLimiter.tryAcquire()) {
//執行方法
obj = joinPoint.proceed();
} else {
//拒絕了請求（服務降級）
String result = objectMapper.writeValueAsString(MyResult.Error(500, "系統繁忙！"));
log.info("拒絕了請求：" + result);
outErrorResult(result);
}
} catch (Throwable throwable) {
throwable.printStackTrace();
}
return obj;
}
//將結果返回
public void outErrorResult(String result) {
response.setContentType("application/json;charset=UTF-8");
try (ServletOutputStream outputStream = response.getOutputStream()) {
outputStream.write(result.getBytes("utf-8"));
} catch (IOException e) {
e.printStackTrace();
}
}
static {
objectMapper.setSerializationInclusion(JsonInclude.Include.NON_NULL);
}
}
3.測試限流
2個接口設定沒秒限流5個和美妙限流10個
@RateLimit(limitNum = 5.0)
public MyResult getResults() {
log.info("調用了方法getResults");
return MyResult.OK("調用了方法", null);
}
@RateLimit(limitNum = 10.0)
public MyResult getResultTwo() {
log.info("調用了方法getResultTwo");
return MyResult.OK("調用了方法getResultTwo", null);
}
使用Jmeter測試getResults接口 20個並發（設定每秒只能處理5個請求）
使用Jmeter測試getResultTwo接口 20個並發（設定每秒只能處理10個請求）
結果會比設定的多一個（百度了很久沒找到原因 - -！ ）