有人问我限流怎么做，单独抽出来说一下： 这里使用aizuda-limiter，文档：http://doc.aizuda.com/pages/9xd009/ example仓库：https://gitee.com.../aizuda/aizuda-components-examples/blob/master/aizuda-limiter-example 首先引入： com.aizuda... aizuda-limiter 1.0.0 然后进行配置限流策略...： package com.aizuda.limiter.example; import com.aizuda.limiter.metadata.MethodMetadata; import com.aizuda.limiter.strategy.IKeyGenerateStrategy...; import com.aizuda.limiter.annotation.RateLimit; import com.aizuda.limiter.strategy.IpKeyGenerateStrategy
序 本文主要研究一下dapr的Limiter OIP - 2021-03-06T221220.026.jpeg Limiter dapr/pkg/concurrency/limiter.go const...( // DefaultLimit is the default concurrency limit DefaultLimit = 100 ) // Limiter object type...Limiter struct { limit int tickets chan int numInProgress int32 } Limiter...定义了limit、tickets、numInProgress属性 NewLimiter dapr/pkg/concurrency/limiter.go // NewLimiter allocates...} // allocate a limiter instance c := &Limiter{ limit: limit, tickets
3 Gin框架接口限速实践基于limiter插件的GitHub地址：github.com/ulule/limiter3.1 基本使用package mainimport ( "fmt" "log.../v3" mgin "github.com/ulule/limiter/v3/drivers/middleware/gin" sredis "github.com/ulule/limiter/v3...store, err := sredis.NewStoreWithOptions(client, limiter.StoreOptions{ Prefix: "limiter_gin_example.../v3" mgin "github.com/ulule/limiter/v3/drivers/middleware/gin" sredis "github.com/ulule/limiter/v3.../v3" mgin "github.com/ulule/limiter/v3/drivers/middleware/gin" sredis "github.com/ulule/limiter/v3
{ return &Limiter{ limit: r, burst: b, } } 简单构造了一个limiter对象 type Limiter struct { mu...Limiter提供了三类方法供用户消费Token，用户可以每次消费一个Token，也可以一次性消费多个Token。...func (lim *Limiter) Allow() bool func (lim *Limiter) AllowN(now time.Time, n int) bool 2，当使用 Wait 方法消费...func (lim *Limiter) Wait(ctx context.Context) (err error) func (lim *Limiter) WaitN(ctx context.Context...func (lim *Limiter) Reserve() *Reservation func (lim *Limiter) ReserveN(now time.Time, n int) *Reservation
Doesn't matter whether it's for perm failing // or for success, we'll stop the rate limiter from tracking...type BucketRateLimiter struct { *rate.Limiter } func (r *BucketRateLimiter) When(item interface{})...} func (r *MaxOfRateLimiter) NumRequeues(item interface{}) int { ret := 0 for _, limiter := range...r.limiters { curr := limiter.NumRequeues(item) if curr > ret { ret = curr } } return ret...} func (r *MaxOfRateLimiter) Forget(item interface{}) { for _, limiter := range r.limiters { limiter.Forget
// 分别返回 b 和 r 的值func (lim *Limiter) Burst() intfunc (lim *Limiter) Limit() Limit // token 消费方法func (...lim *Limiter) Allow() boolfunc (lim *Limiter) AllowN(now time.Time, n int) boolfunc (lim *Limiter) Reserve...() *Reservationfunc (lim *Limiter) ReserveN(now time.Time, n int) *Reservationfunc (lim *Limiter) Wait...动态流控func (lim *Limiter) SetBurst(newBurst int)func (lim *Limiter) SetBurstAt(now time.Time, newBurst...(*rate.Limiter).Wait(ctx); err !
testLimiter方法中通过limiter.acquire()方法获取令牌（不带参数时默认获取1张令牌）。...= RateLimiter.create(1); System.out.println(limiter.acquire(4)); System.out.println(...limiter.acquire(3)); System.out.println(limiter.acquire(2)); System.out.println(limiter.acquire...limiter.tryAcquire(1, 2, TimeUnit.SECONDS)); } } 上面例子limiter.tryAcquire设置了超时时间为2秒，由于第一次请求一次性获取了3张令牌...，所以这里需要等待大约3秒钟，超出了2秒的超时时间，所以limiter.tryAcquire不会等待3秒，而是直接返回false。
func main() { fmt.Println(time.Now()) go response() wg := &sync.WaitGroup{} //并发10 limiter...:= make(chan bool, 10) for i := 0; i < 100; i++ { wg.Add(1) limiter <- true...go httpGet(strconv.Itoa(i), limiter, wg) } wg.Wait() fmt.Println("all Done") fmt.Println...(time.Now()) } func httpGet(url string, limiter chan bool, wg *sync.WaitGroup) { defer wg.Done(...:= make(chan bool, 10) defer close(limiter) response := make(chan string, 20) wgResponse
: 10 redis-rate-limiter.burstCapacity: 20 key-resolver: "#{@apiKeyResolver...: 10 redis-rate-limiter.burstCapacity: 20 key-resolver: "#{@apiKeyResolver...: 20 redis-rate-limiter.burstCapacity: 50 key-resolver: "#{@apiKeyResolver...: 10 redis-rate-limiter.burstCapacity: 20 key-resolver: "#{@apiKeyResolver...: 10 redis-rate-limiter.burstCapacity: 20 key-resolver: "#{@apiKeyResolver
, _rate_limit_exceeded_handler from slowapi.util import get_remote_address limiter = Limiter(key_func...=get_remote_address) app = FastAPI() app.state.limiter = limiter app.add_exception_handler(RateLimitExceeded...: Request): return PlainTextResponse("test") @app.get("/mars") @limiter.limit("5/minute") async...def homepage(request: Request, response: Response): return {"key": "value"} 2、 fastapi-limiter[3...import FastAPILimiter from fastapi_limiter.depends import RateLimiter app = FastAPI() @app.on_event
- 进入 [pool-1-thread-16] INFO blog20210109.Limiter - 进入 [pool-1-thread-42] INFO blog20210109.Limiter...- 进入 [pool-1-thread-22] INFO blog20210109.Limiter - 进入 [pool-1-thread-91] INFO blog20210109.Limiter -...进入 [pool-1-thread-10] INFO blog20210109.Limiter - 进入 [pool-1-thread-33] INFO blog20210109.Limiter -...进入 [pool-1-thread-83] INFO blog20210109.Limiter - 进入 [pool-1-thread-62] INFO blog20210109.Limiter - 进入...[pool-1-thread-35] INFO blog20210109.Limiter - 进入 [main] INFO blog20210109.Limiter - 一分钟内进入的请求数有:10
Wait/WaitN func (lim *Limiter) Wait(ctx context.Context) (err error) func (lim *Limiter) WaitN(ctx context.Context...Allow/AllowN func (lim *Limiter) Allow() bool func (lim *Limiter) AllowN(now time.Time, n int) bool...Reserve/ReserveN func (lim *Limiter) Reserve() *Reservation func (lim *Limiter) ReserveN(now time.Time...// 令牌桶限速器，固定速率（qps) type BucketRateLimiter struct { // golang 自带的 Limiter *rate.Limiter } var.../default_rate_limiter.go BucketRateLimiter{Limiter: rate.NewLimiter(rate.Limit(10), 100)} 通过 rate.NewLimiter
限流器的内部结构 time/rate包的Limiter类型对限流器进行了定义，所有限流功能都是通过基于Limiter类型实现的，其内部结构如下： type Limiter struct { mu...第二个参数是 b int，b 代表 Token 桶的容量大小，也就是设置的限流器 Limiter 的burst字段。...Wait/WaitN func (lim *Limiter) Wait(ctx context.Context) (err error) func (lim *Limiter) WaitN(ctx context.Context...= nil { fmt.Println("Error: ", err) } Allow/AllowN func (lim *Limiter) Allow() bool func (lim *Limiter...allowed") } Reserve/ReserveN func (lim *Limiter) Reserve() *Reservation func (lim *Limiter) ReserveN
use Symfony\Component\HttpFoundation\Response; class ThrottleMiddleware { /** * The rate limiter...* * @var \Illuminate\Cache\RateLimiter */ protected $limiter; /** * Create...* * @param \Illuminate\Cache\RateLimiter $limiter * @return void */ public...function __construct(RateLimiter $limiter) { $this->limiter = $limiter; } /**...decayMinutes = 1) { $key = $this->resolveRequestSignature($request); if ($this->limiter
库使用说明 构造限流器 我们首先构造一个限流器对象： limiter := NewLimiter(10, 1); 这里有两个参数： 第一个参数是 r Limit。...消费令牌Token Limiter 提供了三类方法供用户消费 Token，用户可以每次消费一个 Token，也可以一次性消费多个 Token。...Wait/WaitN func (lim *Limiter) Wait(ctx context.Context) (err error) func (lim *Limiter) WaitN(ctx context.Context...如果使用速率限制，我们就可以限制一秒内只能发送一次，实现方法为： (令牌桶)容量为1，速度为每一秒生成一个令牌，这样可以保证一秒钟只会被执行一次，伪代码实现如下 //初始化 limiter 每秒生成1...编码测试功能 //初始化 limiter 每秒10个令牌，令牌桶容量为20 limiter := rate.NewLimiter(rate.Every(time.Millisecond*100), 20
实现简单效果明显，能有效限制系统请求数量冰桶算法缺点：对于突发流量，可能会导致请求被拒绝对于短时间内的请求速率，无法进行精细控制冰桶算法开源库:主流编程语言均有相应的开源库，例如:Python: Flask-Limiter...FastAPI-LimiterJava: Guava RateLimiter, Bucket4jGo: go-ratelimitNode.js: Bottleneck冰桶算法示例代码:以 Python 为例，使用 Flask-Limiter...库实现冰桶算法限流: from flask import Flask from flask_limiter import Limiter from flask_limiter.util import...get_remote_address app = Flask(__name__) limiter = Limiter(app, key_func=get_remote_address) @app.route...('/') @limiter.limit("100/day;10/hour;1/minute") def index(): return "Welcome!"
="rate_limiter"; /** * 使用redis做限流处理使用的lua脚本 */ private static final String LIMITER_LUA...limiter; if(method.isAnnotationPresent(Limiter.class)){ limiter = method.getAnnotation...(Limiter.class); }else { limiter=method.getClass().getAnnotation(Limiter.class);...limiter; if(method.isAnnotationPresent(Limiter.class)){ limiter = method.getAnnotation...(Limiter.class); }else { limiter=method.getClass().getAnnotation(Limiter.class);
内容主要是两个结构体，Limiter struct 和 Reservation struct。两个方法，reserve 预留方法 和 Token 的归还方法。...events. type Reservation struct { // ok 是否 limiter 可以提供请求所需的tokens数目 ok bool // lim...就是上面的结构体 Limiter struct lim *Limiter tokens int // timeToAct reserved action 预定的动作发生的时间...lim.advance(now) 重新计算桶里的token数目，就是通过计算Limiter结构体的last属性减去现在的时间，算出这段时间流逝中应该往桶里加多少token，加上旧的token数目（Limiter...// return // } // time.Sleep(r.Delay()) // Act() func (lim *Limiter) Reserve() *Reservation
time.time())) print('Rate limited, sleeping for {:d} seconds'.format(duration)) # 3秒之内只能访问2次 rate_limiter...= RateLimiter(max_calls=2, period=3, callback=limited) for i in range(3): with rate_limiter:...) print('Rate limited, sleeping for {:d} seconds'.format(duration)) async def coro(): rate_limiter...RateLimiter(max_calls=2, period=3, callback=limited) for i in range(3): async with rate_limiter...= Limiter(key_func=get_remote_address) FastAPI().state.limiter = limiter FastAPI().add_exception_handler
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