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How to implement routing request current limiting in Go language

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2023-12-17 18:57:401076browse

How to implement routing request current limiting in Go language

How to implement routing request flow limiting in Go language

With the development of web applications and the increase in the number of users, the number of requests to the server will also increase. . In order to ensure the stability and performance of the server, we need to limit the flow of requests. Current limiting can effectively control the number of requests and avoid server crashes or performance degradation. In the Go language, you can use the gomodule library to implement routing request flow limiting. The following will introduce how to use the gomodule library to implement routing request flow limiting, and attach the corresponding code examples.

  1. Introducing the gomodule library
    First, we need to introduce the gomodule library into the Go program. You can use the go get command to obtain the library. The command is as follows:

    go get -u github.com/juju/ratelimit
  2. Implementing the request current limiter
    Next, we need to implement a request current limiter. The request limiter is a timer-like structure used to limit the frequency of requests. We can use the ratelimit package in the gomodule library to implement the request rate limiter. The sample code is as follows:

    package main
    
    import (
     "fmt"
     "time"
    
     "github.com/juju/ratelimit"
    )
    
    func main() {
     // 设置每秒钟可以处理的请求数
     limit := ratelimit.NewBucket(time.Second, 10)
    
     // 模拟处理请求
     for i := 0; i < 20; i++ {
         // 获取当前时间
         startTime := time.Now()
    
         // 尝试获取一个请求令牌
         limit.Wait(1)
    
         // 处理请求
         fmt.Printf("Processing request %d
    ", i)
    
         // 计算处理时间
         elapsedTime := time.Since(startTime)
         fmt.Printf("Processing time: %dms
    ", elapsedTime.Milliseconds())
     }
    }

In the above sample code, we create a request limiter that can handle 10 requests per second through the ratelimit.NewBucket function. Then, we simulate processing 20 requests and implement request current limiting through the limit.Wait(1) method. Before each request is processed, we use time.Now() to get the current time, and then calculate the processing time after processing the request.

  1. Using request limiters in routing
    In actual web applications, we usually use routing to handle requests. The following is an example of routing code using a request limiter:

    package main
    
    import (
     "fmt"
     "net/http"
     "time"
    
     "github.com/juju/ratelimit"
    )
    
    func rateLimitMiddleware(next http.HandlerFunc, limit *ratelimit.Bucket) http.HandlerFunc {
     return func(w http.ResponseWriter, r *http.Request) {
         startTime := time.Now()
    
         // 尝试获取一个请求令牌
         limit.Wait(1)
    
         // 计算处理时间
         elapsedTime := time.Since(startTime)
         fmt.Printf("Processing time: %dms
    ", elapsedTime.Milliseconds())
    
         // 调用下一个处理器
         next(w, r)
     }
    }
    
    func helloHandler(w http.ResponseWriter, r *http.Request) {
     fmt.Fprintln(w, "Hello, world!")
    }
    
    func main() {
     // 创建请求限流器
     limit := ratelimit.NewBucket(time.Second, 10)
    
     // 创建路由器
     mux := http.NewServeMux()
    
     // 添加路由处理函数,并使用请求限流器中间件
     mux.HandleFunc("/", rateLimitMiddleware(helloHandler, limit))
    
     // 启动HTTP服务器
     http.ListenAndServe(":8080", mux)
    }

In the above example code, we first create a request limiter limit. Then, we created a router mux and added the request rate limiter middleware rateLimitMiddleware to the route processing function helloHandler. Before processing each request, the middleware will wait for a request token to implement request flow limiting. Finally, we start the HTTP server using the http.ListenAndServe function.

By using the gomodule library, we can easily implement routing request flow limiting. In this way, we can effectively control the server's request volume and avoid server crashes or performance degradation. At the same time, using the request limiter can help us better understand the load of the server and optimize system performance.

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