How to use pipe buffers for flow control in Goroutine?

Using pipe buffers for flow control ensures safe communication in Goroutines. It allows blocking when the buffer is full when sending data and blocking when the buffer is empty when receiving data: Creating a pipe with a buffer The send data operation blocks when the buffer is empty , receiving data operations will block

How to use pipe buffers for flow control in Goroutine

##Introduction

In Goroutine concurrent programming, a pipe is a data structure used to communicate safely between Goroutines. Pipe buffers are an optional feature in pipes that provide flow control for send and receive operations.

Use pipe buffer for flow control

1. Create a pipe with buffer

bufsize := 10
pipeline := make(chan int, bufsize)

The above code creates Creates a pipe with buffer size

bufsize.

2. Send data to the pipe

When the pipe buffer is full, the

Send operation will block until there is room for more data .

for i := 0; i < 100; i++ {
    pipeline <- i
}

3. Receive data from the pipe

Similarly, when the pipe buffer is empty, the

Receive operation will block until there is data Available for reception.

for i := 0; i < 100; i++ {
    data := <-pipeline
    fmt.Println(data)
}

Practical case

Asynchronous web service

In an asynchronous web service, the pipe buffer can be used to control the incoming The requested rate. By limiting the size of the pipe buffer, we ensure that the server is not overloaded by handling too many requests at the same time.

Code example:

func main() {
    bufsize := 10
    pipeline := make(chan *http.Request, bufsize)

    // 启动 HTTP 服务器
    http.HandleFunc("/", func(w http.ResponseWriter, r *http.Request) {
        pipeline <- r
    })

    // 启动 Goroutine 来处理请求
    go func() {
        for {
            req := <-pipeline
            // 处理请求
        }
    }()

    http.ListenAndServe(":8080", nil)
}

In this case, the size of the buffer is

10, which means the server can handle at most 10 simultaneously requests to prevent problems due to excessive request load.

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