Use Go to efficiently handle large-scale concurrent requests

By using Go's concurrency primitives such as goroutine and channel, you can efficiently handle large-scale concurrent requests: create a fixed number of goroutines and use channels to buffer requests. Protect shared resources with locks or mutexes. Limit the number of concurrent requests, for example by using context to set a timeout.

Use Go to efficiently handle large-scale concurrent requests

Introduction
Handle large-scale concurrent requests is a common challenge, especially in microservices and web applications. Go is a language built for concurrency and is particularly well-suited to handle such workloads. This article will introduce Go’s concurrency primitives and best practices, and use a practical case to demonstrate how to efficiently handle large-scale concurrent requests.

Goroutine and Channel
Goroutine is a lightweight parallel execution unit in Go, similar to a thread. Channel is a mechanism for communication between goroutines.

Best Practices

• Create a fixed number of goroutines instead of creating new goroutines for each request.
• Use channels to buffer requests and limit the number of concurrent requests.
• Use locks or mutexes to protect shared resources.

Practical case
We create a web application to process files uploaded by users. The application needs to handle multiple file upload requests concurrently.

package main

import (
    "context"
    "log"
    "net/http"
    "sync"
)

const maxConcurrency = 10

var wg sync.WaitGroup

func main() {
    http.HandleFunc("/upload", uploadHandler)
    http.ListenAndServe(":8080", nil)
}

func uploadHandler(w http.ResponseWriter, r *http.Request) {
    wg.Add(1)
    defer wg.Done()

    // 创建一个 goroutine 来处理文件上传
    go func() {
        defer r.Body.Close()
        if err := handleFileUpload(r.Body); err != nil {
            log.Println(err)
        }
    }()
    
    // 限制并发上传的数量
    ctx, cancel := context.WithTimeout(context.Background(), time.Second*10)
    defer cancel()
    select {
    case <-ctx.Done():
        http.Error(w, "Too many concurrent uploads", http.StatusTooManyRequests)
        return
    default:
    }
}

func handleFileUpload(r io.Reader) error {
    // 省略实际的文件上传处理
    return nil
}

Conclusion
By following the best practices introduced in this article, you can build efficient and scalable Go applications that can handle large-scale concurrent requests.

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