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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