search
HomeBackend DevelopmentGolangHow to use context to implement request concurrency control in Go

How to use context to implement request concurrency control in Go

Jul 22, 2023 am 09:03 AM
controlconcurrentcontext

As a high-performance programming language, Go language has always been outstanding in its concurrent programming capabilities. In order to better manage and control concurrent requests, in Go language, we can use context to implement request concurrency control. This article will introduce how to use context to implement request concurrency control in Go language, and demonstrate it through code examples.

Introduction to Context

In the Go language, the context package provides a way to manage collision requests. It can pass request-wide data between goroutines, including deadlines, timeouts, cancellation signals, etc. By using context, we can better manage and control concurrent requests.

Steps to use context to implement request concurrency control

The following are the steps to use context to implement request concurrency control:

  1. Create root context: First, we need to create a root context. The root context is the parent context of all child contexts. We can use context.TODO() or context.Background() to create an empty root context.
ctx := context.TODO()
  1. Create subcontext: Next, we can use the context.WithXXX() function to create a subcontext. This function receives a parent context as a parameter and returns a new child context.
childCtx := context.WithTimeout(ctx, time.Second*10)

In the above code, we use the context.WithTimeout() function to create a subcontext with a timeout of 10 seconds.

  1. Processing requests: When processing specific requests, we can use context.Context type parameters to receive the passed context. During the process of processing the request, we can use the context.Context method to obtain context-related information.
func HandleRequest(ctx context.Context) {
    // 处理请求
}
  1. Control concurrency: When making concurrent requests, we can use the Done() method of context.Context to determine whether the request has been canceled or timed out. When the Done() method is called, it returns a read-only Channel. If the request is canceled or times out, the Done() method will close the Channel.
go func() {
    for {
        select {
        case <-ctx.Done():
            return
        default:
            // 发起请求
            HandleRequest(ctx)
        }
    }
}()

In the above code, we use a for loop and select statement to monitor the Done() method of context. When the Done() method returns, we know that the request has been canceled or timed out and we can exit the loop.

  1. Cancel Request: In some cases we wish to cancel a request that is being processed. At this time, we can call the cancel() method of type context.CancelFunc to cancel the request.
cancel()

In the above code, we call the cancel() method to cancel the request.

Sample code

The following is a simple sample code that demonstrates how to use context to implement request concurrency control.

package main

import (
    "context"
    "fmt"
    "sync"
    "time"
)

func Worker(ctx context.Context, wg *sync.WaitGroup) {
    defer wg.Done()
 
    for {
        select {
        case <-ctx.Done():
            // 请求已被取消或超时
            return
        default:
            // 处理请求
            fmt.Println("Handling request...")
            time.Sleep(time.Second * 1)
        }
    }
}

func main() {
    ctx := context.TODO()
    childCtx, cancel := context.WithTimeout(ctx, time.Second*5)
    defer cancel()

    var wg sync.WaitGroup
    for i := 0; i < 5; i++ {
        wg.Add(1)
        go Worker(childCtx, &wg)
    }

    wg.Wait()
    fmt.Println("All requests processed")
}

In the above code, we create a root context and a child context with a timeout of 5 seconds. Then, we created 5 goroutines to handle the requests. During the process of processing the request, we use the context's Done() method to determine whether the request was canceled or timed out. Finally, we use sync.WaitGroup to wait for all requests to be processed.

Summary

By using context, we can better manage and control concurrent requests. This article introduces the steps to use context to implement request concurrency control and demonstrates it through sample code. I believe that readers can better understand and apply context to achieve request concurrency control through the introduction and sample code of this article.

The above is the detailed content of How to use context to implement request concurrency control in Go. For more information, please follow other related articles on the PHP Chinese website!

Statement
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
Golang vs. Python: Concurrency and MultithreadingGolang vs. Python: Concurrency and MultithreadingApr 17, 2025 am 12:20 AM

Golang is more suitable for high concurrency tasks, while Python has more advantages in flexibility. 1.Golang efficiently handles concurrency through goroutine and channel. 2. Python relies on threading and asyncio, which is affected by GIL, but provides multiple concurrency methods. The choice should be based on specific needs.

Golang and C  : The Trade-offs in PerformanceGolang and C : The Trade-offs in PerformanceApr 17, 2025 am 12:18 AM

The performance differences between Golang and C are mainly reflected in memory management, compilation optimization and runtime efficiency. 1) Golang's garbage collection mechanism is convenient but may affect performance, 2) C's manual memory management and compiler optimization are more efficient in recursive computing.

Golang vs. Python: Applications and Use CasesGolang vs. Python: Applications and Use CasesApr 17, 2025 am 12:17 AM

ChooseGolangforhighperformanceandconcurrency,idealforbackendservicesandnetworkprogramming;selectPythonforrapiddevelopment,datascience,andmachinelearningduetoitsversatilityandextensivelibraries.

Golang vs. Python: Key Differences and SimilaritiesGolang vs. Python: Key Differences and SimilaritiesApr 17, 2025 am 12:15 AM

Golang and Python each have their own advantages: Golang is suitable for high performance and concurrent programming, while Python is suitable for data science and web development. Golang is known for its concurrency model and efficient performance, while Python is known for its concise syntax and rich library ecosystem.

Golang vs. Python: Ease of Use and Learning CurveGolang vs. Python: Ease of Use and Learning CurveApr 17, 2025 am 12:12 AM

In what aspects are Golang and Python easier to use and have a smoother learning curve? Golang is more suitable for high concurrency and high performance needs, and the learning curve is relatively gentle for developers with C language background. Python is more suitable for data science and rapid prototyping, and the learning curve is very smooth for beginners.

The Performance Race: Golang vs. CThe Performance Race: Golang vs. CApr 16, 2025 am 12:07 AM

Golang and C each have their own advantages in performance competitions: 1) Golang is suitable for high concurrency and rapid development, and 2) C provides higher performance and fine-grained control. The selection should be based on project requirements and team technology stack.

Golang vs. C  : Code Examples and Performance AnalysisGolang vs. C : Code Examples and Performance AnalysisApr 15, 2025 am 12:03 AM

Golang is suitable for rapid development and concurrent programming, while C is more suitable for projects that require extreme performance and underlying control. 1) Golang's concurrency model simplifies concurrency programming through goroutine and channel. 2) C's template programming provides generic code and performance optimization. 3) Golang's garbage collection is convenient but may affect performance. C's memory management is complex but the control is fine.

Golang's Impact: Speed, Efficiency, and SimplicityGolang's Impact: Speed, Efficiency, and SimplicityApr 14, 2025 am 12:11 AM

Goimpactsdevelopmentpositivelythroughspeed,efficiency,andsimplicity.1)Speed:Gocompilesquicklyandrunsefficiently,idealforlargeprojects.2)Efficiency:Itscomprehensivestandardlibraryreducesexternaldependencies,enhancingdevelopmentefficiency.3)Simplicity:

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Article

R.E.P.O. Energy Crystals Explained and What They Do (Yellow Crystal)
1 months agoBy尊渡假赌尊渡假赌尊渡假赌
R.E.P.O. Best Graphic Settings
1 months agoBy尊渡假赌尊渡假赌尊渡假赌
R.E.P.O. How to Fix Audio if You Can't Hear Anyone
1 months agoBy尊渡假赌尊渡假赌尊渡假赌
R.E.P.O. Chat Commands and How to Use Them
1 months agoBy尊渡假赌尊渡假赌尊渡假赌

Hot Tools

EditPlus Chinese cracked version

EditPlus Chinese cracked version

Small size, syntax highlighting, does not support code prompt function

WebStorm Mac version

WebStorm Mac version

Useful JavaScript development tools

Safe Exam Browser

Safe Exam Browser

Safe Exam Browser is a secure browser environment for taking online exams securely. This software turns any computer into a secure workstation. It controls access to any utility and prevents students from using unauthorized resources.

SublimeText3 English version

SublimeText3 English version

Recommended: Win version, supports code prompts!

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment