Concurrency performance optimization practice in Go language

Practice of optimizing the concurrency performance of Go language include: establishing Goroutine pool to avoid goroutine creation/destruction overhead. Optimize channel usage and avoid blocking operations to improve responsiveness. Use read-write locks to reduce lock contention and improve shared resource access efficiency. Leverage Context to propagate cancellation and deadline information within goroutines to handle cancellation requests gracefully. Significantly improve request processing speed by processing HTTP requests in parallel through goroutines.

Concurrency performance optimization practice in Go language

Concurrency is an effective method to improve program performance, but if you do not pay attention to optimization, It may also cause performance degradation. This article introduces how to apply concurrency optimization practices in Go language and provides practical cases.

Goroutine Pool

goroutine pool avoids the overhead of frequently creating and destroying goroutines. Throughput can be improved by creating a pool of pre-allocated goroutines.

type Job struct {
    task func()
}

func main() {
    pool := make(chan Job, 100)
    for i := 0; i < 100; i++ {
        go func(i int) {
            for {
                job, ok := <-pool
                if !ok {
                    return
                }
                job.task()
            }
        }(i)
    }

    // 向池中提交任务
    for j := 0; j < 100000; j++ {
        pool <- Job{
            task: func() { time.Sleep(500 * time.Microsecond) },
        }
    }

    //关闭池
    close(pool)
}

Channel optimization

Channel is an important mechanism for communication between goroutines. Optimizing channels can improve the efficiency of data transfer.

Avoid using blocking operations: Using non-blocking operations (such as Select or Timeout) can improve the responsiveness of the program.

select {
case value := <-chan:
    // 处理 value
default:
    // 通道为空，执行其他任务
}

Lock optimization

Locks are used to protect shared resources, but excessive use of locks can lead to deadlocks or performance degradation.

Use read-write locks: Read-write locks allow multiple read operations to access concurrently, while write operations have exclusive access to resources, which can reduce lock contention.

import "sync"

var rwmu sync.RWMutex

func main() {
    rwmu.RLock()
    // 并发读操作
    rwmu.RUnlock()

    rwmu.Lock()
    // 写操作
    rwmu.Unlock()
}

Context

Context provides a way to propagate cancellation and deadline information in goroutines. Use Context to handle cancellation requests gracefully and avoid wasting resources.

import "context"

func main() {
    ctx, cancel := context.WithTimeout(context.Background(), 10*time.Second)
    defer cancel()

    go func() {
        for {
            select {
            case <-ctx.Done():
                return
            default:
                // 执行任务
            }
        }
    }()
}

Practical case

Parallel HTTP request

By using goroutine to process HTTP requests concurrently, the request processing speed can be significantly improved .

import (
    "net/http"
    "time"
)

func main() {
    client := &http.Client{
        Timeout: 10 * time.Second,
    }

    urls := []string{"https://example.com", "https://example2.com", "https://example3.com"}

    var wg sync.WaitGroup
    for _, url := range urls {
        wg.Add(1)
        go func(url string) {
            defer wg.Done()
            resp, err := client.Get(url)
            if err != nil {
                // 处理错误
                return
            }
            _ = resp.Body.Close() // 确保关闭连接
        }(url)
    }
    wg.Wait()
}

By applying these optimization practices, the concurrency performance of Go language programs can be significantly improved and the potential of the program can be released.

The above is the detailed content of Concurrency performance optimization practice in Go language. For more information, please follow other related articles on the PHP Chinese website!