Positioning of performance bottlenecks in Golang function concurrent programming

Steps to locate performance bottlenecks in Go function concurrent programming: 1. Locate goroutine leaks (use runtime/debug.SetMaxThreads and debug.PrintStack); 2. Identify goroutine blocking (use runtime.SetBlockProfileRate and runtime/pprof); 3 . Analyze goroutine scheduling (using runtime/pprof).

Location of performance bottlenecks in concurrent programming of Go functions

In Go, concurrent programming is implemented through Goroutine, which allows developers to write parallel code to fully Take advantage of multi-core CPUs. However, when an application does not perform as expected, identifying bottlenecks becomes critical. The following steps can help locate performance bottlenecks in functional concurrent programming:

1. Locate goroutine leaks

Goroutine leaks refer to forgetting to close goroutines when they are no longer needed, resulting in The number of goroutines in the program continues to increase, causing memory and performance problems. Use the runtime/debug.SetMaxThreads function and the runtime/debug.PrintStack function to monitor the number of goroutines and identify leaks.

// 定位 goroutine 泄漏
package main

import (
    "fmt"
    "runtime"
    "runtime/debug"
)

func main() {
    // 实战案例：创建一个循环中持续创建 goroutine 的函数
    createGoroutineLeak()
    
    // 检查 goroutine 数量
    fmt.Println("Current goroutine count:", runtime.NumGoroutine())
    
    // 打印 goroutine 栈信息以调试泄漏
    debug.PrintStack()
}

// 创建 goroutine 泄漏（模拟不关闭 goroutine）
func createGoroutineLeak() {
    for {
        go func() {
            // 无限循环（模拟不关闭 goroutine）
            for {}
        }()
    }
}

2. Identify goroutine blocking

Goroutine blocking will prevent other goroutines from running, resulting in performance degradation. You can use the runtime.SetBlockProfileRate function to enable goroutine blocking sampling, and use the runtime/pprof package to generate a blocking configuration file for analysis.

// 定位 goroutine 阻塞
package main

import (
    "fmt"
    "net/http/pprof"
    "runtime"
)

func main() {
    // 开启 goroutine 阻塞采样
    runtime.SetBlockProfileRate(1)
    
    // 实战案例：创建一个使用互斥锁死锁的函数
    createGoroutineDeadlock()
    
    // 生成本地阻塞配置文件
    f, err := os.Create("goroutine-block.pprof")
    if err != nil {
        log.Fatal(err)
    }
    defer f.Close()
    pprof.Lookup("block").WriteTo(f, 1)
    
    fmt.Println("阻塞配置文件已生成：goroutine-block.pprof")
}

// 创建 goroutine 死锁（模拟互斥锁使用不当）
func createGoroutineDeadlock() {
    var mu sync.Mutex
    
    // goroutine 1 试图获取锁
    go func() {
        mu.Lock()
        defer mu.Unlock()
        // 无限循环（模拟死锁）
        for {}
    }()
    
    // goroutine 2 试图获取锁
    go func() {
        mu.Lock()
        defer mu.Unlock()
        // 无限循环（模拟死锁）
        for {}
    }()
}

3. Analyze goroutine scheduling

The Goroutine scheduler is responsible for assigning goroutine to available CPU cores. Improper scheduling strategies can cause performance issues. You can use the runtime/pprof package to generate a goroutine scheduling configuration file for analysis.

// 分析 goroutine 调度
package main

import (
    "fmt"
    "net/http/pprof"
    "runtime"
)

func main() {
    // 生成本地 goroutine 调度配置文件
    f, err := os.Create("goroutine-sched.pprof")
    if err != nil {
        log.Fatal(err)
    }
    defer f.Close()
    pprof.Lookup("goroutine").WriteTo(f, 1)
    
    fmt.Println("调度配置文件已生成：goroutine-sched.pprof")
}

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