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Introduction to golang framework performance analysis tool

Jun 05, 2024 pm 03:34 PM
golang Performance analysis

In order to optimize the performance of Go applications, you can choose the following tools: pprof: built-in tool for analyzing CPU and memory usage; go-torch: open source tool that provides more granular performance analysis, including CPU, memory, GC and network usage; gopsutil: a cross-platform library for obtaining system-level performance metrics such as CPU usage, memory usage, disk I/O, and network throughput.

Introduction to golang framework performance analysis tool

Introduction to Go framework performance analysis tools

In Go application development, performance optimization is crucial. To help developers identify bottlenecks and improve code efficiency, here are some valuable performance analysis tools.

1. pprof

pprof is a powerful tool built into Go for analyzing CPU and memory usage. It provides a graphical interface to interactively visualize an application's performance data.

Practical case:

import "net/http"

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

func fibHandler(w http.ResponseWriter, r *http.Request) {
    n, err := strconv.Atoi(r.FormValue("n"))
    if err != nil || n < 0 {
        http.Error(w, "invalid input", http.StatusBadRequest)
        return
    }

    w.Header().Set("Content-Type", "text/plain")
    fmt.Fprintf(w, "%d", fib(n))
}

func fib(n int) int {
    if n <= 1 {
        return 1
    }

    return fib(n-1) + fib(n-2)
}
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2. go-torch

go-torch is an open source tool that provides more detailed Granular performance analysis including CPU, memory, GC and network usage. It allows developers to set custom events and capture performance data about specific pieces of code.

Practical case:

import "github.com/uber-go/go-torch"

func main() {
    // 创建一个 Torch 实例
    t, err := torch.New()
    if err != nil {
        // handle error
    }

    // 开始一个名为 "my-function" 的事件
    t.MeasureSegment("my-function", func() {
        // 执行要分析的代码
    })

    // 获取事件的性能数据
    stats, err := t.Stats()
    if err != nil {
        // handle error
    }

    // 分析性能数据
}
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3. gopsutil

gopsutil is a cross-platform library that can obtain system-level performance indicators , such as CPU usage, memory usage, disk I/O and network throughput.

Practical case:

import "github.com/shirou/gopsutil/v3/cpu"

func main() {
    // 获取 CPU 使用率
    usage, err := cpu.Percent(time.Second, false)
    if err != nil {
        // handle error
    }

    for _, p := range usage {
        fmt.Println("CPU utilization:", p)
    }
}
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