golang pprof性能调试：寻找cpu瓶颈

1、引入pprof进行性能调试

在代码中加入：

import _ "net/http/pprof"go func() {http.ListenAndServe("0.0.0.0:8899", nil)
}()

示例：为冒泡排序加入pprof debug

package mainimport ("math/rand""net/http"_ "net/http/pprof""time"
)func generate(n int) []int {rand.Seed(time.Now().UnixNano())nums := make([]int, 0)for i := 0; i < n; i++ {nums = append(nums, rand.Int())}return nums
}
func bubbleSort(nums []int) {for i := 0; i < len(nums); i++ {for j := 1; j < len(nums)-i; j++ {if nums[j] < nums[j-1] {nums[j], nums[j-1] = nums[j-1], nums[j]}}}
}func main() {go func() {http.ListenAndServe("0.0.0.0:8899", nil)}()for {n := 10for i := 0; i < 5; i++ {nums := generate(n)bubbleSort(nums)n *= 10}}
}

2、pprof命令行交互式查看程序最消耗cpu的地方

1、启动上述程序：

go run main.go

2、访问pprof暴露的cpu debug api接口，收集30s内的cpu数据：

go tool pprof http://localhost:8899/debug/pprof/profile\?seconds\=30

3、在交互命令中，使用top，list来查看最消耗cpu的地方

go tool pprof http://localhost:8899/debug/pprof/profile\?seconds\=30
Fetching profile over HTTP from http://localhost:8899/debug/pprof/profile?seconds=30
Saved profile in /Users/zejia.lu/pprof/pprof.samples.cpu.003.pb.gz
Type: cpu
Time: Nov 27, 2022 at 12:09pm (CST)
Duration: 30.19s, Total samples = 26.13s (86.56%)
Entering interactive mode (type "help" for commands, "o" for options)
(pprof) top
Showing nodes accounting for 26.06s, 99.73% of 26.13s total
Dropped 18 nodes (cum <= 0.13s)flat  flat%   sum%        cum   cum%24.57s 94.03% 94.03%     26.06s 99.73%  main.bubbleSort (inline)1.49s  5.70% 99.73%      1.49s  5.70%  runtime.asyncPreempt0     0% 99.73%     26.06s 99.73%  main.main0     0% 99.73%     26.06s 99.73%  runtime.main
(pprof) list main.bubbleSort
Total: 26.13s
ROUTINE ======================== main.bubbleSort in /Users/zejia.lu/go_pprof/main.go24.57s     26.06s (flat, cum) 99.73% of Total.          .     15:	}.          .     16:	return nums.          .     17:}.          .     18:func bubbleSort(nums []int) {.          .     19:	for i := 0; i < len(nums); i++ {12.41s     13.31s     20:		for j := 1; j < len(nums)-i; j++ {4.33s      4.92s     21:			if nums[j] < nums[j-1] {7.83s      7.83s     22:				nums[j], nums[j-1] = nums[j-1], nums[j].          .     23:			}.          .     24:		}.          .     25:	}.          .     26:}.          .     27:

4、输出列解析

flat	当前函数占用 cpu 耗时
flat %	当前函数占用 cpu 耗时百分比
sum%	函数占用 cpu 时间累积占比，从小到大一直累积到 100%
cum	    当前函数加上调用当前函数的函数占用 cpu 的总耗时
%cum	当前函数加上调用当前函数的函数占用 cpu 的总耗时占比

5、结果分析

我们可以看到最消耗cpu的函数：
24.57s 94.03% 94.03%     26.06s 99.73%  main.bubbleSort (inline)我们可以看到这个函数里cpu消耗在哪里：
12.41s     13.31s     20:		for j := 1; j < len(nums)-i; j++ {
4.33s      4.92s     21:			if nums[j] < nums[j-1] {
7.83s      7.83s     22:				nums[j], nums[j-1] = nums[j-1], nums[j]

3、pprof ui方式查看程序最消耗cpu的地方

1、调试时指定通过ui方式查看，ui地址为8888端口，要调试的服务暴露的pprof端口为8899：

go tool pprof -http=":8888" http://localhost:8899/debug/pprof/profile

2、访问8888端口查看ui界面进行可视化调试：

查看最消耗cpu的地方：

4、pprof ui方式查看cpu消耗拓扑图

5、pprof ui方式查看cpu消耗火焰图

生成追踪图和火焰图需要安装graphviz

brew install graphviz

常用命令

// 查看cpu消耗前20的函数调用
top 20// 查看累计cpu消耗前20的函数调用
top -cum 20// 查看代码符号附近的cpu占用情况。其中代码符号类似于c++的函数符号表，可以简单理解成函数名
list "代码符号"