Go CPU和內存分析入門


我將說明使用Dave Cheney的軟件包進行性能分析,該軟件包通過在我們的程序中添加單行代碼使程序非常易於調試main()





go get github.com/pkg/profile



package main

import ( //… github.com/pkg/profile )

func main() { // CPU profiling by default defer profile.Start().Stop()

<span style="color:#75715e">//...




2017/08/03 14:26:28 profile: cpu profiling enabled, /var/...../cpu.pprof

Step #4: install graphviz if you don’t have it installed yet

This is used to generate the graph on a pdf. On a Mac, it’s a simple brew install graphviz. Refer to https://www.graphviz.org for other platforms.

Step #5: run go tool pprof

Pass your binary location, and the location of the cpu.pprof file as returned when running your program.

You can generate the analysis in various formats. The PDF one is pretty amazing:

go tool pprof --pdf ~/go/bin/yourbinary /var/path/to/cpu.pprof > file.pdf

You can generate other kind of visualizations as well, e.g. txt:

go tool pprof --txt ~/go/bin/yourbinary /var/path/to/cpu.pprof > file.txt

Memory profiling

Memory profiling is essentially the same as CPU profiling, but instead of using the default configuration for profile.Start(), we pass a profile.MemProfile flag:

defer profile.Start(profile.MemProfile).Stop()

thus the code becomes

package main

import ( //… github.com/pkg/profile )

func main() { // Memory profiling defer profile.Start(profile.MemProfile).Stop()

<span style="color:#75715e">//...


and when running the program, it will generate a mem.pprof file instead of cpu.pprof.

Read more about profiling Go apps

This is just a start. Read more at:

More go tutorials: