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Created CustomPprofProfiles (markdown)
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CustomPprofProfiles.md
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CustomPprofProfiles.md
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Originally published at https://rakyll.org/custom-profiles/.
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Go provides several pprof profiles out of thet box to gather
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profiling data from Go programs.
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The builtin profiles provided by the [runtime/pprof](https://golang.org/pkg/runtime/pprof/) package:
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* **profile**: CPU profile determines where a program spends its time while actively consuming CPU cycles (as opposed while sleeping or waiting for I/O).
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* **heap**: Heap profile reports the currently live allocations; used to monitor current memory usage or check for memory leaks.
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* **threadcreate**: Thread creation profile reports the sections of the program that lead the creation of new OS threads.
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* **goroutine**: Goroutine profile report the stack traces of all current goroutines.
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* **block**: Block profile show where goroutines block waiting on synchronization primitives (including timer channels). Block profile is not enabled by default; use runtime.SetBlockProfileRate to enable it.
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* **mutex**: Mutex profile reports the lock contentions. When you think your CPU is not fully utilized due to a mutex contention, use this profile. Mutex profile is not enabled by default, see runtime.SetMutexProfileFraction to enable.
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Additional to the builtin profiles, [runtime/pprof](https://golang.org/pkg/runtime/pprof/) package allows you to export your custom profiles, and instrument your code to record
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execution stacks that contributes to this profile.
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Imagine we have a blob server, and we are writing a Go client for it. And our users want to be able to profile the opened blobs on the client. We can create a profile and record the events of blob opening and closing, so the user can tell how many open blobs they are at any time.
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Here is a blobstore package that allows you to open some blobs. We will create a new custom profile and start
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recording execution stacks that contributes to opening of blobs:
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``` go
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package blobstore
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import "runtime/pprof"
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var openBlobProfile = pprof.NewProfile("blobstore.Open")
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// Open opens a blob, all opened blobs need
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// to be closed when no longer in use.
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func Open(name string) (*Blob, error) {
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blob := &Blob{name: name}
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// TODO: Initialize the blob...
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openBlobProfile.Add(blob, 2) // add the current execution stack to the profile
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return blob, nil
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}
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```
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And once users want to close the blob, we need to remove the execution stack associated with the current blob from the profile:
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```go
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// Close closes the blob and frees the
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// underlying resources.
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func (b *Blob) Close() error {
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// TODO: Free other resources.
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openBlobProfile.Remove(b)
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return nil
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}
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```
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And now, from the programs using this package, we should be able to retrieve `blobstore.Open` profile data and use our daily pprof tools to examine and visualize them.
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Let's write a small main program than opens some blobs:
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```
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package main
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import (
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"fmt"
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"math/rand"
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"net/http"
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_ "net/http/pprof" // as a side effect, registers the pprof endpoints.
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"time"
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"myproject.org/blobstore"
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)
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func main() {
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for i := 0; i < 1000; i++ {
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name := fmt.Sprintf("task-blob-%d", i)
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go func() {
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b, err := blobstore.Open(name)
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if err != nil {
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// TODO: Handle error.
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}
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defer b.Close()
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// TODO: Perform some wrork, write to the blob.
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}()
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}
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http.ListenAndServe("localhost:8888", nil)
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}
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```
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Start the server, then use go tool to read and visualize the profile data:
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```
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$ go tool pprof http://localhost:8888/debug/pprof/blobstore.Open
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(pprof) top
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Showing nodes accounting for 800, 100% of 800 total
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flat flat% sum% cum cum%
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800 100% 100% 800 100% main.main.func1 /Users/jbd/src/hello/main.go
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```
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You will see that there are 800 open blobs and all openings are coming from main.main.func1. In this small example, there is nothing more to see, but in a complex server you can examine the hottest spots that works with an open blob and find out bottlenecks or leaks.
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