Go's pprof tool & format

The various profilers built into Go are designed to work with the pprof visualization tool. The upstream pprof tool is designed to work with C++, Java and Go programs, but it's recommended to access the tool via the go tool pprof version that's bundled with the Go core. It's largely the same except for a few tweaks.

Features

The pprof tool features an interactive command line interface, but also a Web UI, as well as various other output format options.

File Format

Description

The pprof tool defines a protocol buffer output format, which is always stored with gzip compression and described in great detail this README as well as the profile.proto definition file itself.

pprof's data format appears to be designed to for efficency, multiple languages and different profile types (CPU, Heap, etc.), but because of this it's very abstract and full of indirection. If you want all the details, follow the links above. If you want the tl;dr, keep reading:

A pprof file contains a list of stack traces called samples that have one or more numeric value associated with them. For a CPU profile the value might be the CPU time duration in nanoseonds that the stack trace was observed for during profiling. For a heap profile it might be the number of bytes allocated. The value types themselves are described in the beginning of the file and used to populate the "SAMPLE" drop down in the pprof UI. In addition to the values, each stack trace can also include a set of labels. The labels are key-value pairs and can even include a unit. In Go those labels are used for profiler labels.

The profile also includes the time (in UTC) that the profile was recorded, and the duration of the recording.

Additionally the format allows for drop/keep regexes for excluding/including certain stack traces, but they're not used by Go. There is also room for a list of comments (not used either), as well as describing the periodic interval at which samples were taken.

The code for generating pprof output in Go can be found in: runtime/pprof/proto.go.

Decoding

Using `go tool pprof`

The easiest way to decode a pprof file and see its contents is to use go tool pprof -raw. The output is formatted for human readability, so arguabiliy it's not as -raw as the protoc output shown later on.

Let's have a look at the examples/cpu/pprof.samples.cpu.001.pb.gz CPU profile included in this repository:

$ go tool pprof -raw examples/cpu/pprof.samples.cpu.001.pb.gz

PeriodType: cpu nanoseconds
Period: 10000000
Time: 2021-01-08 17:10:32.116825 +0100 CET
Duration: 3.13
Samples:
samples/count cpu/nanoseconds
         19  190000000: 1 2 3
          5   50000000: 4 5 2 3
          1   10000000: 6 7 8 9 10 11 12 13 14
          1   10000000: 15 16 17 11 18 14
          2   20000000: 6 7 8 9 10 11 18 14
          7   70000000: 19 20 21 22 23 24 14
          3   30000000: 25 26 27 28
Locations
     1: 0x1372f7f M=1 main.computeSum /Users/felix.geisendoerfer/go/src/github.com/felixge/go-profiler-notes/examples/cpu/main.go:39 s=0
     2: 0x13730f2 M=1 main.run.func2 /Users/felix.geisendoerfer/go/src/github.com/felixge/go-profiler-notes/examples/cpu/main.go:31 s=0
     3: 0x1372cf8 M=1 golang.org/x/sync/errgroup.(*Group).Go.func1 /Users/felix.geisendoerfer/go/pkg/mod/golang.org/x/sync@v0.0.0-20201207232520-09787c993a3a/errgroup/errgroup.go:57 s=0
     ...
Mappings
1: 0x0/0x0/0x0   [FN]

The output above is truncated, examples/cpu/pprof.samples.cpu.001.pprof.txt has the full version.

Using `protoc`

For those interested in seeing data closer to the raw binary storage, we need the protoc protocol buffer compiler. On macOS you can use brew install protobuf to install it, for other platform take a look at the README's install section.

Now let's take a look at the same CPU profile from above:

$ gzcat examples/cpu/pprof.samples.cpu.001.pb.gz | protoc --decode perftools.profiles.Profile ./profile.proto

sample_type {
  type: 1
  unit: 2
}
sample_type {
  type: 3
  unit: 4
}
sample {
  location_id: 1
  location_id: 2
  location_id: 3
  value: 19
  value: 190000000
}
sample {
  location_id: 4
  location_id: 5
  location_id: 2
  location_id: 3
  value: 5
  value: 50000000
}
...
mapping {
  id: 1
  has_functions: true
}
location {
  id: 1
  mapping_id: 1
  address: 20393855
  line {
    function_id: 1
    line: 39
  }
}
location {
  id: 2
  mapping_id: 1
  address: 20394226
  line {
    function_id: 2
    line: 31
  }
}
...
function {
  id: 1
  name: 5
  system_name: 5
  filename: 6
}
function {
  id: 2
  name: 7
  system_name: 7
  filename: 6
}
...
string_table: ""
string_table: "samples"
string_table: "count"
string_table: "cpu"
string_table: "nanoseconds"
string_table: "main.computeSum"
string_table: "/Users/felix.geisendoerfer/go/src/github.com/felixge/go-profiler-notes/examples/cpu/main.go"
...
time_nanos: 1610122232116825000
duration_nanos: 3135113726
period_type {
  type: 3
  unit: 4
}
period: 10000000

The output above is truncated also, pprof.samples.cpu.001.protoc.txt has the full version.

Todo

Write more about using go tool pprof itself.
Explain why pprof can be given a path to the binary the profile belongs to.
Get into more details about line numbers / addresses.
Talk about mappings and when a Go binary might have more than one

Disclaimers

I work at Datadog on Continuous Profiling for Go. You should check it out. We're also hiring : ).

The information on this page is believed to be correct, but no warranty is provided. Feedback is welcome!

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