### Pull Request Checklist <!-- Please read https://matrix-org.github.io/dendrite/development/contributing before submitting your pull request --> I was reading through the Dendrite documentation on https://matrix-org.github.io/dendrite/development/contributing and noticed the installation link leads to a 404 error. This link works fine if it is viewed directly from [docs/CONTRIBUTING.md](https://github.com/matrix-org/dendrite/blob/main/docs/CONTRIBUTING.md) but this might not be very obvious to new contributors who are reading through the [contribution page](https://matrix-org.github.io/dendrite/development/contributing) directly. This PR is mainly a small re-organization of the online documentation mainly in the [Development](https://matrix-org.github.io/dendrite/development) tab along with any links throughout the doc that may be impacted by the change. This does not contain any Go unit tests as this does not actually touch core dendrite functionality. * [ ] I have added Go unit tests or [Complement integration tests](https://github.com/matrix-org/complement) for this PR _or_ I have justified why this PR doesn't need tests * [x] Pull request includes a [sign off below using a legally identifiable name](https://matrix-org.github.io/dendrite/development/contributing#sign-off) _or_ I have already signed off privately Signed-off-by: `Kento Okamoto <kentokamoto@proton.me>`
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title | parent | permalink |
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Profiling | Development | /development/profiling |
Profiling Dendrite
If you are running into problems with Dendrite using excessive resources (e.g. CPU or RAM) then you can use the profiler to work out what is happening.
Dendrite contains an embedded profiler called pprof
, which is a part of the standard Go toolchain.
Enable the profiler
To enable the profiler, start Dendrite with the PPROFLISTEN
environment variable. This variable specifies which address and port to listen on, e.g.
PPROFLISTEN=localhost:65432 ./bin/dendrite-monolith-server ...
If pprof has been enabled successfully, a log line at startup will show that pprof is listening:
WARN[2020-12-03T13:32:33.669405000Z] [/Users/neilalexander/Desktop/dendrite/internal/log.go:87] SetupPprof
Starting pprof on localhost:65432
All examples from this point forward assume PPROFLISTEN=localhost:65432
but you may need to adjust as necessary for your setup.
Profiling CPU usage
To examine where CPU time is going, you can call the profile
endpoint:
http://localhost:65432/debug/pprof/profile?seconds=30
The profile will run for the specified number of seconds
and then will produce a result.
Examine a profile using the Go toolchain
If you have Go installed and want to explore the profile, you can invoke go tool pprof
to start the profile directly. The -http=
parameter will instruct go tool pprof
to start a web server providing a view of the captured profile:
go tool pprof -http=localhost:23456 http://localhost:65432/debug/pprof/profile?seconds=30
You can then visit http://localhost:23456
in your web browser to see a visual representation of the profile. Particularly usefully, in the "View" menu, you can select "Flame Graph" to see a proportional interactive graph of CPU usage.
Download a profile to send to someone else
If you don't have the Go tools installed but just want to capture the profile to send to someone else, you can instead use curl
to download the profiler results:
curl -O http://localhost:65432/debug/pprof/profile?seconds=30
This will block for the specified number of seconds, capturing information about what Dendrite is doing, and then produces a profile
file, which you can send onward.
Profiling memory usage
To examine where memory usage is going, you can call the heap
endpoint:
http://localhost:65432/debug/pprof/heap
The profile will return almost instantly.
Examine a profile using the Go toolchain
If you have Go installed and want to explore the profile, you can invoke go tool pprof
to start the profile directly. The -http=
parameter will instruct go tool pprof
to start a web server providing a view of the captured profile:
go tool pprof -http=localhost:23456 http://localhost:65432/debug/pprof/heap
You can then visit http://localhost:23456
in your web browser to see a visual representation of the profile. The "Sample" menu lets you select between four different memory profiles:
inuse_space
: Shows how much actual heap memory is allocated per function (this is generally the most useful profile when diagnosing high memory usage)inuse_objects
: Shows how many heap objects are allocated per functionalloc_space
: Shows how much memory has been allocated per function (although that memory may have since been deallocated)alloc_objects
: Shows how many allocations have been made per function (although that memory may have since been deallocated)
Also in the "View" menu, you can select "Flame Graph" to see a proportional interactive graph of the memory usage.
Download a profile to send to someone else
If you don't have the Go tools installed but just want to capture the profile to send to someone else, you can instead use curl
to download the profiler results:
curl -O http://localhost:65432/debug/pprof/heap
This will almost instantly produce a heap
file, which you can send onward.