This is a tool used to convert performance profiles from Xcode's Instruments tool on macOS to pprof.
First clone the repo,
$ git clone https://github.com/google/instrumentsToPprof.git
The tool requires Go, which can be downloaded at the Go homepage
instrumentsToPprof
can be installed to the GOPATH
using
go install github.com/google/instrumentsToPprof@latest
or run directly in the repo using
go run main.go
The tool's input is the copied data from Deep Copy inside Instruments. The Deep Copy must be from the Time Profile tool in instruments, and the selection roots must be processes.
To get started, make a trace, either using xctrace
or in the Instruments app.
$ xcrun -r xctrace record --template 'Time Profiler' --all-processes --time-limit 5s --output 'profile.trace'
Open the trace in the Instruments tool, and select the process that you want to have converted.
Multiple processes may be selected using Cmd+Shift+C
. Then get the text data using Deep Copy
in the Edit menu.
Paste the deep copy to a text file and run instrumentsToPprof
which produces a file profile.pb.gz
.
This file can analyzed using the google/pprof tool.
$ instrumentsToPprof deep_copy_paste.txt
Alternatively, one can produce the profile.pb.gz
by piping the clipboard directly into instrumentsToPprof
$ pbpaste | instrumentsToPpof
instrumentsToPprof
also supports output from the sample
command on Mac.
To get a sample, run
$ sample <pid> -f <output-file>
and to produce a pprof from that sample, use the --format
flag
$ instrumentsToPprof --format=sample <output-file>
It's now possible to profile Google Chrome's various release channels (Stable, Beta, Dev, Canary) using instrumentsToPprof.
Use the new download_symbols.py script to download the symbols for the specific release version of Chrome you're profiling. For example:
download_symbols.py -v 115.0.5763.0 -o .
Then use Instruments' Time Profiler to gather a trace. Next, in Instruments,
select File > Symbols...
. Locate the Chrome or Chrome Helper process from
which you wanted the trace; sometimes it's easiest to find this using Chrome's
Task Manager, for example to find the PID of the GPU process. Then you can find
the specific PID in Instruments' list.
Click "Locate" next to the dSYM path, and navigate to the directory the
download_symbols.py
script created.
At this point, the stack traces for this process should be well symbolized in Instruments. If so, proceed with the deep copy instructions above, and pprof's flame graphs will look good.
This is not an officially supported Google product.