There are several ways to profile sbt. The new hotness in profiling is FlameGraph. You first collect stack trace samples, and then it is processed into svg graph. See:
- Using FlameGraphs To Illuminate The JVM by Nitsan Wakart
- USENIX ATC '17: Visualizing Performance with Flame Graphs
The first one I recommend is async-profiler. This is available for macOS and Linux, and works fairly well.
- Download the installer from https://github.com/jvm-profiling-tools/async-profiler/releases/tag/v1.2
- Make symbolic link to
build/
andprofiler.sh
to$HOME/bin
, assuming you have PATH to$HOME/bin
:ln -s ~/Applications/async-profiler/profiler.sh $HOME/bin/profiler.sh
ln -s ~/Applications/async-profiler/build $HOME/bin/build
Next, close all Java applications and anything that may affect the profiling, and run sbt in one terminal:
$ sbt exit
In another terminal, run:
$ jps
92746 sbt-launch.jar
92780 Jps
This tells you the process ID of sbt. In this case, it's 92746. While it's running, run
$ profiler.sh -d 60 <process id>
Started [cpu] profiling
--- Execution profile ---
Total samples: 31602
Non-Java: 3239 (10.25%)
GC active: 46 (0.15%)
Unknown (native): 14667 (46.41%)
Not walkable (native): 3 (0.01%)
Unknown (Java): 433 (1.37%)
Not walkable (Java): 8 (0.03%)
Thread exit: 1 (0.00%)
Deopt: 9 (0.03%)
Frame buffer usage: 55.658%
Total: 1932000000 (6.11%) samples: 1932
[ 0] java.lang.ClassLoader$NativeLibrary.load
[ 1] java.lang.ClassLoader.loadLibrary0
[ 2] java.lang.ClassLoader.loadLibrary
[ 3] java.lang.Runtime.loadLibrary0
[ 4] java.lang.System.loadLibrary
....
This should show a bunch of stacktraces that are useful. To visualize this as a flamegraph, run:
$ profiler.sh -d 60 -f /tmp/flamegraph.svg <process id>
This should produce /tmp/flamegraph.svg
at the end.
See https://gist.github.com/eed3si9n/82d43acc95a002876d357bd8ad5f40d5
One of the tricky things you come across while profiling is figuring out the process ID, while wnating to profile the beginning of the application.
For this purpose, we've added sbt.launcher.standby
JVM flag.
In the next version of sbt, you should be able to run:
$ sbt -J-Dsbt.launcher.standby=20s exit
This will count down for 20s before doing anything else.
If you want to try the mixed flamegraph, you can try perf-map-agent.
This uses dtrace
on macOS and perf
on Linux.
You first have to compile https://github.com/jvm-profiling-tools/perf-map-agent.
For macOS, here to how to export JAVA_HOME
before running cmake .
:
$ export JAVA_HOME=$(/usr/libexec/java_home)
$ cmake .
-- The C compiler identification is AppleClang 9.0.0.9000039
-- The CXX compiler identification is AppleClang 9.0.0.9000039
...
$ make
In addition, you have to git clone https://github.com/brendangregg/FlameGraph
In a fresh termimal, run sbt with -XX:+PreserveFramePointer
flag:
$ sbt -J-Dsbt.launcher.standby=20s -J-XX:+PreserveFramePointer exit
In the terminal that you will run the perf-map:
$ cd quicktest/
$ export JAVA_HOME=$(/usr/libexec/java_home)
$ export FLAMEGRAPH_DIR=$HOME/work/FlameGraph
$ jps
94592 Jps
94549 sbt-launch.jar
$ $HOME/work/perf-map-agent/bin/dtrace-java-flames 94549
dtrace: system integrity protection is on, some features will not be available
dtrace: description 'profile-99 ' matched 2 probes
Flame graph SVG written to DTRACE_FLAME_OUTPUT='/Users/xxx/work/quicktest/flamegraph-94549.svg'.
This would produce better flamegraph in theory, but the output looks too messy for sbt exit
case.
See https://gist.github.com/eed3si9n/b5856ff3d987655513380d1a551aa0df
This might be because it assumes that the operations are already JITed.
https://github.com/ktoso/sbt-jmh
Due to JIT warmup etc, benchmarking is difficult. JMH runs the same tests multiple times to remove these effects and comes closer to measuring the performance of your code.
There's also an integration with jvm-profiling-tools/async-profiler, apparently.
I'd also mention traditional JVM profiling tool. Since VisualVM is opensource, I'll mention this one: https://visualvm.github.io/
- First VisualVM.
- Start sbt from a terminal.
- You should see
xsbt.boot.Boot
under Local. - Open it, and select either sampler or profiler, and hit CPU button at the point when you want to start.
If you are familiar with YourKit, it also works similarly.