#Profiling

In this section, we'll explore how to profile Rspack for identifying bottlenecks. By examining where Rspack spends its time, we can gain insights into how to improve performance. Since different profilers have different strengths. It is good to use more than one.

#Build release version with debug info

Performance analysis should be conducted on a release version that includes debug information. This approach ensures accurate performance results while providing sufficient debug information for analysis. Use the following command to profiling using local build rspack.

1. Build a release version with debug information:

pnpm build:binding:profiling

2. Change @rspack/core and @rspack/cli to use link protocol to link to local build Rspack:

  dependencies: {
-    "@rspack/core": "x.y.z",
-    "@rspack/cli": "x.y.z",
     # link protocol only works in pnpm
+    "@rspack/core": "link:{your_rspack_repo}/packages/rspack",
+    "@rspack/cli": "link:{your_rspack_repo}/packages/rspack-cli"
  }

3. Reinstall:

pnpm install

#CPU profiling

#Samply

Samply supports performance analysis for both Rust and JavaScript simultaneously. Follow these steps to perform a complete performance analysis:

• Run the following command to start performance analysis:

samply record -- node --perf-prof --perf-basic-prof --interpreted-frames-native-stack {your_rspack_folder}/rspack-cli/bin/rspack.js -c {your project}/rspack.config.js

• After the command execution, the analysis results will automatically open in the Firefox Profiler. The screenshot below is from a Samply profiler.

#JavaScript profiling

Rspack’s JavaScript typically runs in the Node.js thread. Select the Node.js thread to view the time distribution on the Node.js side.

#Rust profiling

Rspack’s Rust code usually runs in the tokio thread. Select the tokio thread to view the time distribution on the Rust side.

#Rsdoctor timeline

If we want to analyze the time cost of loaders and plugins or the compilation behavior of loaders, we can use Rsdoctor to view:

Refer to Rsdoctor Compilation Analysis

#Mac Xcode instruments

Xcode instruments can be used to produce a CPU profile if you are on a Mac.

To install Xcode Instruments, simply install the Command Line Tools:

xcode-select --install

For normal Rust builds, cargo instruments can be used as the glue for profiling and creating the trace file.

Since Rspack takes quite a while to build, you can use the following procedure without invoking cargo instruments. It has the same effect.

In workspace root's Cargo.toml, turn on debug symbols and disable symbol stripping in the [profile.release] section

[profile.release]
debug = 1 # debug info with line tables only
strip = false # do not strip symbols

Then build the project

pnpm run build:cli:release

The final binary is located at packages/rspack-cli/bin/rspack once the project is built.

Under the hood, cargo instruments invokes the xcrun command, which means we can run the following in our own project that uses Rspack.

xcrun xctrace record --template 'Time Profile' --output . --launch -- /path/to/rspack/packages/rspack-cli/bin/rspack build

It produces the following output

Starting recording with the Time Profiler template. Launching process: rspack.
Ctrl-C to stop the recording
Target app exited, ending recording...
Recording completed. Saving output file...
Output file saved as: Launch_rspack_2023-04-24_11.32.06_9CFE3A63.trace

We can open the trace file by

open Launch_rspack_2023-04-24_11.32.06_9CFE3A63.trace