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      • 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
      1. Change @rspack/core and @rspack/cli to use link protocol to link to local build Rspack:
      package.json
        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"
  }
      1. 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
      Warning

      Node.js currently only supports --perf-prof on Linux platforms. JavaScript profiling in Samply depends on --perf-prof support. If you need to use Samply for JavaScript profiling on other platforms, consider using Docker for profiling, or you can compile Node.js yourself for macOS using node-perf-maps for profiling purposes.

      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.

      Javascript Profiling

      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.

      Rust Profiling

      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:

      image

      Refer to Rsdoctor Compilation Analysis

      Mac Xcode instruments

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

      image

      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