tp: scope pprof archive members and intern their fallback mappings

An archive with dozens of pprofs currently imports as an undifferentiated
blob: every profile lands on the hard-coded "pprof_file" scope. Scope each
profile by its source file instead: TraceFileTracker gains a CurrentFile()
accessor and the pprof reader walks the file-nesting chain past the gzip
layer to the nearest named ancestor. The file id is captured on the first
Parse() call -- ParseProfile runs from OnPushDataToSorter, which may fire
after the end-of-file notifications have popped the trace-file parsing
stack, so reading CurrentFile() there would make scope attribution depend
on pipeline ordering.

Locations without a pprof mapping each allocated a fresh dummy mapping, so
identical frames never interned across profiles and callsites multiplied
by the profile count: a 32 MB / 1000-profile archive peaked at 1.8 GB and
OOMed the Wasm heap. Intern the shared fallback mapping and skip
re-symbolizing interned frames; the same archive now peaks at 647 MB.

Diff tests lock the behaviour in: zip/tar members are scoped by member
file name (walking past the unnamed gzip layer), directly opened pprofs
keep the "pprof_file" scope, duplicate archive members do not duplicate
frames/mappings/symbols, and mapping-less locations share a single
interned "[unknown]" fallback mapping (asserted with a minimal
hand-encoded pprof, since no checked-in pprof lacks mappings).
4 files changed
tree: 142a4a10430dfa5ffa9022d96c20bbb6d25b3cd4
  1. .github/
  2. ai/
  3. bazel/
  4. build_overrides/
  5. buildtools/
  6. contrib/
  7. docs/
  8. examples/
  9. gn/
  10. include/
  11. infra/
  12. protos/
  13. python/
  14. sdk/
  15. src/
  16. test/
  17. third_party/
  18. tools/
  19. ui/
  20. .bazelignore
  21. .bazelrc
  22. .bazelversion
  23. .clang-format
  24. .clang-tidy
  25. .git-blame-ignore-revs
  26. .gitallowed
  27. .gitattributes
  28. .gitignore
  29. .gn
  30. .style.yapf
  31. Android.bp
  32. Android.bp.extras
  33. BUILD
  34. BUILD.extras
  35. BUILD.gn
  36. CHANGELOG
  37. CONTRIBUTORS.txt
  38. DIR_METADATA
  39. heapprofd.rc
  40. LICENSE
  41. meson.build
  42. METADATA
  43. MODULE.bazel
  44. MODULE.bazel.lock
  45. MODULE_LICENSE_APACHE2
  46. OWNERS
  47. OWNERS.github
  48. perfetto.rc
  49. perfetto_flags.aconfig
  50. PerfettoIntegrationTests.xml
  51. persistent_cfg.pbtxt
  52. README.chromium
  53. README.md
  54. TEST_MAPPING
  55. traced_perf.rc
  56. WORKSPACE
README.md

Perfetto - System profiling, app tracing and trace analysis

Perfetto is an open-source suite of SDKs, daemons and tools which use tracing to help developers understand the behaviour of complex systems and root-cause functional and performance issues on client and embedded systems.

It is a production-grade tool that is the default tracing system for the Android operating system and the Chromium browser.

Core Components

Perfetto is not a single tool, but a collection of components that work together:

  • High-performance tracing daemons: For capturing tracing information from many processes on a single machine into a unified trace file.
  • Low-overhead tracing SDK: A C++17 library for direct userspace-to-userspace tracing of timings and state changes in your application.
  • Extensive OS-level probes: For capturing system-wide context on Android and Linux (e.g. scheduling states, CPU frequencies, memory profiling, callstack sampling).
  • Browser-based UI: A powerful, fully local UI for visualizing and exploring large, multi-GB traces on a timeline. It works in all major browsers, requires no installation, and can open traces from other tools.
  • SQL-based analysis library: A powerful engine that allows you to programmatically query traces using SQL to automate analysis and extract custom metrics.

Why Use Perfetto?

Perfetto was designed to be a versatile and powerful tracing system for a wide range of use cases.

  • For Android App & Platform Developers: Debug and root-cause functional and performance issues like slow startups, dropped frames (jank), animation glitches, low memory kills, and ANRs. Profile both Java/Kotlin and native C++ memory usage with heap dumps and profiles.
  • For C/C++ Developers (Linux, macOS, Windows): Use the Tracing SDK to instrument your application with custom trace points to understand its execution flow, find performance bottlenecks, and debug complex behavior. On Linux, you can also perform detailed CPU and native heap profiling.
  • For Linux Kernel & System Developers: Get deep insights into kernel behavior. Perfetto acts as an efficient userspace daemon for ftrace, allowing you to visualize scheduling, syscalls, interrupts, and custom kernel tracepoints on a timeline.
  • For Chromium Developers: Perfetto is the tracing backend for chrome://tracing. Use it to debug and root-cause issues in the browser, V8, and Blink.
  • For Performance Engineers & SREs: Analyze and visualize a wide range of profiling and tracing formats, not just Perfetto's. Use the powerful SQL interface to programmatically analyze traces from tools like Linux perf, macOS Instruments, Chrome JSON traces, and more.

Getting Started

We‘ve designed our documentation to guide you to the right information as quickly as possible, whether you’re a newcomer to performance analysis or an experienced developer.

  1. New to tracing? If you're unfamiliar with concepts like tracing and profiling, start here:

  2. Ready to dive in? Our “Getting Started” guide is the main entry point for all users. It will help you find the right tutorials and documentation for your specific needs:

  3. Want the full overview? For a comprehensive look at what Perfetto is, why it's useful, and who uses it, see our main documentation page:

Debian Distribution

For users interested in the Debian distribution of Perfetto, the official source of truth and packaging efforts are maintained at Debian Perfetto Salsa Repository

Community & Support

Have questions? Need help?

We follow Google's Open Source Community Guidelines.