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fuchsia/third_party/github.com/google/perfetto/43e84a00efa142eae7876a5fee171b4d18665278
commit
43e84a00efa142eae7876a5fee171b4d18665278
[log]
author
Lalit Maganti <lalitm@google.com>
Tue Aug 11 18:38:03 2026 +0100
committer
GitHub <noreply@github.com>
Tue Aug 11 18:38:03 2026 +0100
tree
10b264f2a828d8283e8ff3ab7e13b56fd6c18762
parent
b81398d2c98767c5ac927d17779e83856fd5c23a [diff]
tp: copy dense Arrow columns straight from their pieces (#7061)

A buffer spanning more than one of the chunks the embedder pushed was
joined
into a fresh allocation by `TraceBlobViewReader::SliceOff` before being
copied
again into column storage, so those bytes were copied twice.

Dense columns only need the bytes moved, so
`BodyReader::ReadExactPieces` hands
back the pieces as they arrived and each is copied straight into its
place in
the column's `FlexVector`. Sparse columns keep taking a contiguous
slice, since
they index by row rather than copying straight through.

A bulk byte copy does not care where the piece boundaries fall, so this
needs no
handling for values split across chunks, and it works for any chunking —
including WASM, where the file cannot be mmapped and buffers routinely
span
several pushed chunks.

Reimporting a 2.26GB archive goes from 2.36s to 2.02s. The existing
`RoundTripChunkedInput` test already drives the multi-piece path.

Third of a three-PR stack, based on #7060.
1 file changed
tree: 10b264f2a828d8283e8ff3ab7e13b56fd6c18762
  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. CLAUDE.md ⇨ docs/AGENTS.md
  21. GEMINI.md ⇨ docs/AGENTS.md
  22. .bazelignore
  23. .bazelrc
  24. .bazelversion
  25. .clang-format
  26. .clang-tidy
  27. .git-blame-ignore-revs
  28. .gitallowed
  29. .gitattributes
  30. .gitignore
  31. .gn
  32. .style.yapf
  33. Android.bp
  34. Android.bp.extras
  35. BUILD
  36. BUILD.extras
  37. BUILD.gn
  38. CHANGELOG
  39. CONTRIBUTORS.txt
  40. DIR_METADATA
  41. heapprofd.rc
  42. LICENSE
  43. meson.build
  44. METADATA
  45. MODULE.bazel
  46. MODULE.bazel.lock
  47. MODULE_LICENSE_APACHE2
  48. OWNERS
  49. OWNERS.github
  50. perfetto.rc
  51. perfetto_flags.aconfig
  52. PerfettoIntegrationTests.xml
  53. persistent_cfg.pbtxt
  54. README.chromium
  55. README.md
  56. TEST_MAPPING
  57. traced_perf.rc
  58. 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.