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flutter / third_party / perfetto / d15fb7ed0fc139f9441062c2371bb89d6979ae34
commitd15fb7ed0fc139f9441062c2371bb89d6979ae34[log] [tgz]
authorRyan Savitski <rsavitski@google.com>Tue Jul 26 14:41:50 2022 +0100
committerRyan Savitski <rsavitski@google.com>Tue Jul 26 14:41:50 2022 +0100
treec04d476c4e20c8d02e9f2aaffdb7d631cdc6ce6f
parent79350c98f2cee15490cfc8afb1ac35e640f29396 [diff]
traced_perf: process sharding (choosing random processes for callstacks)

The config will specify N shards for one or more data sources, we need
to choose a random value [0,N) to use as the shard for all those data
sources. We know which sources share a session (i.e. a config) via
tracing_session_id as supplied by traced.

Instead of introducing session-scoped data and linking that to the
lifetime of data sources, I've opted to simply replicate this state in
each DataSourceState. The extra plumbing through EventConfig::Create is
a bit clumsy, but ultimately TargetFilter is a logical place to host
this state.

Doc: go/tperf-sharding
Bug: 223773242
Change-Id: I84982c819ef541735bf3c6821c30efed2122ae94
8 files changed
tree: c04d476c4e20c8d02e9f2aaffdb7d631cdc6ce6f
  1. .github/
  2. bazel/
  3. build_overrides/
  4. buildtools/
  5. debian/
  6. docs/
  7. examples/
  8. gn/
  9. include/
  10. infra/
  11. protos/
  12. python/
  13. src/
  14. test/
  15. tools/
  16. ui/
  17. .clang-format
  18. .clang-tidy
  19. .gitattributes
  20. .gitignore
  21. .gn
  22. .style.yapf
  23. Android.bp
  24. Android.bp.extras
  25. BUILD
  26. BUILD.extras
  27. BUILD.gn
  28. CHANGELOG
  29. codereview.settings
  30. DIR_METADATA
  31. heapprofd.rc
  32. LICENSE
  33. meson.build
  34. METADATA
  35. MODULE_LICENSE_APACHE2
  36. OWNERS
  37. perfetto.rc
  38. PerfettoIntegrationTests.xml
  39. PRESUBMIT.py
  40. README.chromium
  41. README.md
  42. TEST_MAPPING
  43. traced_perf.rc
  44. WORKSPACE
README.md

Perfetto - System profiling, app tracing and trace analysis

Perfetto is a production-grade open-source stack for performance instrumentation and trace analysis. It offers services and libraries and for recording system-level and app-level traces, native + java heap profiling, a library for analyzing traces using SQL and a web-based UI to visualize and explore multi-GB traces.

See https://perfetto.dev/docs or the /docs/ directory for documentation.