Add new track for top level scroll jank summary.

This track includes slices for
* Scrolling intervals (total time scrolling regardless of the
number of scrolls
* Jank duration during the scrolling interval
* Specific causes of scroll jank

See screenshot: https://screenshot.googleplex.com/8vtrtwa6rqRWcUa.png

Additionally migrate to a unified Scroll Jank selection type; we can
migrate further to a single Custom Track selection type in a future
patch for further reuse. In the same vein, added a generic details
panel for scroll jank, that we can migrate out into a generic
Custom Details Panel in a future patch.

NOTE: The event latencies track will be revised in this patch:
https://android-review.git.corp.google.com/c/platform/external/perfetto/+/2576994.
Changes may include where the track is rendered in the UI.

Bug: b/225885015
Change-Id: I220b10a12621000a1cc1307d12721a51137379a7
24 files changed
tree: 0adde5557b3b85ced726e9393d1d701e982747e8
  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. third_party/
  16. tools/
  17. ui/
  18. .clang-format
  19. .clang-tidy
  20. .git-blame-ignore-revs
  21. .gitattributes
  22. .gitignore
  23. .gn
  24. .style.yapf
  25. Android.bp
  26. Android.bp.extras
  27. BUILD
  28. BUILD.extras
  29. BUILD.gn
  30. CHANGELOG
  31. codereview.settings
  32. DIR_METADATA
  33. heapprofd.rc
  34. LICENSE
  35. meson.build
  36. METADATA
  37. MODULE_LICENSE_APACHE2
  38. OWNERS
  39. perfetto.rc
  40. PerfettoIntegrationTests.xml
  41. PRESUBMIT.py
  42. README.chromium
  43. README.md
  44. TEST_MAPPING
  45. traced_perf.rc
  46. 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.