Common tasks

The checklists below show how to achieve some common tasks in the codebase.

Add a new ftrace event

1. Find the format file for your event. The location of the file depends where tracefs is mounted but can often be found at /sys/kernel/debug/tracing/events/EVENT_GROUP/EVENT_NAME/format.
2. Copy the format file into the codebase at src/traced/probes/ftrace/test/data/synthetic/events/EVENT_GROUP/EVENT_NAME/format.
3. Add the event to src/tools/ftrace_proto_gen/event_list.
4. Run tools/run_ftrace_proto_gen. This will update protos/perfetto/trace/ftrace/ftrace_event.proto and protos/perfetto/trace/ftrace/GROUP_NAME.proto.
5. Run tools/gen_all out/YOUR_BUILD_DIRECTORY. This will update src/traced/probes/ftrace/event_info.cc and protos/perfetto/trace/perfetto_trace.proto.
6. If special handling in trace_processor is desired update src/trace_processor/importers/ftrace/ftrace_parser.cc to parse the event.
7. Upload and land your change as normal.

Here is an example change which added the ion/ion_stat event.

Contribute to SQL standard library

1. Add or edit an SQL file inside perfetto/src/trace_processor/stdlib/.
2. For a new file inside an existing module add the file to the corresponding BUILD.gn.
3. For a new module (subdirectory of /stdlib/), module name (directory name) has to be added to the list in /stdlib/BUILD.gn.

Files inside the standard library have to be formatted in a very specific way, as its structure is used to generate documentation. There are presubmit checks, but they are not infallible.

• Running the file cannot generate any data. There can be only CREATE PERFETTO FUNCTION, CREATE PERFETTO TABLE and CREATE PERFETTO VIEW statements inside.
• The name of each table/view/function needs to start with {module_name}_ or {internal_}. The names of views/tables/functions are must be [a-z_]. When a module is imported (using the IMPORT function), objects prefixed with internal should not be used.
  • The only exception is the common module. The name of functions/views/tables inside should not be prefixed with common_, as they are supposed to be module agnostic and widely used.
• Every table or view should have a schema.
• Every non internal object, as well as its function arguments and columns in its schema have to be prefixed with an SQL comment documenting it. Any text is going to be parsed as markdown, so usage of markdown functionality (code, links, lists) is encouraged. Whitespaces in anything apart from descriptions are ignored, so comments can be formatted neatly. If the line with description exceeds 80 chars, description can be continued in following lines.
  • Table/view: each has to have schema, object description and a comment above each column's definition in the schema.
    • Description is any text in the comment above CREATE PERFETTO {TABLE,VIEW} statement.
    • Column's comment is the text immediately above column definition in the schema.
  • Scalar Functions: each has to have a function description and description of return value in this order.
    • Function description is any text in the comment above CREATE PERFETTO FUNCTION statement.
    • For each argument there has to be a comment line immediately above argument definition.
    • Return comment should immediately precede RETURNS.
  • Table Functions: each has to have a function description, list of arguments (names, types, description) and list of columns.
    • Function description is any text in the comment above CREATE PERFETTO FUNCTION statement.
    • For each argument there has to be a comment line immediately above argument definition.
    • For each column there has to be a comment line immediately above column definition.

NOTE: Break lines outside of import description will be ignored.

Example of properly formatted view in module android:

-- Count Binder transactions per process.
CREATE PERFETTO VIEW android_binder_metrics_by_process(
  -- Name of the process that started the binder transaction.
  process_name STRING,
  -- PID of the process that started the binder transaction.
  pid INT,
-- Name of the slice with binder transaction.
  slice_name STRING,
-- Number of binder transactions in process in slice.
  event_count INT
) AS
SELECT
  process.name AS process_name,
  process.pid AS pid,
  slice.name AS slice_name,
  COUNT(*) AS event_count
FROM slice
INNER JOIN thread_track ON slice.track_id = thread_track.id
INNER JOIN thread ON thread.utid = thread_track.utid
INNER JOIN process ON thread.upid = process.upid
WHERE
  slice.name GLOB 'binder*'
GROUP BY
  process_name,
  slice_name;

Example of function in module common:

-- Extracts an int value with the given name from the metadata table.
CREATE PERFETTO FUNCTION extract_int_metadata(
  -- The name of the metadata entry.
  name STRING)
-- int_value for the given name. NULL if there's no such entry.
RETURNS LONG
AS SELECT int_value FROM metadata WHERE name = ($name)

Example of table function in module android:

-- Given a launch id and GLOB for a slice name, returns columns for matching slices.
CREATE PERFETTO FUNCTION ANDROID_SLICES_FOR_LAUNCH_AND_SLICE_NAME(
  -- Id of launch.
  launch_id INT,
  -- Name of slice with launch.
  slice_name STRING
)
RETURNS TABLE(
  -- Name of slice with launch.
  slice_name STRING,
  -- Timestamp of slice start.
  slice_ts INT,
  -- Duration of slice.
  slice_dur INT,
  -- Name of thread with slice.
  thread_name STRING,
  -- Arg set id.
  arg_set_id INT
)
AS
SELECT slice_name, slice_ts, slice_dur, thread_name, arg_set_id
FROM thread_slices_for_all_launches
WHERE launch_id = $launch_id AND slice_name GLOB $slice_name;

Add a new trace-based metric

1. Create the proto file containing the metric in the protos/perfetto/metrics folder. The appropriate BUILD.gn file should be updated as well.
2. Import the proto in protos/perfetto/metrics/metrics.proto and add a field for the new message.
3. Run tools/gen_all out/YOUR_BUILD_DIRECTORY. This will update the generated headers containing the descriptors for the proto.

• Note: this step has to be performed any time any metric-related proto is modified.
• If you don't see anything inside the out/ directory you might have to rerun tools/setup_all_configs.py.

4. Add a new SQL file for the metric to src/trace_processor/metrics. The appropriate BUILD.gn file should be updated as well.

• To learn how to write new metrics, see the trace-based metrics documentation.

5. Build all targets in your out directory with tools/ninja -C out/YOUR_BUILD_DIRECTORY.
6. Add a new diff test for the metric. This can be done by adding files to the tests.*.py files in a proper test/trace_processor subfolder.
7. Run the newly added test with tools/diff_test_trace_processor.py <path to trace processor binary>.
8. Upload and land your change as normal.

Here is an example change which added the time_in_state metric.

Add a new trace processor table

1. Create the new table in the appropriate header file in src/trace_processor/tables by copying one of the existing macro definitions.

• Make sure to understand whether a root or derived table is needed and copy the appropriate one. For more information see the trace processor documentation.

2. Register the table with the trace processor in the constructor for the TraceProcessorImpl class.
3. If also implementing ingestion of events into the table:
4. Modify the appropriate parser class in src/trace_processor/importers and add the code to add rows to the newly added table.
5. Add a new diff test for the added parsing code and table.
6. Run the newly added test with tools/diff_test_trace_processor.py <path to trace processor shell binary>.
7. Upload and land your change as normal.

Adding new derived events

As derived events depend on metrics, the initial steps are same as that of developing a metric (see above).

NOTE: the metric can be just an empty proto message during prototyping or if no summarization is necessary. However, generally if an event is important enough to display in the UI, it should also be tracked in benchmarks as a metric.

To extend a metric with annotations:

1. Create a new table or view with the name <metric name>_event.

• For example, for the android_startup metric, we create a view named android_startup_event.
• Note that the trailing _event suffix in the table name is important.
• The schema required for this table is given below.

2. List your metric in the initialiseHelperViews method of trace_controller.ts.
3. Upload and land your change as normal.

The schema of the <metric name>_event table/view is as follows:

Name	Type	Presence	Meaning
track_type	string	Mandatory	‘slice’ for slices, ‘counter’ for counters
track_name	string	Mandatory	Name of the track to display in the UI. Also the track identifier i.e. all events with same track_name appear on the same track.
ts	int64	Mandatory	The timestamp of the event (slice or counter)
dur	int64	Mandatory for slice, NULL for counter	The duration of the slice
slice_name	string	Mandatory for slice, NULL for counter	The name of the slice
value	double	Mandatory for counter, NULL for slice	The value of the counter
group_name	string	Optional	Name of the track group under which the track appears. All tracks with the same group_name are placed under the same group by that name. Tracks that lack this field or have NULL value in this field are displayed without any grouping.

Known issues:

• Nested slices within the same track are not supported. We plan to support this once we have a concrete usecase.
• Tracks are always created in the global scope. We plan to extend this to threads and processes in the near future with additional contexts added as necessary.
• Instant events are currently not supported in the UI but this will be implemented in the near future. In trace processor, instants are always 0 duration slices with special rendering on the UI side.
• There is no way to tie newly added events back to the source events in the trace which were used to generate them. This is not currently a priority but something we may add in the future.

Update TRACE_PROCESSOR_CURRENT_API_VERSION

Generally you do not have to worry about version skew between the UI and the trace_processor since they are built together at the same commit. However version skew can occur when using the --httpd mode which allows a native trace_processor instance to be used with the UI.

A common case is when the UI is more recent than trace_processor and depends on a new table definition. With older versions of trace_processor in --httpd mode the UI crashes attempting to query a non-existant table. To avoid this we use a version number. If the version number trace_processor reports is older than the one the UI was built with we prompt the user to update.

1. Go to protos/perfetto/trace_processor/trace_processor.proto
2. Increment TRACE_PROCESSOR_CURRENT_API_VERSION
3. Add a comment explaining what has changed.