Trace Processor

The Trace Processor is a C++ library (/src/trace_processor) that ingests traces encoded in a wide variety of formats and exposes an SQL interface for querying trace events contained in a consistent set of tables. It also has other features including computation of summary metrics, annotating the trace with user-friendly descriptions and deriving new events from the contents of the trace.

Quickstart

The quickstart provides a quick overview on how to run SQL queries against traces using trace processor.

Introduction

Events in a trace are optimized for fast, low-overhead recording. Therefore traces need significant data processing to extract meaningful information from them. This is compounded by the number of legacy formats which are still in use and need to be supported in trace analysis tools.

The trace processor abstracts this complexity by parsing traces, extracting the data inside, and exposing it in a set of database tables which can be queried with SQL.

Features of the trace processor include:

• Execution of SQL queries on a custom, in-memory, columnar database backed by the SQLite query engine.
• Metrics subsystem which allows computation of summarized view of the trace (e.g. CPU or memory usage of a process, time taken for app startup etc.).
• Annotating events in the trace with user-friendly descriptions, providing context and explanation of events to newer users.
• Creation of new events derived from the contents of the trace.

The formats supported by trace processor include:

• Perfetto native protobuf format
• Linux ftrace
• Android systrace
• Chrome JSON (including JSON embedding Android systrace text)
• Fuchsia binary format
• Ninja logs (the build system)

The trace processor is embedded in a wide variety of trace analysis tools, including:

• trace_processor, a standalone binary providing a shell interface (and the reference embedder).
• Perfetto UI, in the form of a WebAssembly module.
• Android Graphics Inspector.
• Android Studio.

Concepts

The trace processor has some foundational terminology and concepts which are used in the rest of documentation.

Events

In the most general sense, a trace is simply a collection of timestamped “events”. Events can have associated metadata and context which allows them to be interpreted and analyzed.

Events form the foundation of trace processor and are one of two types: slices and counters.

Slices

A slice refers to an interval of time with some data describing what was happening in that interval. Some example of slices include:

• Scheduling slices for each CPU
• Atrace slices on Android
• Userspace slices from Chrome

Counters

A counter is a continuous value which varies over time. Some examples of counters include:

• CPU frequency for each CPU core
• RSS memory events - both from the kernel and polled from /proc/stats
• atrace counter events from Android
• Chrome counter events

Tracks

A track is a named partition of events of the same type and the same associated context. For example:

• Scheduling slices have one track for each CPU
• Sync userspace slice have one track for each thread which emitted an event
• Async userspace slices have one track for each “cookie” linking a set of async events

The most intuitive way to think of a track is to imagine how they would be drawn in a UI; if all the events are in a single row, they belong to the same track. For example, all the scheduling events for CPU 5 are on the same track:

Tracks can be split into various types based on the type of event they contain and the context they are associated with. Examples include:

• Global tracks are not associated to any context and contain slices
• Thread tracks are associated to a single thread and contain slices
• Counter tracks are not associated to any context and contain counters
• CPU counter tracks are associated to a single CPU and contain counters

Thread and process identifiers

The handling of threads and processes needs special care when considered in the context of tracing; identifiers for threads and processes (e.g. pid/tgid and tid in Android/macOS/Linux) can be reused by the operating system over the course of a trace. This means they cannot be relied upon as a unique identifier when querying tables in trace processor.

To solve this problem, the trace processor uses utid (unique tid) for threads and upid (unique pid) for processes. All references to threads and processes (e.g. in CPU scheduling data, thread tracks) uses utid and upid instead of the system identifiers.

Object-oriented tables

Modeling an object with many types is a common problem in trace processor. For example, tracks can come in many varieties (thread tracks, process tracks, counter tracks etc). Each type has a piece of data associated to it unique to that type; for example, thread tracks have a utid of the thread, counter tracks have the unit of the counter.

To solve this problem in object-oriented languages, a Track class could be created and inheritance used for all subclasses (e.g. ThreadTrack and CounterTrack being subclasses of Track, ProcessCounterTrack being a subclass of CounterTrack etc).

In trace processor, this “object-oriented” approach is replicated by having different tables for each type of object. For example, we have a track table as the “root” of the hierarchy with the thread_track and counter_track tables “inheriting from” the track table.

NOTE: The appendix below gives the exact rules for inheritance between tables for interested readers.

Inheritance between the tables works in the natural way (i.e. how it works in OO languages) and is best summarized by a diagram.

NOTE: For an up-to-date of how tables currently inherit from each other as well as a comprehensive reference of all the column and how they are inherited see the SQL tables reference page.

Writing Queries

Context using tracks

A common question when querying tables in trace processor is: “how do I obtain the process or thread for a slice?”. Phrased more generally, the question is “how do I get the context for an event?”.

In trace processor, any context associated with all events on a track is found on the associated track tables.

For example, to obtain the utid of any thread which emitted a measure slice

SELECT utid
FROM slice
JOIN thread_track ON thread_track.id = slice.track_id
WHERE slice.name = 'measure'

Similarly, to obtain the upids of any process which has a mem.swap counter greater than 1000

SELECT upid
FROM counter
JOIN process_counter_track ON process_counter_track.id = slice.track_id
WHERE process_counter_track.name = 'mem.swap' AND value > 1000

If the source and type of the event is known beforehand (which is generally the case), the following can be used to find the track table to join with

Event type	Associated with	Track table	Constraint in WHERE clause
slice	N/A (global scope)	track	type = 'track'
slice	thread	thread_track	N/A
slice	process	process_track	N/A
counter	N/A (global scope)	counter_track	type = 'counter_track'
counter	thread	thread_counter_track	N/A
counter	process	process_counter_track	N/A
counter	cpu	cpu_counter_track	N/A

On the other hand, sometimes the source is not known. In this case, joining with the track table and looking up the type column will give the exact track table to join with.

For example, to find the type of track for measure events, the following query could be used.

SELECT type
FROM slice
JOIN track ON track.id = slice.track_id
WHERE slice.name = 'measure'

Thread and process tables

While obtaining utids and upids are a step in the right direction, generally users want the original tid, pid, and process/thread names.

The thread and process tables map utids and upids to threads and processes respectively. For example, to lookup the thread with utid 10

SELECT tid, name
FROM thread
WHERE utid = 10

The thread and process tables can also be joined with the associated track tables directly to jump directly from the slice or counter to the information about processes and threads.

For example, to get a list of all the threads which emitted a measure slice

SELECT thread.name AS thread_name
FROM slice
JOIN thread_track ON slice.track_id = thread_track.id
JOIN thread USING(utid)
WHERE slice.name = 'measure'
GROUP BY thread_name

Metrics

TIP: To see how to add to add a new metric to trace processor, see the checklist here.

The metrics subsystem is a significant part of trace processor and thus is documented on its own page.

Annotations

TIP: To see how to add to add a new annotation to trace processor, see the checklist here.

Annotations attach a human-readable description to a slice in the trace. This can include information like the source of a slice, why a slice is important and links to documentation where the viewer can learn more about the slice. In essence, descriptions act as if an expert was telling the user what the slice means.

For example, consider the inflate slice which occurs during view inflation in Android. We can add the following description and link:

Description: Constructing a View hierarchy from pre-processed XML via LayoutInflater#layout. This includes constructing all of the View objects in the hierarchy, and applying styled attributes.

Creating derived events

TIP: To see how to add to add a new annotation to trace processor, see the checklist here.

This feature allows creation of new events (slices and counters) from the data in the trace. These events can then be displayed in the UI tracks as if they were part of the trace itself.

This is useful as often the data in the trace is very low-level. While low level information is important for experts to perform deep debugging, often users are just looking for a high level overview without needing to consider events from multiple locations.

For example, an app startup in Android spans multiple components including ActivityManager, system_server, and the newly created app process derived from zygote. Most users do not need this level of detail; they are only interested in a single slice spanning the entire startup.

Creating derived events is tied very closely to metrics subsystem; often SQL-based metrics need to create higher-level abstractions from raw events as intermediate artifacts.

From previous example, the startup metric creates the exact launching slice we want to display in the UI.

The other benefit of aligning the two is that changes in metrics are automatically kept in sync with what the user sees in the UI.

Alerts

Alerts are used to draw the attention of the user to interesting parts of the trace; this are usually warnings or errors about anomalies which occurred in the trace.

Currently, alerts are not implemented in the trace processor but the API to create derived events was designed with them in mind. We plan on adding another column alert_type (name to be finalized) to the annotations table which can have the value warning, error or null. Depending on this value, the Perfetto UI will flag these events to the user.

NOTE: we do not plan on supporting case where alerts need to be added to existing events. Instead, new events should be created using annotations and alerts added on these instead; this is because the trace processor storage is monotonic-append-only.

Appendix: table inheritance

Concretely, the rules for inheritance between tables works are as follows:

• Every row in a table has an id which is unique for a hierarchy of tables.
  • For example, every track will have an id which is unique among all tracks (regardless of the type of track)
• If a table C inherits from P, each row in C will also be in P with the same id
  • This allows for ids to act as “pointers” to rows; lookups by id can be performed on any table which has that row
  • For example, every process_counter_track row will have a matching row in counter_track which will itself have matching rows in track
• If a table C with columns A and B inherits from P with column A, A will have the same data in both C and P
  • For example, suppose
    • process_counter_track has columns name, unit and upid
    • counter_track has name and unit
    • track has name
  • Every row in process_counter_track will have the same name for the row with the same id in track and counter_track
  • Similarly, every row in process_counter_track will have both the same name and unit for the row with the same id in counter_track
• Every row in a table has a type column. This specifies the most specific table this row belongs to.
  • This allows dynamic casting of a row to its most specific type
  • For example, for if a row in the track is actually a process_counter_track, it's type column will be process_counter_track.