perfetto atrce

Perfetto Trace是一款由Google开源的高性能系统级追踪工具，它专为移动、嵌入式以及云环境设计，用于收集并分析系统性能数据。perfetto trace能够实时捕获各种类型的事件，包括CPU调度、内存分配、网络I/O、图形处理器操作等，并支持详细的上下文信息，方便开发者理解和调试复杂的系统行为。

使用perfetto trace，开发者可以创建定制化的trace配置文件，对特定部分的应用进行跟踪，然后通过perfetto的可视化工具如TraceView或在线分析平台进行查看和分析。它的优势在于高吞吐量、低开销和灵活的数据模型，使得性能分析变得更加精确和高效。

相关问题

perfetto UI

### Perfetto UI Introduction and Usage

Perfetto is an open-source performance tracing platform designed to provide detailed insights into system operations on Android devices as well as other systems that support this tool. The Perfetto user interface (UI), accessible via a web-based application, serves as a powerful visualization tool for analyzing trace data collected by the Perfetto tracer.

The Perfetto UI allows users to load traces either directly from connected devices or through uploading pre-recorded trace files. Once loaded, various aspects of device performance can be explored including CPU scheduling, memory allocation, disk I/O activity such as those obtained using `storaged` command with `-u` option[^1], network traffic, and more.

For interacting effectively within the Perfetto UI:

- **Navigating Traces:** Users may zoom in/out along timelines; pan across different sections of interest.

- **Inspecting Events:** Clickable events display additional metadata about specific occurrences during execution periods.

- **Filtering Data:** Filters help narrow down displayed information based upon event types, processes involved, etc., making it easier to focus analysis efforts where needed most.

An example Python script demonstrating how one might interact programmatically with Perfetto's capabilities could look like below but note actual implementation would depend heavily on intended use case specifics beyond simple interaction patterns shown here:

import subprocess

def start_trace():
    """Starts a perfetto trace session."""
    cmd = ["perfetto", "-c", "config.txt"]
    process = subprocess.Popen(cmd)
    
def stop_and_pull_trace(file_path):
    """Stops current perfetto trace and pulls generated file."""
    pull_cmd = f"adb shell ls /data/misc/perfetto-traces/*.trace > {file_path}"
    subprocess.run(pull_cmd, shell=True)

start_trace()
# ... perform actions you want to profile ...
stop_and_pull_trace("/path/to/local/file.trace")

--related questions--

1. How does one configure custom metrics collection when setting up Perfetto?
2. What are some common pitfalls encountered while interpreting results inside the Perfetto UI?
3. Can multiple instances of Perfetto tracers run simultaneously without interfering each other?
4. Is there any way to automate periodic capturing of performance snapshots over extended durations using Perfetto scripts?

perfetto使用

### 如何使用 Perfetto 进行性能跟踪和调试

#### 安装与配置
为了开始使用 Perfetto，需先安装并设置环境。可以从官方GitHub仓库下载源码或二进制文件[^1]。

#### 基本概念介绍
Perfetto是一个生产级的开源性能工具栈，旨在帮助开发者进行系统级和应用级别的性能分析和跟踪工作。其核心功能包括但不限于收集、处理以及展示来自不同平台的数据流，这些数据可以用来诊断应用程序的行为模式及其对底层硬件的影响程度[^3]。

#### 启动追踪会话
启动一次新的追踪可以通过命令行界面完成，在此之前应该确保已经正确设置了`PERFETTO_TRACING_SERVICE`环境变量指向本地运行的服务实例地址。对于大多数情况，默认值即可满足需求；而对于更复杂的场景，则可能需要自定义参数来调整采集频率或者其他行为特性[^2]。

# 开始一个新的追踪会话
$ perfetto --txt -o /path/to/output.trace proto://android/capture_config.proto

上述命令将会创建一个名为`output.trace`的新文件保存捕获到的信息，并按照指定路径存储下来以便后续查看或者分享给他人做进一步的研究之用。

#### 数据解析与查询
一旦获得了原始日志资料之后，就可以利用内置的支持SQL语法的功能来进行高效检索操作了。这使得即使面对海量的日志条目也能够迅速定位感兴趣的部分，从而加快问题排查的速度。下面给出了一段简单的Python脚本来演示如何连接至数据库并对其中的内容执行基本的选择语句：

import sqlite3

conn = sqlite3.connect('/path/to/output.trace')
cursor = conn.cursor()

query = """
SELECT ts, name FROM slice WHERE dur > 0 ORDER BY ts ASC LIMIT 10;
"""
for row in cursor.execute(query):
    print(row)

conn.close()

这段代码片段展示了怎样通过SQLite接口读取trace文件中的时间戳(`ts`)字段同事件名称(`name`)之间的关联关系，并筛选出持续时间大于零秒的所有切片(slice)，最后按发生时刻升序排列取出前十个结果输出显示出来。

#### 可视化分析
除了依靠纯文本形式展现外，还可以借助于专门设计过的Web UI组件实现更加直观的效果呈现方式。只需打开浏览器访问[Perfetto WebUI](https://ui.perfetto.dev/)页面并将先前导出得到的`.trace`格式档案拖拽上传进去就可以了。该界面上集成了多种图表样式可供选择，允许用户根据不同视角深入理解整个系统的运作机制。

#### 学习更多
想要深入了解Perfetto的各项特性和最佳实践案例的话，建议参考项目主页上的文档资源，那里不仅有详尽的操作指南还有丰富的实战经验总结等待着大家去发掘。