diff options
Diffstat (limited to 'simpleperf/doc/scripts_reference.md')
| -rw-r--r-- | simpleperf/doc/scripts_reference.md | 242 |
1 files changed, 88 insertions, 154 deletions
diff --git a/simpleperf/doc/scripts_reference.md b/simpleperf/doc/scripts_reference.md index 31dee02d..734c56d2 100644 --- a/simpleperf/doc/scripts_reference.md +++ b/simpleperf/doc/scripts_reference.md @@ -1,170 +1,182 @@ # Scripts reference -[TOC] +## Table of Contents -## Record a profile +- [Scripts reference](#scripts-reference) + - [Table of Contents](#table-of-contents) + - [app_profiler.py](#appprofilerpy) + - [Profile from launch of an application](#profile-from-launch-of-an-application) + - [api_profiler.py](#apiprofilerpy) + - [run_simpleperf_without_usb_connection.py](#runsimpleperfwithoutusbconnectionpy) + - [binary_cache_builder.py](#binarycachebuilderpy) + - [run_simpleperf_on_device.py](#runsimpleperfondevicepy) + - [report.py](#reportpy) + - [report_html.py](#reporthtmlpy) + - [inferno](#inferno) + - [purgatorio](#purgatorio) + - [pprof_proto_generator.py](#pprofprotogeneratorpy) + - [report_sample.py](#reportsamplepy) + - [simpleperf_report_lib.py](#simpleperfreportlibpy) -### app_profiler.py -`app_profiler.py` is used to record profiling data for Android applications and native executables. +## app_profiler.py + +app_profiler.py is used to record profiling data for Android applications and native executables. ```sh # Record an Android application. -$ ./app_profiler.py -p simpleperf.example.cpp +$ python app_profiler.py -p com.example.simpleperf.simpleperfexamplewithnative # Record an Android application with Java code compiled into native instructions. -$ ./app_profiler.py -p simpleperf.example.cpp --compile_java_code +$ python app_profiler.py -p com.example.simpleperf.simpleperfexamplewithnative --compile_java_code # Record the launch of an Activity of an Android application. -$ ./app_profiler.py -p simpleperf.example.cpp -a .SleepActivity +$ python app_profiler.py -p com.example.simpleperf.simpleperfexamplewithnative -a .SleepActivity # Record a native process. -$ ./app_profiler.py -np surfaceflinger +$ python app_profiler.py -np surfaceflinger # Record a native process given its pid. -$ ./app_profiler.py --pid 11324 +$ python app_profiler.py --pid 11324 # Record a command. -$ ./app_profiler.py -cmd \ - "dex2oat --dex-file=/data/local/tmp/app-debug.apk --oat-file=/data/local/tmp/a.oat" +$ python app_profiler.py -cmd \ + "dex2oat --dex-file=/data/local/tmp/app-profiling.apk --oat-file=/data/local/tmp/a.oat" # Record an Android application, and use -r to send custom options to the record command. -$ ./app_profiler.py -p simpleperf.example.cpp \ +$ python app_profiler.py -p com.example.simpleperf.simpleperfexamplewithnative \ -r "-e cpu-clock -g --duration 30" # Record both on CPU time and off CPU time. -$ ./app_profiler.py -p simpleperf.example.cpp \ +$ python app_profiler.py -p com.example.simpleperf.simpleperfexamplewithnative \ -r "-e task-clock -g -f 1000 --duration 10 --trace-offcpu" # Save profiling data in a custom file (like perf_custom.data) instead of perf.data. -$ ./app_profiler.py -p simpleperf.example.cpp -o perf_custom.data +$ python app_profiler.py -p com.example.simpleperf.simpleperfexamplewithnative -o perf_custom.data ``` ### Profile from launch of an application -Sometimes we want to profile the launch-time of an application. To support this, we added `--app` in -the record command. The `--app` option sets the package name of the Android application to profile. +Sometimes we want to profile the launch-time of an application. To support this, we added --app in +the record command. The --app option sets the package name of the Android application to profile. If the app is not already running, the record command will poll for the app process in a loop with an interval of 1ms. So to profile from launch of an application, we can first start the record -command with `--app`, then start the app. Below is an example. +command with --app, then start the app. Below is an example. ```sh -$ ./run_simpleperf_on_device.py record --app simpleperf.example.cpp \ +$ python run_simpleperf_on_device.py record + --app com.example.simpleperf.simpleperfexamplewithnative \ -g --duration 1 -o /data/local/tmp/perf.data # Start the app manually or using the `am` command. ``` -To make it convenient to use, `app_profiler.py` supports using the `-a` option to start an Activity +To make it convenient to use, app_profiler.py supports using the -a option to start an Activity after recording has started. ```sh -$ ./app_profiler.py -p simpleperf.example.cpp -a .MainActivity +$ python app_profiler.py -p com.example.simpleperf.simpleperfexamplewithnative -a .MainActivity ``` -### api_profiler.py +## api_profiler.py -`api_profiler.py` is used to control recording in application code. It does preparation work +api_profiler.py is used to control recording in application code. It does preparation work before recording, and collects profiling data files after recording. [Here](./android_application_profiling.md#control-recording-in-application-code) are the details. -### run_simpleperf_without_usb_connection.py +## run_simpleperf_without_usb_connection.py -`run_simpleperf_without_usb_connection.py` records profiling data while the USB cable isn't -connected. Maybe `api_profiler.py` is more suitable, which also don't need USB cable when recording. +run_simpleperf_without_usb_connection.py records profiling data while the USB cable isn't +connected. Maybe api_profiler.py is more suitable, which also don't need USB cable when recording. Below is an example. ```sh -$ ./run_simpleperf_without_usb_connection.py start -p simpleperf.example.cpp +$ python run_simpleperf_without_usb_connection.py start \ + -p com.example.simpleperf.simpleperfexamplewithnative # After the command finishes successfully, unplug the USB cable, run the -# SimpleperfExampleCpp app. After a few seconds, plug in the USB cable. -$ ./run_simpleperf_without_usb_connection.py stop +# SimpleperfExampleWithNative app. After a few seconds, plug in the USB cable. +$ python run_simpleperf_without_usb_connection.py stop # It may take a while to stop recording. After that, the profiling data is collected in perf.data # on host. ``` -### binary_cache_builder.py +## binary_cache_builder.py -The `binary_cache` directory is a directory holding binaries needed by a profiling data file. The +The binary_cache directory is a directory holding binaries needed by a profiling data file. The binaries are expected to be unstripped, having debug information and symbol tables. The -`binary_cache` directory is used by report scripts to read symbols of binaries. It is also used by -`report_html.py` to generate annotated source code and disassembly. +binary_cache directory is used by report scripts to read symbols of binaries. It is also used by +report_html.py to generate annotated source code and disassembly. -By default, `app_profiler.py` builds the binary_cache directory after recording. But we can also -build `binary_cache` for existing profiling data files using `binary_cache_builder.py`. It is useful +By default, app_profiler.py builds the binary_cache directory after recording. But we can also +build binary_cache for existing profiling data files using binary_cache_builder.py. It is useful when you record profiling data using `simpleperf record` directly, to do system wide profiling or record without the USB cable connected. -`binary_cache_builder.py` can either pull binaries from an Android device, or find binaries in -directories on the host (via `-lib`). +binary_cache_builder.py can either pull binaries from an Android device, or find binaries in +directories on the host (via -lib). ```sh # Generate binary_cache for perf.data, by pulling binaries from the device. -$ ./binary_cache_builder.py +$ python binary_cache_builder.py # Generate binary_cache, by pulling binaries from the device and finding binaries in -# SimpleperfExampleCpp. -$ ./binary_cache_builder.py -lib path_of_SimpleperfExampleCpp +# SimpleperfExampleWithNative. +$ python binary_cache_builder.py -lib path_of_SimpleperfExampleWithNative ``` -### run_simpleperf_on_device.py +## run_simpleperf_on_device.py -This script pushes the `simpleperf` executable on the device, and run a simpleperf command on the +This script pushes the simpleperf executable on the device, and run a simpleperf command on the device. It is more convenient than running adb commands manually. -## Viewing the profile - -Scripts in this section are for viewing the profile or converting profile data into formats used by -external UIs. For recommended UIs, see [view_the_profile.md](view_the_profile.md). - -### report.py +## report.py -report.py is a wrapper of the `report` command on the host. It accepts all options of the `report` +report.py is a wrapper of the report command on the host. It accepts all options of the report command. ```sh # Report call graph -$ ./report.py -g +$ python report.py -g # Report call graph in a GUI window implemented by Python Tk. -$ ./report.py -g --gui +$ python report.py -g --gui ``` -### report_html.py +## report_html.py -`report_html.py` generates `report.html` based on the profiling data. Then the `report.html` can show +report_html.py generates report.html based on the profiling data. Then the report.html can show the profiling result without depending on other files. So it can be shown in local browsers or passed to other machines. Depending on which command-line options are used, the content of the -`report.html` can include: chart statistics, sample table, flamegraphs, annotated source code for +report.html can include: chart statistics, sample table, flamegraphs, annotated source code for each function, annotated disassembly for each function. ```sh # Generate chart statistics, sample table and flamegraphs, based on perf.data. -$ ./report_html.py +$ python report_html.py # Add source code. -$ ./report_html.py --add_source_code --source_dirs path_of_SimpleperfExampleCpp +$ python report_html.py --add_source_code --source_dirs path_of_SimpleperfExampleWithNative # Add disassembly. -$ ./report_html.py --add_disassembly +$ python report_html.py --add_disassembly # Adding disassembly for all binaries can cost a lot of time. So we can choose to only add # disassembly for selected binaries. -$ ./report_html.py --add_disassembly --binary_filter libgame.so +$ python report_html.py --add_disassembly --binary_filter libgame.so # report_html.py accepts more than one recording data file. -$ ./report_html.py -i perf1.data perf2.data +$ python report_html.py -i perf1.data perf2.data ``` -Below is an example of generating html profiling results for SimpleperfExampleCpp. +Below is an example of generating html profiling results for SimpleperfExampleWithNative. ```sh -$ ./app_profiler.py -p simpleperf.example.cpp -$ ./report_html.py --add_source_code --source_dirs path_of_SimpleperfExampleCpp \ +$ python app_profiler.py -p com.example.simpleperf.simpleperfexamplewithnative +$ python report_html.py --add_source_code --source_dirs path_of_SimpleperfExampleWithNative \ --add_disassembly ``` -After opening the generated [`report.html`](./report_html.html) in a browser, there are several tabs: +After opening the generated [report.html](./report_html.html) in a browser, there are several tabs: The first tab is "Chart Statistics". You can click the pie chart to show the time consumed by each process, thread, library and function. @@ -172,7 +184,7 @@ process, thread, library and function. The second tab is "Sample Table". It shows the time taken by each function. By clicking one row in the table, we can jump to a new tab called "Function". -The third tab is "Flamegraph". It shows the graphs generated by [`inferno`](./inferno.md). +The third tab is "Flamegraph". It shows the graphs generated by [inferno](./inferno.md). The fourth tab is "Function". It only appears when users click a row in the "Sample Table" tab. It shows information of a function, including: @@ -184,9 +196,9 @@ It shows information of a function, including: 4. Annotated disassembly of that function. It only appears when there are binaries containing that function. -### inferno +## inferno -[`inferno`](./inferno.md) is a tool used to generate flamegraph in a html file. +[inferno](./inferno.md) is a tool used to generate flamegraph in a html file. ```sh # Generate flamegraph based on perf.data. @@ -197,17 +209,17 @@ $ ./inferno.sh -sc --record_file perf.data $ ./inferno.sh -np surfaceflinger ``` -### purgatorio +## purgatorio -[`purgatorio`](../scripts/purgatorio/README.md) is a visualization tool to show samples in time order. +[purgatorio](../scripts/purgatorio/README.md) is a visualization tool to show samples in time order. -### pprof_proto_generator.py +## pprof_proto_generator.py -It converts a profiling data file into `pprof.proto`, a format used by [pprof](https://github.com/google/pprof). +It converts a profiling data file into pprof.proto, a format used by [pprof](https://github.com/google/pprof). ```sh # Convert perf.data in the current directory to pprof.proto format. -$ ./pprof_proto_generator.py +$ python pprof_proto_generator.py # Show report in pdf format. $ pprof -pdf pprof.profile @@ -218,99 +230,21 @@ $ pprof -pdf pprof.profile $ pprof -http=:8080 pprof.profile ``` -### gecko_profile_generator.py - -Converts `perf.data` to [Gecko Profile -Format](https://github.com/firefox-devtools/profiler/blob/main/docs-developer/gecko-profile-format.md), -the format read by https://profiler.firefox.com/. - -Firefox Profiler is a powerful general-purpose profiler UI which runs locally in -any browser (not just Firefox), with: +## report_sample.py -- Per-thread tracks -- Flamegraphs -- Search, focus for specific stacks -- A time series view for seeing your samples in timestamp order -- Filtering by thread and duration - -Usage: - -``` -# Record a profile of your application -$ ./app_profiler.py -p simpleperf.example.cpp - -# Convert and gzip. -$ ./gecko_profile_generator.py -i perf.data | gzip > gecko-profile.json.gz -``` - -Then open `gecko-profile.json.gz` in https://profiler.firefox.com/. - -### report_sample.py - -`report_sample.py` converts a profiling data file into the `perf script` text format output by -`linux-perf-tool`. - -This format can be imported into: - -- [FlameGraph](https://github.com/brendangregg/FlameGraph) -- [Flamescope](https://github.com/Netflix/flamescope) -- [Firefox - Profiler](https://github.com/firefox-devtools/profiler/blob/main/docs-user/guide-perf-profiling.md), - but prefer using `gecko_profile_generator.py`. -- [Speedscope](https://github.com/jlfwong/speedscope/wiki/Importing-from-perf-(linux)) +It converts a profiling data file into a format used by [FlameGraph](https://github.com/brendangregg/FlameGraph). ```sh -# Record a profile to perf.data -$ ./app_profiler.py <args> - # Convert perf.data in the current directory to a format used by FlameGraph. -$ ./report_sample.py --symfs binary_cache >out.perf - +$ python report_sample.py --symfs binary_cache >out.perf $ git clone https://github.com/brendangregg/FlameGraph.git $ FlameGraph/stackcollapse-perf.pl out.perf >out.folded $ FlameGraph/flamegraph.pl out.folded >a.svg ``` -### stackcollapse.py - -`stackcollapse.py` converts a profiling data file (`perf.data`) to [Brendan -Gregg's "Folded Stacks" -format](https://queue.acm.org/detail.cfm?id=2927301#:~:text=The%20folded%20stack%2Dtrace%20format,trace%2C%20followed%20by%20a%20semicolon). - -Folded Stacks are lines of semicolon-delimited stack frames, root to leaf, -followed by a count of events sampled in that stack, e.g.: - -``` -BusyThread;__start_thread;__pthread_start(void*);java.lang.Thread.run 17889729 -``` - -All similar stacks are aggregated and sample timestamps are unused. - -Folded Stacks format is readable by: - -- The [FlameGraph](https://github.com/brendangregg/FlameGraph) toolkit -- [Inferno](https://github.com/jonhoo/inferno) (Rust port of FlameGraph) -- [Speedscope](https://speedscope.app/) - -Example: - -```sh -# Record a profile to perf.data -$ ./app_profiler.py <args> - -# Convert to Folded Stacks format -$ ./stackcollapse.py --kernel --jit | gzip > profile.folded.gz - -# Visualise with FlameGraph with Java Stacks and nanosecond times -$ git clone https://github.com/brendangregg/FlameGraph.git -$ gunzip -c profile.folded.gz \ - | FlameGraph/flamegraph.pl --color=java --countname=ns \ - > profile.svg -``` - ## simpleperf_report_lib.py -`simpleperf_report_lib.py` is a Python library used to parse profiling data files generated by the +simpleperf_report_lib.py is a Python library used to parse profiling data files generated by the record command. Internally, it uses libsimpleperf_report.so to do the work. Generally, for each profiling data file, we create an instance of ReportLib, pass it the file path (via SetRecordFile). Then we can read all samples through GetNextSample(). For each sample, we can read its event info @@ -318,5 +252,5 @@ Then we can read all samples through GetNextSample(). For each sample, we can re (via GetCallChainOfCurrentSample). We can also get some global information, like record options (via GetRecordCmd), the arch of the device (via GetArch) and meta strings (via MetaInfo). -Examples of using `simpleperf_report_lib.py` are in `report_sample.py`, `report_html.py`, -`pprof_proto_generator.py` and `inferno/inferno.py`. +Examples of using simpleperf_report_lib.py are in report_sample.py, report_html.py, +pprof_proto_generator.py and inferno/inferno.py. |