# heaptrack

**Repository Path**: jjzhang166/heaptrack

## Basic Information

- **Project Name**: heaptrack
- **Description**: Heaptrack 是一个 Linux 的堆内存分析器
- **Primary Language**: C/C++
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: https://www.oschina.net/p/heaptrack
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 2
- **Created**: 2022-01-03
- **Last Updated**: 2022-01-03

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# heaptrack - a heap memory profiler for Linux

![heaptrack_gui summary page](screenshots/gui_summary.png?raw=true "heaptrack_gui summary page")

Heaptrack traces all memory allocations and annotates these events with stack traces.
Dedicated analysis tools then allow you to interpret the heap memory profile to:

- find hotspots that need to be optimized to reduce the **memory footprint** of your application
- find **memory leaks**, i.e. locations that allocate memory which is never deallocated
- find **allocation hotspots**, i.e. code locations that trigger a lot of memory allocation calls
- find **temporary allocations**, which are allocations that are directly followed by their deallocation

## Using heaptrack

The recommended way is to launch your application and start tracing from the beginning:

    heaptrack <your application and its parameters>

    heaptrack output will be written to "/tmp/heaptrack.APP.PID.gz"
    starting application, this might take some time...

    ...

    heaptrack stats:
        allocations:            65
        leaked allocations:     60
        temporary allocations:  1

    Heaptrack finished! Now run the following to investigate the data:

        heaptrack_gui "/tmp/heaptrack.APP.PID.gz"

Alternatively, you can attach to an already running process:

    heaptrack --pid $(pidof <your application>)

    heaptrack output will be written to "/tmp/heaptrack.APP.PID.gz"
    injecting heaptrack into application via GDB, this might take some time...
    injection finished

    ...

    Heaptrack finished! Now run the following to investigate the data:

        heaptrack_gui "/tmp/heaptrack.APP.PID.gz"

## Building heaptrack

Heaptrack is split into two parts: The data collector, i.e. `heaptrack` itself, and the
analyzer GUI called `heaptrack_gui`. The following summarizes the dependencies for these
two parts as they can be build independently. You will find corresponding development
packages on all major distributions for these dependencies.

On an embedded device or older Linux distribution, you will only want to build `heaptrack`.
The data can then be analyzed on a different machine with a more modern Linux distribution
that has access to the required GUI dependencies.

If you need help with building, deploying or using heaptrack, you can contact KDAB for
commercial support: https://www.kdab.com/software-services/workshops/profiling-workshops/

### Shared dependencies

Both parts require the following tools and libraries:

- cmake 2.8.9 or higher
- a C\+\+11 enabled compiler like g\+\+ or clang\+\+
- zlib
- optionally: zstd for faster (de)compression
- libdl
- pthread
- libc

### `heaptrack` dependencies

The heaptrack data collector and the simplistic `heaptrack_print` analyzer depend on the
following libraries:

- boost 1.41 or higher: iostreams, program_options
- libunwind

For runtime-attaching, you will need `gdb` installed.

### `heaptrack_gui` dependencies

The graphical user interface to interpret and analyze the data collected by heaptrack
depends on Qt 5 and some KDE libraries:

- extra-cmake-modules
- Qt 5.2 or higher: Core, Widgets
- KDE Frameworks 5: CoreAddons, I18n, ItemModels, ThreadWeaver, ConfigWidgets, KIO, IconThemes

When any of these dependencies is missing, `heaptrack_gui` will not be build.
Optionally, install the following dependencies to get additional features in
the GUI:

- KDiagram: KChart (for chart visualizations)

### Compiling

Run the following commands to compile heaptrack. Do pay attention to the output
of the CMake command, as it will tell you about missing dependencies!

    cd heaptrack # i.e. the source folder
    mkdir build
    cd build
    cmake -DCMAKE_BUILD_TYPE=Release .. # look for messages about missing dependencies!
    make -j$(nproc)

#### Compile `heaptrack_gui` on macOS using homebrew

`heaptrack_print` and `heaptrack_gui` can be built on platforms other than Linux, using the dependencies mentioned above.
On macOS the dependencies can be installed easily using [homebrew](http://brew.sh) and the [KDE homebrew tap](https://github.com/KDE-mac/homebrew-kde).

    # prepare tap
    brew tap kde-mac/kde https://invent.kde.org/packaging/homebrew-kde.git
    "$(brew --repo kde-mac/kde)/tools/do-caveats.sh"
    
    # install dependencies
    brew install kde-mac/kde/kf5-kcoreaddons kde-mac/kde/kf5-kitemmodels kde-mac/kde/kf5-kconfigwidgets \
                 kde-mac/kde/kf5-kio kde-mac/kde/kdiagram \
                 kde-extra-cmake-modules kde-ki18n kde-threadweaver \
                 boost zstd gettext
    
    # run manual steps as printed by brew
    ln -sfv "$(brew --prefix)/share/kf5" "$HOME/Library/Application Support"
    ln -sfv "$(brew --prefix)/share/knotifications5" "$HOME/Library/Application Support"
    ln -sfv "$(brew --prefix)/share/kservices5" "$HOME/Library/Application Support"
    ln -sfv "$(brew --prefix)/share/kservicetypes5" "$HOME/Library/Application Support"

To compile make sure to use Qt from homebrew and to have gettext in the path:

    cd heaptrack # i.e. the source folder
    mkdir build
    cd build
    CMAKE_PREFIX_PATH=/usr/local/opt/qt PATH=$PATH:/usr/local/opt/gettext/bin cmake ..
    cmake -DCMAKE_BUILD_TYPE=Release .. # look for messages about missing dependencies!
    make heaptrack_gui heaptrack_print

## Interpreting the heap profile

Heaptrack generates data files that are impossible to analyze for a human. Instead, you need
to use either `heaptrack_print` or `heaptrack_gui` to interpret the results.

### heaptrack_gui

![heaptrack_gui flamegraph page](screenshots/gui_flamegraph.png?raw=true "heaptrack_gui flamegraph page")

![heaptrack_gui allocations chart page](screenshots/gui_allocations_chart.png?raw=true "heaptrack_gui allocations chart page")

The highly recommended way to analyze a heap profile is by using the `heaptrack_gui` tool.
It depends on Qt 5 and KF 5 to graphically visualize the recorded data. It features:

- a summary page of the data
- bottom-up and top-down tree views of the code locations that allocated memory with
  their aggregated cost and stack traces
- flame graph visualization
- graphs of allocation costs over time

### heaptrack_print

The `heaptrack_print` tool is a command line application with minimal dependencies. It takes
the heap profile, analyzes it, and prints the results in ASCII format to the command line.

In its most simple form, you can use it like this:

    heaptrack_print heaptrack.APP.PID.gz | less

By default, the report will contain three sections:

    MOST CALLS TO ALLOCATION FUNCTIONS
    PEAK MEMORY CONSUMERS
    MOST TEMPORARY ALLOCATIONS

Each section then lists the top ten hotspots, i.e. code locations that triggered e.g.
the most memory allocations.

Have a look at `heaptrack_print --help` for changing the output format and other options.

Note that you can use this tool to convert a heaptrack data file to the Massif data format.
You can generate a collapsed stack report for consumption by `flamegraph.pl`.

## Comparison to Valgrind's massif

The idea to build heaptrack was born out of the pain in working with Valgrind's massif.
Valgrind comes with a huge overhead in both memory and time, which sometimes prevent you
from running it on larger real-world applications. Most of what Valgrind does is not
needed for a simple heap profiler.

### Advantages of heaptrack over massif

- *speed and memory overhead*

  Multi-threaded applications are not serialized when you trace them with heaptrack and
  even for single-threaded applications the overhead in both time and memory is significantly
  lower. Most notably, you only pay a price when you allocate memory -- time-intensive CPU
  calculations are not slowed down at all, contrary to what happens in Valgrind.

- *more data*

  Valgrind's massif aggregates data before writing the report. This step loses a lot of
  useful information. Most notably, you are not longer able to find out how often memory
  was allocated, or where temporary allocations are triggered. Heaptrack does not aggregate the
  data until you interpret it, which allows for more useful insights into your allocation patterns.

### Advantages of massif over heaptrack

- *ability to profile page allocations as heap*

  This allows you to heap-profile applications that use pool allocators that circumvent
  malloc & friends. Heaptrack can in principle also profile such applications, but it
  requires code changes to annotate the memory pool implementation.

- *ability to profile stack allocations*

  This is inherently impossible to implement efficiently in heaptrack as far as I know.

## Contributing to heaptrack

As a FOSS project, we welcome contributions of any form. You can help improve the project by:

- submitting bug reports at https://bugs.kde.org/enter_bug.cgi?product=Heaptrack
- contributing patches via https://invent.kde.org/sdk/heaptrack
- translating the GUI with the help of https://l10n.kde.org/
- writing documentation on https://userbase.kde.org/Heaptrack

When submitting bug reports, you can anonymize your data with the `tools/anonymize` script:

    tools/anonymize heaptrack.APP.PID.gz heaptrack.bug_report_data.gz

## Known bugs and limitations

### Issues with old gold linker

Libunwind may produce bogus backtraces when unwinding from code linked with old versions of the gold linker.
In such cases, recording with heaptrack seems to work and produces data files. But parsing these data files
with heaptrack_gui will often lead to out-of-memory crashes. Looking at the data with heaptrack_print, one
will see garbage backtraces that are completely broken.

If you encounter such issues, try to relink your application and also libunwind with `ld.bfd` instead of `ld.gold`.
You can see if you are affected by running the libunwind unit tests via `make check`. But do note that you
need to relink your application too, not only libunwind.