Developing on Windows

Like Linux and macOS, we have worked to enable builds to work “out of the box” with CMake for a reasonably large subset of the project.

System Setup

Microsoft provides the free Visual Studio Community edition. When doing development in the shell, you must initialize the development environment each time you open the shell.

For Visual Studio 2017, execute the following batch script:

"C:\Program Files (x86)\Microsoft Visual Studio\2017\Community\Common7\Tools\VsDevCmd.bat" -arch=amd64

For Visual Studio 2019, the script is:

"C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\Common7\Tools\VsDevCmd.bat" -arch=amd64

One can configure a console emulator like cmder to automatically launch this when starting a new development console.

Using conda-forge for build dependencies

Miniconda is a minimal Python distribution including the conda package manager. Some memers of the Apache Arrow community participate in the maintenance of conda-forge, a community-maintained cross-platform package repository for conda.

To use conda-forge for your C++ build dependencies on Windows, first download and install a 64-bit distribution from the Miniconda homepage

To configure conda to use the conda-forge channel by default, launch a command prompt (cmd.exe), run the initialization command shown above (vcvarsall.bat or VsDevCmd.bat), then run the command:

conda config --add channels conda-forge

Now, you can bootstrap a build environment (call from the root directory of the Arrow codebase):

conda create -y -n arrow-dev --file=ci\conda_env_cpp.txt

Then “activate” this conda environment with:

activate arrow-dev

If the environment has been activated, the Arrow build system will automatically see the %CONDA_PREFIX% environment variable and use that for resolving the build dependencies. This is equivalent to setting

-DARROW_DEPENDENCY_SOURCE=SYSTEM ^
-DARROW_PACKAGE_PREFIX=%CONDA_PREFIX%\Library

To use the Visual Studio IDE with this conda environment activated, launch it by running the command devenv from the same command prompt.

Note that dependencies installed as conda packages are built in release mode and cannot link with debug builds. If you intend to use -DCMAKE_BUILD_TYPE=debug then you must build the packages from source. -DCMAKE_BUILD_TYPE=relwithdebinfo is also available, which produces a build that can both be linked with release libraries and be debugged.

Note

If you run into any problems using conda packages for dependencies, a very common problem is mixing packages from the defaults channel with those from conda-forge. You can examine the installed packages in your environment (and their origin) with conda list

Using vcpkg for build dependencies

vcpkg is an open source package manager from Microsoft. It hosts community-contributed ports of C and C++ packages and their dependencies. Arrow includes a manifest file cpp/vcpkg.json that specifies which vcpkg packages are required to build the C++ library.

To use vcpkg for C++ build dependencies on Windows, first install and integrate vcpkg. Then change working directory in cmd.exe to the root directory of Arrow and run the command:

vcpkg install ^
  --triplet x64-windows ^
  --x-manifest-root cpp  ^
  --feature-flags=versions ^
  --clean-after-build

On Windows, vcpkg builds dynamic link libraries by default. Use the triplet x64-windows-static to build static libraries. vcpkg downloads source packages and compiles them locally, so installing dependencies with vcpkg is more time-consuming than with conda.

Then in your cmake command, to use dependencies installed by vcpkg, set:

-DARROW_DEPENDENCY_SOURCE=VCPKG

You can optionally set other variables to override the default CMake configurations for vcpkg, including:

  • -DCMAKE_TOOLCHAIN_FILE: by default, the CMake scripts automatically find the location of the vcpkg CMake toolchain file vcpkg.cmake; use this to instead specify its location

  • -DVCPKG_TARGET_TRIPLET: by default, the CMake scripts attempt to infer the vcpkg triplet; use this to instead specify the triplet

  • -DARROW_DEPENDENCY_USE_SHARED: default is ON; set to OFF for static libraries

  • -DVCPKG_MANIFEST_MODE: default is ON; set to OFF to ignore the vcpkg.json manifest file and only look for vcpkg packages that are already installed under the directory where vcpkg is installed

Building using Visual Studio (MSVC) Solution Files

Change working directory in cmd.exe to the root directory of Arrow and do an out of source build by generating a MSVC solution:

cd cpp
mkdir build
cd build
cmake .. -G "Visual Studio 15 2017" -A x64 ^
      -DARROW_BUILD_TESTS=ON
cmake --build . --config Release

For newer versions of Visual Studio, specify the generator Visual Studio 16 2019 or see cmake --help for available generators.

Building with Ninja and clcache

The Ninja build system offers better build parallelization, and the optional clcache compiler cache keeps track of past compilations to avoid running them over and over again (in a way similar to the Unix-specific ccache).

Newer versions of Visual Studio include Ninja. To see if your Visual Studio includes Ninja, run the initialization command shown above (vcvarsall.bat or VsDevCmd.bat), then run ninja --version.

If Ninja is not included in your version of Visual Studio, and you are using conda, activate your conda environment and install Ninja and clcache:

activate arrow-dev
conda install -c conda-forge ninja
pip install git+https://github.com/frerich/clcache.git

If you are not using conda, install Ninja from another source and optionally install clcache from another source .

After installation is complete, change working directory in cmd.exe to the root directory of Arrow and do an out of source build by generating Ninja files:

cd cpp
mkdir build
cd build
cmake -G "Ninja" ^
      -DCMAKE_C_COMPILER=clcache ^
      -DCMAKE_CXX_COMPILER=clcache ^
      -DARROW_BUILD_TESTS=ON ^
      -DGTest_SOURCE=BUNDLED ..
cmake --build . --config Release

Setting CMAKE_C_COMPILER and CMAKE_CXX_COMPILER in the command line of cmake is the preferred method of using clcache. Alternatively, you can set CC and CXX environment variables before calling cmake:

...
set CC=clcache
set CXX=clcache
cmake -G "Ninja" ^
...

Building with NMake

Change working directory in cmd.exe to the root directory of Arrow and do an out of source build using nmake:

cd cpp
mkdir build
cd build
cmake -G "NMake Makefiles" ..
nmake

Building on MSYS2

You can build on MSYS2 terminal, cmd.exe or PowerShell terminal.

On MSYS2 terminal:

cd cpp
mkdir build
cd build
cmake -G "MSYS Makefiles" ..
make

On cmd.exe or PowerShell terminal, you can use the following batch file:

setlocal

REM For 64bit
set MINGW_PACKAGE_PREFIX=mingw-w64-x86_64
set MINGW_PREFIX=c:\msys64\mingw64
set MSYSTEM=MINGW64

set PATH=%MINGW_PREFIX%\bin;c:\msys64\usr\bin;%PATH%

rmdir /S /Q cpp\build
mkdir cpp\build
pushd cpp\build
cmake -G "MSYS Makefiles" .. || exit /B
make || exit /B
popd

Debug builds

To build a Debug version of Arrow, you should have pre-installed a Debug version of Boost. It’s recommended to configure cmake with the following variables for Debug build:

  • -DARROW_BOOST_USE_SHARED=OFF: enables static linking with boost debug libs and simplifies run-time loading of 3rd parties

  • -DBOOST_ROOT: sets the root directory of boost libs. (Optional)

  • -DBOOST_LIBRARYDIR: sets the directory with boost lib files. (Optional)

The command line to build Arrow in Debug mode will look something like this:

cd cpp
mkdir build
cd build
cmake .. -G "Visual Studio 15 2017" -A x64 ^
      -DARROW_BOOST_USE_SHARED=OFF ^
      -DCMAKE_BUILD_TYPE=Debug ^
      -DBOOST_ROOT=C:/local/boost_1_63_0  ^
      -DBOOST_LIBRARYDIR=C:/local/boost_1_63_0/lib64-msvc-14.0
cmake --build . --config Debug

Windows dependency resolution issues

Because Windows uses .lib files for both static and dynamic linking of dependencies, the static library sometimes may be named something different like %PACKAGE%_static.lib to distinguish itself. If you are statically linking some dependencies, we provide some options

  • -DBROTLI_MSVC_STATIC_LIB_SUFFIX=%BROTLI_SUFFIX%

  • -DSNAPPY_MSVC_STATIC_LIB_SUFFIX=%SNAPPY_SUFFIX%

  • -LZ4_MSVC_STATIC_LIB_SUFFIX=%LZ4_SUFFIX%

  • -ZSTD_MSVC_STATIC_LIB_SUFFIX=%ZSTD_SUFFIX%

To get the latest build instructions, you can reference ci/appveyor-built.bat, which is used by automated Appveyor builds.

Statically linking to Arrow on Windows

The Arrow headers on Windows static library builds (enabled by the CMake option ARROW_BUILD_STATIC) use the preprocessor macro ARROW_STATIC to suppress dllimport/dllexport marking of symbols. Projects that statically link against Arrow on Windows additionally need this definition. The Unix builds do not use the macro.

Replicating Appveyor Builds

For people more familiar with linux development but need to replicate a failing appveyor build, here are some rough notes from replicating the Static_Crt_Build (make unittest will probably still fail but many unit tests can be made with there individual make targets).

  1. Microsoft offers trial VMs for Windows with Microsoft Visual Studio. Download and install a version.

  2. Run the VM and install Git, CMake, and Miniconda or Anaconda (these instructions assume Anaconda). Also install the “Build Tools for Visual Studio”. Make sure to select the C++ toolchain in the installer wizard, and reboot after installation.

  3. Download pre-built Boost debug binaries and install it.

    Run this from an Anaconda/Miniconda command prompt (not PowerShell prompt), and make sure to run “vcvarsall.bat x64” first. The location of vcvarsall.bat will depend, it may be under a different path than commonly indicated, e.g. “C:\Program Files (x86)\Microsoft Visual Studio\2019\BuildTools\VC\Auxiliary\Build\vcvarsall.bat” with the 2019 build tools.

cd $EXTRACT_BOOST_DIRECTORY
.\bootstrap.bat
@rem This is for static libraries needed for static_crt_build in appveyor
.\b2 link=static --with-filesystem --with-regex --with-system install
@rem this should put libraries and headers in c:\Boost

  1. Activate anaconda/miniconda:

@rem this might differ for miniconda
C:\Users\User\Anaconda3\Scripts\activate

  1. Clone and change directories to the arrow source code (you might need to install git).

  2. Setup environment variables:

@rem Change the build type based on which appveyor job you want.
SET JOB=Static_Crt_Build
SET GENERATOR=Ninja
SET APPVEYOR_BUILD_WORKER_IMAGE=Visual Studio 2017
SET USE_CLCACHE=false
SET ARROW_BUILD_GANDIVA=OFF
SET ARROW_LLVM_VERSION=8.0.*
SET PYTHON=3.6
SET ARCH=64
SET PATH=C:\Users\User\Anaconda3;C:\Users\User\Anaconda3\Scripts;C:\Users\User\Anaconda3\Library\bin;%PATH%
SET BOOST_LIBRARYDIR=C:\Boost\lib
SET BOOST_ROOT=C:\Boost

  1. Run appveyor scripts:

conda install -c conda-forge --file .\ci\conda_env_cpp.txt
.\ci\appveyor-cpp-setup.bat
@rem this might fail but at this point most unit tests should be buildable by there individual targets
@rem see next line for example.
.\ci\appveyor-cpp-build.bat
@rem you can also just invoke cmake directly with the desired options
cmake --build . --config Release --target arrow-compute-hash-test

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