Packaging and Testing with Crossbow

The content of arrow/dev/tasks directory aims for automating the process of Arrow packaging and integration testing.

Packages:

• C++ and Python conda-forge packages for Linux, Mac and Windows

• Python Wheels for Linux, Mac and Windows

• C++ and GLib Linux packages for multiple distributions

• Java for Gandiva

Integration tests:

• Various docker tests

• Pandas

• Dask

• Turbodbc

• HDFS

• Spark

Architecture

Executors

Individual jobs are executed on public CI services, currently:

• Linux: TravisCI, CircleCI, Azure Pipelines

• Mac: TravisCI, Azure Pipelines

• Windows: AppVeyor, Azure Pipelines

Queue

Because of the nature of how the CI services work, the scheduling of jobs happens through an additional git repository, which acts like a job queue for the tasks. Anyone can host a queue repository which is usually called as crossbow.

A job is a git commit on a particular git branch, containing only the required configuration file to run the requested build (like .travis.yml, appveyor.yml or azure-pipelines.yml).

Scheduler

Crossbow.py handles version generation, task rendering and submission. The tasks are defined in tasks.yml.

Install

The following guide depends on GitHub, but theoretically any git server can be used.

1. Create the queue repository

2. Enable TravisCI, Appveyor, Azure Pipelines_ and CircleCI integrations on for the newly created queue repository.

   • turn off Travis’ auto cancellation feature on branches

3. Clone the newly created repository next to the arrow repository:

   By default the scripts looks for crossbow next to arrow repository, but this can configured through command line arguments.

   git clone https://github.com/<user>/crossbow crossbow
   

   Important note: Crossbow only supports GitHub token based authentication. Although it overwrites the repository urls provided with ssh protocol, it’s advisable to use the HTTPS repository URLs.

4. Create a Personal Access Token with repo permissions (other permissions are not needed)

5. Locally export the token as an environment variable:

   export CROSSBOW_GITHUB_TOKEN=<token>
   

   or pass as an argument to the CLI script --github-token

6. Export the previously created GitHub token on both CI services:

   Use CROSSBOW_GITHUB_TOKEN encrypted environment variable. You can set them at the following URLs, where ghuser is the GitHub username and ghrepo is the GitHub repository name (typically crossbow):

   • TravisCI: https://travis-ci.org/<ghuser>/<ghrepo>/settings

   • Appveyor: https://ci.appveyor.com/project/<ghuser>/<ghrepo>/settings/environment

   • CircleCI: https://circleci.com/gh/<ghuser>/<ghrepo>/edit#env-vars

   On Appveyor check the skip branches without appveyor.yml checkbox on the web UI under crossbow repository’s settings.

7. Install Python (minimum supported version is 3.6):

   Miniconda is preferred, see installation instructions: https://conda.io/docs/user-guide/install/index.html

8. Install the python dependencies for the script:

   conda install -c conda-forge -y --file arrow/ci/conda_env_crossbow.txt
   

   # pygit2 requires libgit2: http://www.pygit2.org/install.html
   pip install \
       jinja2 \
       pygit2 \
       click \
       ruamel.yaml \
       setuptools_scm \
       github3.py \
       toolz \
       jira
   

9. Try running it:

   $ python crossbow.py --help
   

Usage

The script does the following:

1. Detects the current repository, thus supports forks. The following snippet will build kszucs’s fork instead of the upstream apache/arrow repository.

   $ git clone https://github.com/kszucs/arrow
   $ git clone https://github.com/kszucs/crossbow
   
   $ cd arrow/dev/tasks
   $ python crossbow.py submit --help  # show the available options
   $ python crossbow.py submit conda-win conda-linux conda-osx
   

2. Gets the HEAD commit of the currently checked out branch and generates the version number based on setuptools_scm. So to build a particular branch check out before running the script:

   git checkout ARROW-<ticket number>
   python dev/tasks/crossbow.py submit --dry-run conda-linux conda-osx
   

   Note that the arrow branch must be pushed beforehand, because the script will clone the selected branch.

3. Reads and renders the required build configurations with the parameters substituted.

4. Create a branch per task, prefixed with the job id. For example to build conda recipes on linux it will create a new branch: crossbow@build-<id>-conda-linux.

5. Pushes the modified branches to GitHub which triggers the builds. For authentication it uses GitHub OAuth tokens described in the install section.

Query the build status

Build id (which has a corresponding branch in the queue repository) is returned by the submit command.

python crossbow.py status <build id / branch name>

Download the build artifacts

python crossbow.py artifacts <build id / branch name>

Examples

Submit command accepts a list of task names and/or a list of task-group names to select which tasks to build.

Run multiple builds:

$ python crossbow.py submit debian-stretch conda-linux-gcc-py37
Repository: https://github.com/kszucs/arrow@tasks
Commit SHA: 810a718836bb3a8cefc053055600bdcc440e6702
Version: 0.9.1.dev48+g810a7188.d20180414
Pushed branches:
 - debian-stretch
 - conda-linux-gcc-py37

Just render without applying or committing the changes:

$ python crossbow.py submit --dry-run task_name

Run only conda package builds and a Linux one:

$ python crossbow.py submit --group conda centos-7

Run wheel builds:

$ python crossbow.py submit --group wheel

There are multiple task groups in the tasks.yml like docker, integration and cpp-python for running docker based tests.

python crossbow.py submit supports multiple options and arguments, for more see its help page:

$ python crossbow.py submit --help