jobdiogenes/fastr repository overview

⁠FastR Docker

⁠Tags available

latest which is the default, give the latest stable Community Version of Graal/FastR, using debian as base dev give the development version of Community Version of Graal/FastR, using debian as base colab an effort to bring fastr to run under Google Colaboratory.

⁠Why use docker

• You could create a well defined environment to your research task. Where the tools and packages are in their respective versions that are need to run. No more need to uninstall and install tools and packages in your computer. All this tools will be containerized under docker and isolated of your system.

• Containers could be shared, moved and accessed remotely.

• Publish a paper, working in a group ? just publish your docker to others use.

• Need more power? For example, you develop a research that is too slow to your computer, just move you docker image to some Cloud Provider, or other Supercomputer/Cluster that you have access. You will don't need to prepare, or ask to IT prepare the environment to run.

⁠Why FastR is so fast

⁠When use FastR ?

• Use FastR to get very high performance for R scripts
• When using scripts that take time to run

⁠Caveats

• FastR its not viable for short run scripts, since loading are more slow than standard Gnu-R and will not benefited from optimizations
• FastR are under early development, so you need takes more care about installing R packages.

⁠How to use this FastR Docker

• First you need to have docker engine installed in your computer. Under Debian, Ubuntu, LinuxMint or other Debian base system, is already on base repositories. But, you could use Docker.com repositories to get the newest version.
• If you want really deploy FastR for your needs or research group in your own computer or server. Its highly recommended to configure where docker engine will store contents. Do this changing "graph" parameter in daemon.json that in ubuntu/debian is at /etc/docker/daemon, to a directory mapped to outside of system partition.

⁠Using this docker image

docker pull jobdiogenes/fastr

Running until exit

--rm option mean that after exit, the container will be removed.

--name defined a name to your newly created container

-v /my-folder-path:/inside-container-path map a local folder, remote, or docker volume to a container path.

docker run --rm -it --name mytest -v /path-to/my-local/data-and-scripts:/mnt Rscript /mnt/mytest.R

Loading a FastR Docker that will stay running in background and restart if stopped

-d mean that docker will load and stay running in background until you call to stop or remove. $(pwd) mean (Linux,Unix,OSX,Nix, only) that will replace to the path od current folder where you are calling.

docker run -d --restart always --name myfastr -v $(pwd)/data:/mnt jobdiogenes/fastr

Loading, Prepare, Save and Reuse

# Loading
docker run --rm -it --name mythesis jobdiogenes/fastr:latest

## Prepare now, the FastR running container to your needs. 
# Run R and then install your packages there. 
R
# Or call a script that is in the folder that you map to do this.
Rscript /mnt/install-packages.R

## You could even copy data to the container.
# Remember this could make your docker image bigger. But, its great
# for easy reproducibility.
mkdir /data
cp  /mnt/data/* /data

While running, you container, in another terminal/console session do it:

docker export mythesis -o mythesis.tar

Now you could share your docker image file. Reuse it by doing it:

docker load -i mythesis.tar

⁠Any questions, want help ?