run r script using docker kaggle image

I am trying to reproduce results of an R script on my local Windows OS (reproduce the results which it gave on kaggle server). For this someone suggested to use docker images to run r script on my local.

I have installed docker and finished the steps to set it up by following instructions given here https://docs.docker.com/windows/step_one/

  • Docker container can not run as a daemon
  • Sending logs from docker container to FluentD
  • x509: certificate signed by unknown authority when building docker image
  • cannot remove docker image, error response from daemon
  • Dockerfile supervisord cannot find path
  • Dockerfile - Angular2
  • After installing, I am struggling with on how to create the kaggle R image and run an R script on my local using local resources/data. Can someone please help me with these?

  • how to sshfs/sftp on boot2docker or docker-toolbox
  • android.test did not get installed. Reason: 'Aborted '
  • Unable to push Docker (1.10.2) image to Artifactory through reverse proxy Nginx , error 'Unknown Blob'
  • Docker Running the Java -JAR file to create Cassandra KeySpaces. But its not creating
  • Docker container stuck after enter in container
  • Docker pull ubuntu no reply
  • One Solution collect form web for “run r script using docker kaggle image”

    You can load already builded image rstat from dockerhub:

    docker run kaggle/rstats
    

    For using your local data you should create volume:

    docker run -v /you/local/data/path:path/in/docker/container kaggle/rstat
    

    Volume binds your local storage with container storage. Also you can create additional volume for output data.

    The last line in rstate dockerfile is

    CMD ["R"]
    

    It means that R console will be called after container start. Just past your script in terminal (script should use data from mounted volume in container and write result to mounted output volume). After script execution you can stop container. Your output data will be saved on your local machine.

    P.S. image is giant (6Gb). I never seen before such large docker image.

    Docker will be the best open platform for developers and sysadmins to build, ship, and run distributed applications.