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dockR

Docker images for R based on the official Ubuntu minimal build. The
images have R set as their default entrypoint. Hence, they behave like
R binaries.

Some properties

  • All images are available as automated builds from Docker Hub. You can
    just pull them with docker pull brauner/r-patched
    and docker pull brauner/r-devel.
  • The generic R images which reside in the r-patched and r-devel
    folders are compiled without setting the march flag. This will make
    them run on any system. To see how to adapt the image to a specific
    architecture by setting the march flag take a look at the
    Dockerfiles which reside in the folders which have ivy
    appended to them. There you can also see how to enable 3D support and
    various other tweaks.
  • Set up user so that the container does not need to run as root.
  • Set up /home for user and a default repository in .Rprofile.
  • Install all recommended R dependencies, pull R-patched or R-devel
    from SVN and compile R-patched or R-devel from source.
  • The R binaries reside in /usr/local/bin/R.

Workflow & R Library and Package Management

If you mainly run R as an ephemeral interactive container and install
new packages you will need to commit the newly created layer to your image
before you quit in order to have the packages you install available via
library() when you start the container again. To circumvent this I
suggest sharing volumes between your R containers in the following
manner:

  • Create an extremely tiny container from the busybox image exposing two
    folders R and R-dev (for devtools afficionados) with the right
    permissions which you share via the --volumes-from=DATACONTAINERNAME
    flag among you R containers. You will find the Dockerfile for this
    in the folder rlib and the image on Docker Hub. You can pull it
    with docker pull brauner/rlib.
  • Run docker run --name=RDATA DATACONTAINERNAME true
  • Run docker run --volumes-from = RDATA RCONTAINERNAME

Now you can install packages into RDATA without having to commit the
container as data containers are handled differently by Docker. If you
pull a new R image you can just keep running it with your libraries
still intact. Should a new R version come out that requires upgrading
all libraries you can just remove your RDATA container which will also
remove all installed packages and start a new one.

  • If you still want to install a package ephemerally which gets deleted
    when your R container exits. You can use devtools dev_mode()
    function to specify a new library path: library(devtools); dev_mode(, path = "~/your/path/to/new/library/here") or edit .libPaths()
    directly.

Graphical Output from Docker Containers

There is a nice and semi-easy way of getting graphical output from a
Docker container without having to run an sshd daemon inside of the
container. Docker can provide bare metal performance when running a single
process which in this case is supposed to be R. Running an sshd daemon
will, marginal as it may be, introduce additional overhead. This is not
made better by running the sshd daemon as a child process of the
supervisor daemon. Both can be dispensed with when one makes good use of
bind mounts. After building the image from which the container is supposed
to be run we start an interactive container and bind mount the
/tmp/.X11-unix folder into it. I will state the complete command and
explain in detail what it does:

docker run -i -t --rm \
# -i sets up an interactive session; -t allocates a pseudo tty; --rm makes
# this container ephemeral
-e DISPLAY=$DISPLAY \
# sets the host display to the local machines display (which will usually
# be :0)
-u chbr \
# -u specify the process should be run by a user (here "chbr") and not by
# root. This step is important (v.i.)!
-v /tmp/.X11-unix:/tmp/.X11-unix \
# - v bind mounts the `X11` socket `/tmp/.X11-unix` into `/tmp/.X11-unix`
# in the container.
--name="rdev" ubuntu-r1 R
# --name="" specify the name of the container (here "rdev"); the image you
# want to run the container from (here "ubuntu-r"); the process you want
# to run in the container (here "R"). Note that the process for this image
(here "R") can be left unspecified as the program is the default
entrypoint of the image.

After issuing this command you should be looking at the beautiful R
start output. If you were to try demo(graphics) to see if graphical
output is already working you would note that it is not. That is because
of the Xsecurity extension preventing you from accessing the socket. You
could now type xhost + on your local machine and try demo(graphics) in
your container again. You should now have graphical output. This method
however, is strongly discouraged as you allow access to your xsocket to
any remote host you're currently connected to. As long as you're only
interacting with single-user systems this might be somehow justifiable but
as soon as there are multiple users involved this will be absolutely
unsafe! Hence, you should use a less dangerous method. A good way is to
use the server interpreted xhost +si:localuser:username which can be
used to specify a single local user (see man xhost). This means
username should be the name of the user which runs the X11 server on
your local machine and which runs the Docker container. This is also the
reason why it is important that you specify a user when running your
container. Last but not least there is always the more complex solution of
using xauth and .Xauthority files to grant access to the X11 socket
(see man xauth). This however will also involve a little more knowledge
how X works.

Entering a running container with docker exec

As of release 1.3. the recommended way of entering a running container
is by using docker exec -it rdev bash (rdev is the name of the running
container and bash the program which is supposed to be run in the
container in this example.) which will spawn a new process in the running
container.

Entering a running container with nsenter

Should you need to enter a running container with a new tty you can also
use nsenter. First find the PID of the (main) process running in the
container by either issuing docker top containername or docker inspect --format {{.State.Pid}} containername. Then use nsenter which should
usually be installed on your system. If not install it. It can be found
util-linux (version must be at least 2.23). You can use the command
nsenter --target PID-you-just-found-out --mount --ipc --net --pid or the
short version nsenter -t PID-you-just-found-out -m -i -n -p.

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