How to speed up R packages installation in docker - r

Question

Say you have the following list of packages you would like to install for a docker image
("jsonlite","dplyr","stringr","tidyr","lubridate",
"knitr","purrr","tm","cba","caret",
"plumber","httr")
It actually takes around 1 hour to install these!
Any suggestions into how to speed up such a thing ? (or how to prevent the re-installation at every new image build ?)
Side note
I do not install these packages from the dockerfile like this:
RUN Rscript -e "install.packages('stringr')
...
Instead I create an R script Requirements.R which installs these packages and simply do:
RUN Rscript Requirements.R
Is these less optimal than installing the packages directly from the Dockerfile ?

Answer 1

Use binary packages where you can as we often do in the Rocker Project providing multiple Docker files for R, including the official r-base one.
If you start from Ubuntu, you get Michael's PPAs with over 3000+ packages; if you start from Debian you get fewer from the distro but still many essential ones. (There are some efforts to bring more binary packages to Debian but nothing is up right now.)
Lastly, Dockerfile creation is of course compile time too. You spend the time once (per container creation) and re-use potentially many time after. Also, by using the Docker Hub you can avoid spending your local cpu cycles.
Edit in Sep 2020: The (updated) Ubuntu PPA now has over 4600 package for the three most recent LTS releases. Still highly, highly recommended.

Answer 2

I found an article that described how to install R packages from precompiled binaries. It reduced the build time on our Jenkins server from 45 minutes down to 3 minutes.
Here is my Dockerfile:
FROM rocker/r-apt:bionic
WORKDIR /app
RUN apt-get update && \
apt-get install -y libxml2-dev
# Install binaries (see https://datawookie.netlify.com/blog/2019/01/docker-images-for-r-r-base-versus-r-apt/)
COPY ./requirements-bin.txt .
RUN cat requirements-bin.txt | xargs apt-get install -y -qq
# Install remaining packages from source
COPY ./requirements-src.R .
RUN Rscript requirements-src.R
# Clean up package registry
RUN rm -rf /var/lib/apt/lists/*
COPY ./src /app
EXPOSE 5000
CMD ["Rscript", "Server.R"]
You can add a file requirements-bin.txt with package names:
r-cran-plumber
r-cran-quanteda
r-cran-irlba
r-cran-lsa
r-cran-caret
r-cran-stringr
r-cran-dplyr
r-cran-magrittr
r-cran-randomforest
And finally, a requirements-src.R for packages that are not available as binairies:
pkgs <- c(
'otherpackage'
)
install.packages(pkgs)

Answer 3

I ended up using rocker/r-base as #DirkEddelbuettel suggested. Also thanks to this How to avoid reinstalling packages when building Docker image for Python projects? I wrote my Dockerfile in a way that doesen't reinstall packages every time I rebuild my docker image.
I want to share how my Dockerfile looks like now, hopefully this will be of help to others:
FROM rocker/r-base
RUN apt-get update
# install packages
RUN apt-get -y install libcurl4-openssl-dev
RUN apt-get -y install libssl-dev
# set work directory
WORKDIR /myapp
# copy requirments R script
COPY ./Requirements.R /myapp/Requirements.R
# run requirments R script
RUN Rscript Requirements.R
COPY . /myapp
EXPOSE 8094
ENV NAME R-test-service
CMD ["Rscript", "my_R_api.R"]