Using Docker containers in R

Docker containers are everywhere nowadays, and there are many use cases for containerizing R code. In this deck, I go over the benefits of using containers based on examples from the R universe, and share a few tips and tricks for efficient Docker based workflows.

Transcript

1. Using Docker containers in R
   @tudosgar | tamaszilagyi.com
   

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2. 2
   whoami
   @tudosgar | tamaszilagyi.com
   • EX - Sr. Analyst ING
   • blog: http:/
   /tamaszilagyi.com/
   • love hiking!
   

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3. 3
   • Docker Basics
   • Our first Docker container: 2 usecases
   • Best practices, tools and resources
   Agenda
   @tudosgar | tamaszilagyi.com
   

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4. 4
   @tudosgar | tamaszilagyi.com
   Your program
   you
   not you
   

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5. 5
   @tudosgar | tamaszilagyi.com
   Your program
   dev
   prod
   

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6. 6
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   Common
   problems
   • Different OS
   • Missing system-level dependencies
   • Missing packages
   • Different versions
   • Missing keys
   • …
   

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7. The solution?
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8. The solution?
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9. @tudosgar | tamaszilagyi.com
   Infrastructure
   Host OS
   Docker engine
   app B
   bin / lib bin / lib
   app A
   Infrastructure
   Host OS
   Hypervisor
   guest OS guest OS
   bin / lib bin / lib
   app A app B
   Containers
   Virtual Machines
   Unlike VM’s, containers are not “real
   computers”, just a combination of Linux
   kernel features that isolate what the
   processes inside can see and use.
   

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10. Benefits
    @tudosgar | tamaszilagyi.com
    • OS independent
    • Your code is all of a sudden portable
    • Your analysis is reproducible
    • Consistency in production
    • Prototype -> deployment is faster
    • Relatively lightweight footprint
    

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11. 11
    Your first Docker
    container.
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12. 12
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    Dockerfile Image Container
    

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13. 13
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    Dockerfile Image Container
    write command command
    

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14. 14
    Usecase #1:
    Shiny App
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15. 15
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    A shiny app consists of two components:
    1. A ui.R that defines the frontend logic.
    Shiny App assets
    

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16. 16
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    A shiny app consists of two components:
    1. A ui.R that defines the frontend logic.
    2. And a server.R for the backend.
    Shiny App assets
    

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17. 17
    How do we
    package this up?
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18. 18
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    The Dockerfile is a text file that contains all the
    instructions on how to build and assemble the
    image.
    Each is instruction is a layer. We start with a
    (larger) read-only layers, this is our base image.
    Everything ]after are (small) read-write layers.
    read-only
    base layers
    read-write
    layers
    Write a Dockerfile!
    

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19. 19
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    The base image contains the read-only layers
    and is preceded by FROM. Specifically for R,
    the rocker project (https:/
    /www.rocker-
    project.org/images/) maintains many useful
    images, for example for shiny apps.
    The read-write layers are what we add, and
    here we simply COPY our app into the
    relevant folder inside the container.
    Dockerfile
    

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20. 20
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    Dockerfile Image Container
    write command command
    

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21. 21
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    If your app is large, use volumes!
    

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22. 22
    Interlude:
    docker commands
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    • docker build builds a docker image from our Dockerfile.
    • docker run instantiates the container from our image.
    • docker ps list (running) containers
    • docker kill terminates a container.
    • docker rm deletes a container.
    • docker login login to Dockerhub (to upload our image).
    • docker push uploads the image back to Dockerhub.
    • docker pull pulls an image from the registry (Dockerhub).
    

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23. 23
    Usecase #2:
    Web API
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24. 24
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    We can create Web API’s by creating a plumber.R
    file by “merely decorating your existing R source
    code with special comments”
    Using Plumber
    

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25. 25
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    We can then plumb our function and expose it to
    the outside world (in this case only locally).
    Using Plumber
    

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26. 26
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    We don’t always have everything we need for
    our application to run. In this case we need to
    install additional packages and its system level
    dependencies.
    We can also EXPOSE ports from within the
    Dockerfie and run commands using CMD.
    Dockerfile
    

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27. 27
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    Dockerfile Image Container
    write command command
    

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28. 28
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    Tips & Tricks
    

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29. 29
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    Use shared base layer images
    

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30. 30
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    Less layers is better
    

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31. 31
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    Use volumes
    

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32. 32
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    Push down layers that invalidate the cache
    

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33. 33
    Tools & resources
    @tudosgar | tamaszilagyi.com
    • R-specific base images: https:/
    /hub.docker.com/r/rocker/
    • Free interactive tutorials: https:/
    /katacoda.com/courses/docker
    • Packages containerit and liftr to automatically containerize your R-code
    • Follow @jessfraz and @abbyfuller
    

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34. http:/
    /tamaszilagyi.com/
    @tudosgar
    @tudosgar | tamaszilagyi.com
    Keep in touch!
    

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