| This post was kindly contributed by SAS and R - go there to comment and to read the full post. |
In 2012, we presented a post showing how to run RStudio in the cloud on an Amazon server. There were 7 steps, including one with 7 sub-steps, one of which had 6 sub-sub-steps. It was still pretty easy, for what it was– an effectively free computer in the cloud to run R on.
Today, we show the modern– 3 years later!– way to get the same result, only this approach is much easier, and the resulting installation includes all the best goodies of RStudio, including Markdown -> PDF and Hadley Wickham’s packages pre-installed.
The approach builds on Docker, an infrastructure that saves start-up time and overhead, as well as efforts led by Dirk Eddelbuettel and Carl Boettiger to develop a Docker application of R. This project is called Rocker, and interested readers are encouraged to read the details. But if you want to just get up and running, here are the simple steps to get going.
1. Go to Digital Ocean and sign up for an account. By using this link, you will get a $10 credit. (Full disclosure: Ken will also get a $25 credit once you spend $25 real dollars there.) The reason to use this provider is that they have a system ready to run with Docker already built in. In addition, their prices are quite reasonable. You will need to use a credit card or PayPal to activate your account, but you can play for a long time with your $10 credit– the cheapest machine is $.007 per hour, up to a $5 per month maximum.
2. On your Digital Ocean page, click “Create droplet”. Then choose an (arbitrary) name, a size (meaning cost/power) of machine, and the region closest to you. You can ignore the settings. Under “Select Image”, choose the “Applications” tab and select “Docker (1.3.2 on 14.04)”. (The numbers in the parentheses are the Docker and Ubuntu version, and might change over time.) Then click “Create Droplet” at the bottom of the page.
3. It takes about a minute for the machine to start up. When it’s ready, click the “Console Access” button. This opens a text terminal to your Ubuntu machine, inside your web page. Press enter to get a prompt, and log in (your username is root) using the password that was sent to your e-mail. You’ll have to change the password.
4a. To start a terminal session of R, type
docker run --rm -ti rocker/r-base
you should see a bunch of messages about pulling and downloading, but eventually you will get the “>” prompt– you can do R in here, but who would want to?
4b. To get RStudio server running, type
docker run -d -p 8787:8787 rocker/rstudio
But this is really not where you want to be. Instead, run the following command, to get a set-up that includes more useful packages installed in and with R.
docker run -d -p 8787:8787 rocker/hadleyverse
5. Use it! The IP address of your server is displayed below the terminal where you typed in your docker command. Open a new browser tab and go to the address http://(ip address):8787. For example: http://135.104.92.185:8787. You’ll see the RStudio login screen, and can enter “rstudio” (without the quotes) as the username and password. The system is well tuned enough that you can open a new file –> markdown –> PDF and immediately click “Knit PDF”, and see the example document beautifully presented back to you in moments.
That’s it. It’s still way cooler than sliced bread. let us know if you try it, and if you run into any trouble. Oh, and if you’re feeling creeped out by the standard username and password in your RStudio, you can set them up from your docker command as follows.
docker run -d -p 8787:8787 -e USER=ken -e PASSWORD=ken rocker/hadleyverse
Other customization details and further information can be found on this Rocker page.
Update
I should perhaps have noted that what you are running here is in fact RStudio Server, and that you can allow additional users on your RStudio using instructions found here.
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| This post was kindly contributed by SAS and R - go there to comment and to read the full post. |