RStudio is an integrated development environment (IDE) for R. It includes a console, syntax-highlighting editor that supports direct code execution, as well as tools for plotting, history, debugging and workspace management. For more information, see https://www.rstudio.com/products/RStudio/

Accessing RStudio

LMM users

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You may experience varying performance on rstudio.arcc.albany.edu, but don't worry, you can run RStudio on the cluster!

1. First SSH into head.its.albany.edu, you can follow the tutorial here: How-to: Connect via SSH (PuTTY, macOS terminal)

2. Run the following command:

   Code Block
   language bash
   cp /network/rit/misc/software/singularity/rstudio4.

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1. 4.

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1. 2.sbatch .

2. Now you can edit this file with vim, gedit, emacs, etc to request the amount of resources you need. Follow the FAQ page How-to: Scheduling via SLURM to learn about some of the #SBATCH commands in the file.

3. After changing the #SBATCH commands to suit your needs, run:

   Code Block
   language bash
   sbatch ~/rstudio4.

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1. 4.

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1. 2.sbatch

2. A log file will be generated in your home directory once your jobs spawns, following the naming convention rstudio_######.log, which documents how to connect to the server and kill the server when you are finished. Note that you must use the randomly generated password to log in

Using your own R Library

1. Create a file in your home directory called .Renviron 

2. Set R_LIBS_USER=/path/to/custom/R/lib
   

   1. You can do this in RStudio by clicking File -> new Text File
      

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1. 1. Image Added

   2. Then File -> Save As

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1. 1. Image Added

2. Restart RStudio by pressing 

   Image Modified

    in the upper right hand corner of the UI, then "Start New Session"

3. Check .libPaths() to make sure the correct path is being referenced

Updating your packages

If the system updates R and you find that your packages are no longer importing, please run from RStudio:

update.packages(checkBuilt=TRUE, ask=FALSE)