Since installation of such packages is not possible by running an R script with external stored procedure, we will explore the correct way to do this. In the R language, a library is installed by invoking this command:

Libraries are installed by installing packages available in common repositories, such as CRAN, Biocondutor, Github and many others.

Following on from my previous article, Introduction to R Services, I will extend the example with sp_execute_external_script and we will also call new libraries. But in the system the library must be, in the first place, installed. Referring to an R library in an R Script is super easy simply add the library or use the require() method.

So, to load a package into your R environment, the function library() is used, with the name of package specified in brackets. Deriving from the Windows OS, shared objects are called DLLs (dynamic-link library), hence the word library is used and refers to common and shared objects. The word, library(), is a function that loads functions in particular packages into your R environment. In the R language, when installing a package, the command 'install.packages' is used. A package might also be called a binary package or a tarball, depending on the operating system.Ī package is not equivalent to a library, nor should be mistaken for one. If you navigate to your R library folder, you will see all the packages installed for your R engine. A package is a collection of these files that reside in a library folder. These could be for graphs, for connections to different data sources, for specific mathematical or statistical computations, or many others.Įssentially, an R package is a container of functions that serve a particular purpose, with the binary source code (usually C++), documentation, and sample data. At some point, you will start using particular R packages that are designed for specific purposes.

As you progress in your use of R, you will be adding references to new R packages. The more complex the R script is, the more specific your R computation will be. In my previous article, the R scripts were fairly simple.

Load packages in r