/home//R/-redhat-linux-gnu-library/, which is the destination for any package installed from the R console using install.packages.įor example, these are the library paths for a x86_64 machine with R 4.0 installed./usr/local/lib/R/library (the same for 64-bit architectures), which is not used by any package in the official repositories./usr/share/R/library contains system-provided packages without binary code.Īdditionally, the R installation adds the following paths:./usr/lib/R/library ( /usr/lib64/R/library in 64-bit architectures) contains system-provided packages with binary code./usr/share/R contains documentation, licenses and other non-binary files./usr/lib/R ( /usr/lib64/R in 64-bit architectures) contains R binaries and libraries.(sorry for this much background knowledge, if anyone thinks I am not even following the right phylosophy, feel free to leave in the comment how this whole cluster R package should be managed.The R installation is divided in two directories: before, however, it feels like will only install packages from source file instead of doing install.packages() in R console, figure out the mirror, pull the source file, install it in one command.Ĭan anyone show me how to use one command line in shell to non-interactively install a R package? So I prefer to have one Linux shell command to install the library. And I have to use some tool like Ansible to make it work. So sounds like I need to install it before hand, which leads us to approach2.

So most of the time will be wasted on installing libraries(sophisticated libraries like dplyr has tons of dependencies which will take minutes to install on a vanilla R session). However, this approach will have a dramatic overhead depending on how many libraries you are trying to install. Install.packages('dplyr', lib=temp, repos='') libPaths(c(.libPaths(), temp <- tempdir())) (1) In the reducer code, install the required libraries to a temporary folder and they will be disposed when the session is done, like this. Based on my research seems like there are two approaches: However, I need to figure out a way to access certain libraries that are not built in R, dplyr.etc. I am trying to implement a reducer for Hadoop Streaming using R.

Install r package linux