The difference in using that is that the KNIME-managed one would just call RServe by itself while the R community nodes need RServe to be manually started from within R and the RServe needs to be up and running while using the nodes - that can be confusing, so maybe you stick with KNIME’s own nodes for now. Again there are two flavours of nodes one is the R environment managed by KNIME itself and then there is R Scripting from the community. Once you have R up and running you will need RServe so that KNIME nodes can communicate with it. So first to proper install R (and maybe RStudio to have an easier handling) and then point KNIME to it.
KNIME provides you with an ‘integrated’ R package that sits somewhere deep in the KNIME folders (“KNIME R Statistics Integration (Windows Binaries)”) You have a R version on your computer and you point KNIME to it (“KNIME Interactive R Statistics Integration”)
There are two basic possibilities to use R with KNIME But you will be able and have to install further libraries as your tasks evolve. To work with KNIME R needs several packages most prominently RServe (we come to that in a minute) and Cairo. Alongside that I recommend installing RStudio to easily manage R and that can also be useful in itself. OK first there are two ‘flavours’ of R you can install, on Windows the integrated Binaries (KNIME would manage all of R) or you get yourself a standalone version of R ( which I strongly recommend, and I recommend using the 64 Bit version wherever possible). Yes it takes some effort to get KNIME and R up and running but in the end you will be rewarded with the whole world of possibilities R has to offer, and you will be able to solve some tasks that you were not able to easily solve before while having the power of the workflow concept of one of the leading Data Scientist platforms at you fingertips. (If you are looking for a basic guide about how to install R in the first place you might look here or here).Ī few maybe unnecessary remarks upfront. Over the last months I have collected a few entries about the installation of R alongside KNIME that contain some maybe useful hints how to overcome certain obstacles while installing them.
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