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There are a lot of complaints about this 'slowness', but often the user can speed that up by writing better code. R is not inherently parallel, even if it has libraries and functions that are. So, if you use a loop or an apply function, it is not automatically parallelized. Another reason why we're using Ankhor analytics now is that they spread and execute calculations in loops automatically on all cores. Approved developers can get Grid server nodes. If you have complex long lasting jobs to run, a special shared loop operator sends the jobs to the grid nodes and collects the results for you without any extra effort :)
Interessting. May I propose ANKHOR FlowSheet as an powerful addition or replacement for some R projects ? Meanwhile we have moved completely from R to ANKHOR. Their R plugin helped us a lot in the during the transition. Although some of our programmers were crying ( 'we want to WRITE our code' ), everybody is now a convinced FlowSheeter. The fact that it utilizes all CPU cores ( and the GPU ), makes it a wonderful tool for all kinds of data centric applications. One of the best features ( and probably unique ) is the direct inspection of the results of an operation ( even the intermediate results in a loop ). THAT is much more powerful than any other traditional debugging methods. Just my 2 cents...
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Jun 14, 2015