Hi, Regarding your '10 commandments' in Q3, you may find useful tips in "the R inferno" by Pat Burns.
HTH, baptiste On 2 November 2010 05:04, Santosh Srinivas <santosh.srini...@gmail.com> wrote: > Hello Group, > > This is an open-ended question. > > Quite fascinated by the things I can do and the control I have on my > activities since I started using R. > I basically have been using this for analytical related work off my desktop. > My experience has been quite good and most issues where I need to > investigate and solve are typical items more related to data errors, format > corruption, etc... not necessarily "R" Related. > > Complementing this with Python gives enough firepower to do lots of > production (analytical related activities) on the cloud (from my research I > see that every innovative technology provider seems to support Python ... > google, amazon, etc). > > Question on using R for Production activities: > Q1) Does anyone have experience of using R-scripts etc ... for production > related activities. E.g. serving off a computational/ analytical / > simulation environment from a webportal with the analytical processing done > in R. > I've seen that most useful things for normal (not rocket science) business > (80-20 rule) can be done just as well in R in comparison with tools like > SAS, Matlab, etc. > > Q2) I haven't tried the processing routines for much larger data-sets > assuming "size" is not a constraint nowadays. > I know that I should try out ... but any forewarnings would help. Is it > likely that something that works for my "desktop" dataset is quite as likely > to work when scaled up to a "cloud dataset"? > Assuming that I do the clearing out of unused objects, not running into > infinite loops, etc? > > i.e. is there any problem with the "fundamental architecture of R itself"? > (like press articles often say) > > > Q3) There are big fans of the SAS, Matlab, Mathworks environments out there > .... does anyone have a comparison of how R fares. > >From my experience R is quite neat and low level ... so overheads should be > quite low. > Most slowness comes due to lack of knowledge (see my code ... like using the > wrong structures, functions, loops, etc.) rather than something wrong with > the way R itself is. > Perhaps there is no "commercial" focus to enhance performance related issues > but my guess is that it is just matter of time till the community evolves > the language to score higher on that too. > And perhaps develops documentation to assist the challenge users with > "performance tips" (the ten commandments types) > > Q4) You must have heard about the latest comment from James Goodnight of SAS > ... "We haven't noticed that a lot. Most of our companies need industrial > strength software that has been tested, put through every possible scenario > or failure to make sure everything works correctly." > My "gut" is that random passionate geeks (playing part-time) do better > testing than a military of professionals ... (but I've no empirical evidence > here) > > I am not taking a side here (although I appreciate those who do!) .. but > looking for an objective reasoning. > > Thanks, > S > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.