[R] Exception Handling

[Paul Gilbert]

I do this kind of thing under control of make. If you organize the 
individual pieces as separate targets then make -k will keep going and 
make -j can be used to run things in parallel.  R can be made to throw 
an error with something like this:

egTarget:	
	@$(MKDIR) $(FLAGS)
	@echo "library(tools); z <- doSomething() ; \
	  if (0 == length(capture.output(z))) q('no', status=0) else \
	   {print(z); q('no', status=1)} "  | R --vanilla --slave >$(FLAGS)/$@.tmp
	@mv  $(FLAGS)/$@.tmp $(FLAGS)/$@
	@touch $(FLAGS)/$@ # better time stamp in some parallel situations

In this example I am assuming that printing z has zero length output if 
everything was ok, but you could set up different situations, and you 
will probably want to use try() in doSomething().

HTH.
Paul Gilbert

> On Sun, Jul 6, 2008 at 7:36 PM, Tudor Bodea <gtg757i at mail.gatech.edu> wrote:
> 
>>Dear useRs:
>>
>>Please provide me with your thoughts on an issue related to the design of a
>>production level system.  For example, let's suppose that I need to run the
>>same R script for a finite sequence of items (e.g., in the energy industry, I
>>may need to asses the profitability of all gas stations in the state of
>>Florida).  For each of the items, the R script accesses some remote databases,
>>gets all the necessary information and processes the data locally.  If the
>>data for every item in the item list were not corrupted then the R script
>>would easily do its job.  However, every now and then, the data for some items
>>is partially missing and the R script returns in such cases an error message
>>(e.g., for a given gas station, 1 month worth of data is missing from a 3
>>month decision horizon).  As of right now, using the error option of options
>>(), whenever an exception happens, the R script sends me an email error
>>message and kills the current R instance.  As I already figured it out, this
>>is not necessarily the most efficient way to deal with such exceptions.
>>Ideally, I would like the script to inform me of the data problem but continue
>>the analysis with the remaining of the items.  Based on my searches, I believe
>>that try / stop can answer my problem.  However, if any of you already
>>implemented such a safe fail system I would really appreciate your taking the
>>time to (1) share with me what you think constitutes the best practices and/or
>>(2) point out to me any online material relevant to the topic.  I run various
>>versions of R on Windows and multiple UNIX platforms.  The list of items is
>>read from a .csv file and stored in a dataframe.
>>
>>Thank you.
>>
>>Tudor
>>
>>
>>--
>>Tudor Dan Bodea
>>Georgia Institute of Technology
>>School of Civil and Environmental Engineering
>>Web: http://www.prism.gatech.edu/~gtg757i
>>
>>______________________________________________
>>R-help at 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.
>>
> 
> 
> 
> 
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