[Rcpp-devel] Data Persistence with Rcpp

[Christian Gunning]

On Wed, Sep 7, 2011 at 3:13 PM,
<rcpp-devel-request at r-forge.wu-wien.ac.at> wrote:
>  The question absolutely pertains to using the inline functionality.

I think this is a reasonable R/C++ question -- i.e. Rcpp.  inline is
more or less orthogonal to Rcpp.  inline is a great Rcpp jump-starter.

> As each new data arrives, I want to pass it to my C++ function.

After thinking about this for a bit, this might be a reasonable use
case for an Rcpp-module.  You can instantiate a module as an R object,
it will hold state, and can be easily updated, queried, etc.  The key
weakness here is that modules can't at present be serialized via
save()/load().  So, if you can do all your processing in one R
session, you might want to take a look at this.  The code ends up
clean and powerful.  I've been headed this way myself for
computationally extensive simulations that depend on time-varying
parameters residing in R dataframes.

Incidentally, an important question to ask yourself is:  where are
your bottlenecks?  It wasn't clear to me in reading your question
*why* you need C++.  The most popular use-case of Rcpp seems to be the
huge speed advantage.  Where/why do you need speed?  This should
highlight the code that needs to get pushed into C++.  R can compete
with compiled code in plenty of cases...

-xian

-- 
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