how many vectors can be added in DataFrame::create( vec1, vec2 ... )?

Question

I am creating a DataFrame to hold a parsed haproxy http log files which has quite a few fields (25+).

If I add more than 20 vectors (one for each field), I get the compilation error:

no matching function call to 'create'

The create method:

    return DataFrame::create(
      _["clientIp"]     = clientIp,
      _["clientPort"]   = clientPort,
      _["acceptDate"]   = acceptDate,
      _["frontendName"] = frontendName,
      _["backendName"]  = backendName,
      _["serverName"]   = serverName,
      _["tq"]           = tq,
      _["tw"]           = tw,
      _["tc"]           = tc,
      _["tr"]           = tr,
      _["tt"]           = tt,
      _["status_code"]  = statusCode,
      _["bytes_read"]   = bytesRead,

#if CAPTURED_REQUEST_COOKIE_FIELD == 1
      _["capturedRequestCookie"]   = capturedRequestCookie,
#endif     

#if CAPTURED_REQUEST_COOKIE_FIELD == 1
      _["capturedResponseCookie"]   = capturedResponseCookie,
#endif    

      _["terminationState"] = terminationState,
      _["actconn"]          = actconn,
      _["feconn"]           = feconn,
      _["beconn"]           = beconn,
      _["srv_conn"]         = srvConn,
      _["retries"]          = retries,
      _["serverQueue"]      = serverQueue,
      _["backendQueue"]     = backendQueue 
    );

Questions:

1. Have I hit a hard limit?
2. Is there a workaround to allow me to add more than 20 vectors to a data frame?

Answer 1

Yes, you have hit a hard limit -- Rcpp is limited by the C++98 standard, which requires explicit code bloat to support 'variadic' arguments. Essentially, a new overload must be generated for each create function used, and to avoid choking the compiler Rcpp just provides up to 20.

A workaround would be to use a 'builder' class, where you successively add elements, and then convert to DataFrame at the end. A simple example of such a class -- we create a ListBuilder object, for which we successively add new columns. Try running Rcpp::sourceCpp() with this file to see the output.

#include <Rcpp.h>
using namespace Rcpp;

class ListBuilder {

public:

   ListBuilder() {};
   ~ListBuilder() {};

   inline ListBuilder& add(std::string const& name, SEXP x) {
      names.push_back(name);

      // NOTE: we need to protect the SEXPs we pass in; there is
      // probably a nicer way to handle this but ...
      elements.push_back(PROTECT(x));

      return *this;
   }

   inline operator List() const {
      List result(elements.size());
      for (size_t i = 0; i < elements.size(); ++i) {
         result[i] = elements[i];
      }
      result.attr("names") = wrap(names);
      UNPROTECT(elements.size());
      return result;
   }

   inline operator DataFrame() const {
      List result = static_cast<List>(*this);
      result.attr("class") = "data.frame";
      result.attr("row.names") = IntegerVector::create(NA_INTEGER, XLENGTH(elements[0]));
      return result;
   }

private:

   std::vector<std::string> names;
   std::vector<SEXP> elements;

   ListBuilder(ListBuilder const&) {}; // not safe to copy

};

// [[Rcpp::export]]
DataFrame test_builder(SEXP x, SEXP y, SEXP z) {
   return ListBuilder()
      .add("foo", x)
      .add("bar", y)
      .add("baz", z);
}

/*** R
test_builder(1:5, letters[1:5], rnorm(5))
*/

PS: With Rcpp11, we have variadic functions and hence the limitations are removed.

Answer 2

The other common approach with Rcpp is to just use an outer list containing as many DataFrame objects (with each limited by the number of elements provided via the old-school macro expansion / repetition) in the corresponding header) as you need.

In (untested) code:

Rcpp::DataFrame a = Rcpp::DateFrame::create(/* ... */);
Rcpp::DataFrame b = Rcpp::DateFrame::create(/* ... */);
Rcpp::DataFrame c = Rcpp::DateFrame::create(/* ... */);

return Rcpp::List::create(Rcpp::Named("a") = a,
                          Rcpp::Named("b") = b,
                          Rcpp::Named("c") = c);