As of 2.15.1, data.frame appears to no longer be O(n^2) in the number of columns in the frame. That's certainly an improvement, yes.
However, by eliminating calls to data.frame and replacing them with direct class modifications, I can take a routine which takes minutes and reduce it to a routine which takes seconds. So, pragmatically, in Rcpp, I can get a rough factor of sixty, it appears. On Thu, Jan 17, 2013 at 7:46 PM, Paul Johnson <pauljoh...@gmail.com> wrote: > On Tue, Jan 15, 2013 at 9:20 AM, John Merrill <john.merr...@gmail.com> > wrote: > > It appears that DataFrame::create is a thin layer on top of the R > data.frame > > call. The guarantee correctness, but also means the performance of an > Rcpp > > routine which returns a large data frame is limited by the performance of > > data.frame -- which is utterly horrible. > > Are you certain that this claim is still true? > > I was shocked/surprised by the package "dataframe" and the commentary > about it. The author said that data.frame was slow because "This > contains versions of standard data frame functions in R, modified to > avoid making extra copies of inputs. This is faster, particularly for > large data." > > it was repeatedly copying some objects and he proved a substantially > faster approach. > > In the release notes for R-2.15.1, I recall seeing a note that R Core > had responded by integrating several of those changes. But still > data.frame is not fast for you? > > If they didn't make the core data.frame as fast, would you care to > enlighten us by installing the dataframe package and letting us know > if it is still faster? > > Or perhaps you are way ahead of me and you've already imitated > Hesterberg's algorithms in your C++ design? > > pj > > -- > Paul E. Johnson > Professor, Political Science Assoc. Director > 1541 Lilac Lane, Room 504 Center for Research Methods > University of Kansas University of Kansas > http://pj.freefaculty.org http://quant.ku.edu >
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