[R] Alternatives to merge for large data sets?

[bogdan romocea]

One obvious alternative is an SQL join, which you could do directly in
a DBMS, or from R via RMySQL / RSQLite /... Keep in mind that creating
indexes on user/userid before the join may save a lot of time.


> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Adam
> D. I. Kramer
> Sent: Thursday, September 07, 2006 2:46 PM
> To: Prof Brian Ripley
> Cc: r-help at stat.math.ethz.ch
> Subject: Re: [R] Alternatives to merge for large data sets?
>
>
> On Thu, 7 Sep 2006, Prof Brian Ripley wrote:
>
> > Which version of R?
>
> Previously, 2.3.1.
>
> > Please try 2.4.0 alpha, as it has a different and more efficient
> > algorithm for the case of 1-1 matches.
>
> I downloaded and installed R-latest, but got the same error message:
>
> Error: cannot allocate vector of size 7301 Kb
>
> ...though at least the too-big size was larger this time.
>
> My data set is not exactly 1-1; every item in "prof" may have
> one or more
> matches in "pubbounds," though every item in "pubbounds"
> corrosponds only to
> one "prof."
>
> --Adam
>
> >
> > On Wed, 6 Sep 2006, Adam D. I. Kramer wrote:
> >
> >> Hello,
> >>
> >> I am trying to merge two very large data sets, via
> >>
> >> pubbounds.prof <-
> >>
> merge(x=pubbounds,y=prof,by.x="user",by.y="userid",all=TRUE,so
> rt=FALSE)
> >>
> >> which gives me an error of
> >>
> >> Error: cannot allocate vector of size 2962 Kb
> >>
> >> I am reasonably sure that this is correct syntax.
> >>
> >> The trouble is that pubbounds and prof are large; they are
> data frames which
> >> take up 70M and 11M respectively when saved as .Rdata files.
> >>
> >> I understand from various archive searches that "merge
> can't handle that,"
> >> because merge takes n^2 memory, which I do not have.
> >
> > Not really true (it has been changed since those days).  Of
> course, if you
> > have multiple matches it must do so.
> >
> >> My question is whether there is an alternative to merge
> which would carry
> >> out the process in a slower, iterative manner...or if I
> should just bite the
> >> bullet, write.table, and use a perl script to do the job.
> >>
> >> Thankful as always,
> >> Adam D. I. Kramer
> >
> > --
> > Brian D. Ripley,                  ripley at stats.ox.ac.uk
> > Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
> > University of Oxford,             Tel:  +44 1865 272861 (self)
> > 1 South Parks Road,                     +44 1865 272866 (PA)
> > Oxford OX1 3TG, UK                Fax:  +44 1865 272595
> >
>
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