From: Ernesto Jardim (ernesto@ipimar.pt)
Date: Wed 16 Jan 2002 - 23:22:29 EST
Message-id: <1011183749.18968.19.camel@gandalf>
Hi
I'm using some large datasets and I found the ROracle package to be of
great help.
If you have the chance to create a database in Oracle or MySQL with one
single table for your dataset, you can then use the ROracle package to
access the dataset. I found several advantages on that.
I don't import the data into my environment. I use a small function (see
below) to access the dataset and because the result is a data.frame you
can use it as usually.
Your environment will not be to large and you'll have the ram memory
less full.
It's easier to select subsets with SQL than S/R language.
Hope it helps
Regards
EJ
--//--
ora.fun <- function(){
library(ROracle)
m <- dbManager("Oracle")
con <- dbConnect(m,user="user",password="password")
dat <- quickSQL(con,"select ...")
close(con)
unload(m)
dat
}
--//--
On Tue, 2002-01-15 at 19:43, Prof Brian Ripley wrote:
> On Tue, 15 Jan 2002, wei, xiaoyan wrote:
>
> > As a part of our regular data analysis, I have to read in large data sets
> > with six columns and about a million rows. In Splus, this usually take a
> > couple of minutes. I just tried R, it seems take forever to use read.table()
> > to read in the data frame! It did not help much even though I specified
> > colClasses and nrows in read.table().
> >
> > How is R's ability to analyze large data sets? I used R on solaris 2.6 and I
> > used all default compilation flags when building the R package. Will it help
> > if I use some compilation flags with higher optimization level?
>
> It will help to use R-patched, since I guess you are using 1.4.0.
> Also, look in the list archives, as I answered this more fully earlier
> today.
>
> In either S-PLUS or R, scan would be a better choice for such a dataset.
>
> --
> Brian D. Ripley, ripley@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 272860 (secr)
> Oxford OX1 3TG, UK Fax: +44 1865 272595
>
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