Hi,
I have been working with RODBC for a few months and have posted to this list
with questions(Thank You for the help!). The flexibility that ROracle would
bring to the Windows platform would be outstanding. I would like to write
SQL requests(no matter how complex) and simply call a function interface to
have them execute, and know that the analysis I have done with explain plan
would be accurate. Not to mention the other Oracle specific advantages that
package has.
P.S.
S-Plus Technical support told me to write my complex queries as stored
procedures and call those. I write/modify 2 or 3 a day. The DBA would just
love to hear from me.
Rich
-----Original Message-----
From: Fan [mailto:xiao.gang.fan1 at libertysurf.fr]
Sent: Thursday, January 17, 2002 4:03 PM
To: Ernesto Jardim
Cc: r-help at stat.math.ethz.ch
Subject: Re: [R] R for large data sets
AFAK, ROracle works only for R unix.
RODBC works very well for R Windows, I'd like to know
if there's any interests of ROracle for Windows users
(ex. large data sets, faster, etc.) ?
Thanks for advice
--
Xiao Gang FAN
Ernesto Jardim a ?crit :>
> 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 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 272860 (secr)
> > Oxford OX1 3TG, UK Fax: +44 1865 272595
> >
> >
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