[R] R for large data sets

[Ernesto Jardim]

Hi

ODBC is one more software layer between R and the database. In generic
terms I think it's better to use the proper client and "talk" directly
to the database server. 

Anyway I don't know exactly how ODBC for oracle works and I never made
any comparisons between the to packages (I use linux) so I can not give
you a fundamented answer.

Regards

EJ

On Thu, 2002-01-17 at 21:03, Fan wrote:

    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 écrit :
    > 
    > 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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