Hi, I would like to extend to the query posted earlier on using large data bases. I am trying to use Rgdal to mine within the remote sensing imageries. I dont have problems bring the images within the R environment. But when I try to convert the images to a data.frame I receive an warning message from R saying "1: Reached total allocation of 510Mb: see help(memory.size)" and the process terminates. Due to project constarints I am given a very old 2.4Ghz computer with only 512 MB RAM. I think what R is currently doing is trying to store the results in the RAM and since the image size is very big (some 9 million pixels), I think it gets out of memory.
My question is 1. Is there any possibility to dump the temporary variables in a temp folder within the hard disk (as many softwares do) instead of leting R store them in RAM 2. Could this be possible without creating a connection to a any back hand database like Oracle. Thanks, Mahesh On 7/19/06, Greg Snow <[EMAIL PROTECTED]> wrote: > > You did not say what analysis you want to do, but many common analyses > can be done as special cases of regression models and you can use the > biglm package to do regression models. > > Here is an example that worked for me to get the mean and standard > deviation by day from an oracle database with over 23 million rows (I > had previously set up 'edw' as an odbc connection to the database under > widows, any of the database connections packages should work for you > though): > > library(RODBC) > library(biglm) > > con <- odbcConnect('edw',uid='glsnow',pwd=pass) > > odbcQuery(con, "select ADMSN_WEEKDAY_CD, LOS_DYS from CM.CASEMIX_SMRY") > > t1 <- Sys.time() > > tmp <- sqlGetResults(con, max=100000) > > names(tmp) <- c("Day","LoS") > tmp$Day <- factor(tmp$Day, levels=as.character(1:7)) > tmp <- na.omit(tmp) > tmp <- subset(tmp, LoS > 0) > > ff <- log(LoS) ~ Day > > fit <- biglm(ff, tmp) > > i <- nrow(tmp) > while( !is.null(nrow( tmp <- sqlGetResults(con, max=100000) ) ) ){ > names(tmp) <- c("Day","LoS") > tmp$Day <- factor(tmp$Day, levels=as.character(1:7)) > tmp <- na.omit(tmp) > tmp <- subset(tmp, LoS > 0) > > fit <- update(fit,tmp) > > i <- i + nrow(tmp) > cat(format(i,big.mark=',')," rows processed\n") > } > > summary(fit) > > t2 <- Sys.time() > > t2-t1 > > Hope this helps, > > -- > Gregory (Greg) L. Snow Ph.D. > Statistical Data Center > Intermountain Healthcare > [EMAIL PROTECTED] > (801) 408-8111 > > > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of Yohan CHOUKROUN > Sent: Wednesday, July 19, 2006 9:42 AM > To: 'r-help@stat.math.ethz.ch' > Subject: [R] how to use large data set ? > > Hello R users, > > > > Sorry for my English, i'm French. > > > > I want to use a large dataset (3 millions of rows and 70 var) but I > don't know how to do because my computer crash quickly (P4 2.8Ghz, 1Go > ). > > I have also a bi Xeon with 2Go so I want to do computation on this > computer and show the results on mine. Both of them are on Windows XP... > > > > To do shortly I have: > > > > 1 server with a MySQL database > > 1computer > > and I want to use them with a large dataset. > > > > I'm trying to use RDCOM to connect the database and installing (but it's > hard for me..) Rpad. > > > > Is there another solutions ? > > > > Thanks in advance > > > > > > Yohan C. > > > > ---------------------------------------------------------------------- > Ce message est confidentiel. Son contenu ne represente en aucun cas un > engagement de la part du Groupe Soft Computing sous reserve de tout > accord conclu par ecrit entre vous et le Groupe Soft Computing. Toute > publication, utilisation ou diffusion, meme partielle, doit etre > autorisee prealablement. > Si vous n'etes pas destinataire de ce message, merci d'en avertir > immediatement l'expediteur. > This message is confidential. Its content does not constitute a > commitment by Soft Computing Group except where provided for in a > written agreement between you and Soft Computing Group. Any unauthorised > disclosure, use or dissemination, either whole or partial, is > prohibited. If you are not the intended recipient of this message, > please notify the sender immediately. > ---------------------------------------------------------------------- > > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > [[alternative HTML version deleted]] ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.