On Sat, 24 Oct 2009, Carlos J. Gil Bellosta wrote:
Hello,
Adding to Thomas' email, you could also use package colbycol which
allows you to load into R files that a simple read.table cannot cope
with, study columns independently, select those you are more interested
in and, finally, set up a dataframe with just the columns you are
interested in.
It is just the same strategy Thomas suggested, only that without the
requirement of an external tool and using almost the same syntax as you
would use in case you had no memory problems.
I'm not sure that this has any less requirement for an external tool. Both
approaches require downloading an R package from CRAN. RSQLite requires SQLite,
but that is included in the package. colbycol requires Java (via rJava), which
isn't included in the package, but is already present on many machines.
-thomas
Best regards,
Carlos J. Gil Bellosta
http://www.datanalytics.com
On Fri, 2009-10-23 at 09:36 -0400, Anthony Damico wrote:
I'm working with a 350MB CSV file on a server that has 3GB of RAM, yet I'm
hitting a memory error when I try to store the data frame into a survey
design object, the R object that stores data for complex sample survey data.
When I launch R, I execute the following line from Windows:
"C:\Program Files\R\R-2.9.1\bin\Rgui.exe" --max-mem-size=2047M
Anything higher, and I get an error message saying the maximum has been set
to 2047M.
Here are the commands:
library(survey)
#this step takes more than five minutes
data08<-read.csv("data08.csv",header=TRUE,nrows=210437)
object.size(data08)
#329877112 bytes
#Looking at Windows Task Manager, Mem Usage for Rgui.exe is already 659,632K
brr.dsgn <-svrepdesign( data = data08 , repweights = data08[, grep(
"^repwgt" , colnames( data08)) ], type = "BRR" , combined.weights = TRUE ,
weights = data08$mainwgt )
#Error: cannot allocate vector of size 254.5 Mb
#The survey design object does not get created.
#This also causes Windows Task Manager, Mem Usage to spike to 1,748,136K
#And here are some memory diagnostics
memory.limit()
[1] 2047
memory.size()
[1] 1449.06
gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 131148 3.6 593642 15.9 15680924 418.8
Vcells 45479988 347.0 173526492 1324.0 220358611 1681.3
A description of the survey package can be found here:
http://faculty.washington.edu/tlumley/survey/
I tried creating a work-around by using the database-backed survey objects
(DB SO), included in the survey package to conserve memory on larger
datasets like this one. Unfortunately, I don't think the survey package
supports database connections for replicate weight designs yet, since I've
only been able to get a database connection working after creating a
svydesign object and not a svrepdesign object - and also because neither the
DB SO website nor the svrepdesign help page make any mention of those
parameters.
The DB SOs are described in detail here:
http://faculty.washington.edu/tlumley/survey/svy-dbi.html
Any advice would be truly appreciated.
Thanks,
Anthony Damico
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______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Thomas Lumley Assoc. Professor, Biostatistics
tlum...@u.washington.edu University of Washington, Seattle
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