maiya wrote:
OK, it's the simple math that's confusing me :)

So you're saying 2.4GB, while windows sees the data as 700KB. Why is that
different?

700_MB_, I assume!

In a nutshell, a single column and a spacer takes 2 bytes per subject, but a floating point variable takes 8, and R is not good at detecting things that can be compressed. At best, you can ensure that variables are read as integers or factors, bringing the storage requirements down to four bytes.

The "ff" package might be something for you. The most strongly compressed items have trouble with storing NA values, though.

-p


And lets say I could potentially live with e.g. 1/3 of the cases - that
would make it .8GB, which should be fine? But then my question is if there
is any way to sample the rows in read.table? Or what would be the best way
of importing a random third of my cases?

Thanks!

M.



jholtman wrote:
A little simple math.  You have 3M rows with 100 items on each row.
If read in this would be 300M items.  If numeric, 8 bytes/item, this
is 2.4GB.  Given that you are probably using a 32 bit version of R,
you are probably out of luck.  A rule of thumb is that your largest
object should consume at most 25% of your memory since you will
probably be making copies as part of your processing.

Given that, is you want to read in 100 variables at a time, I would
say your limit would be about 500K rows to be reasonable.  So you have
a choice; read in fewer rolls, read in all 3M rows but at 20 columns
per read, put the data in a database and extract what you need.
Unless you go to a 64-bit version of R you will probably not be able
to have the whole file in memory at one time.

On Tue, Nov 10, 2009 at 7:10 AM, maiya <maja.zaloz...@gmail.com> wrote:
I'm trying to import a table into R the file is about 700MB. Here's my
first
try:

DD<-read.table("01uklicsam-20070301.dat",header=TRUE)
Error: cannot allocate vector of size 15.6 Mb
In addition: Warning messages:
1: In scan(file, what, nmax, sep, dec, quote, skip, nlines, na.strings,
 :
 Reached total allocation of 1535Mb: see help(memory.size)
2: In scan(file, what, nmax, sep, dec, quote, skip, nlines, na.strings,
 :
 Reached total allocation of 1535Mb: see help(memory.size)
3: In scan(file, what, nmax, sep, dec, quote, skip, nlines, na.strings,
 :
 Reached total allocation of 1535Mb: see help(memory.size)
4: In scan(file, what, nmax, sep, dec, quote, skip, nlines, na.strings,
 :
 Reached total allocation of 1535Mb: see help(memory.size)

Then I tried

memory.limit(size=4095)
 and got

DD<-read.table("01uklicsam-20070301.dat",header=TRUE)
Error: cannot allocate vector of size 11.3 Mb

but no additional errors. Then optimistically to clear up the workspace:

rm()
DD<-read.table("01uklicsam-20070301.dat",header=TRUE)
Error: cannot allocate vector of size 15.6 Mb

Can anyone help? I'm confused by the values even: 15.6Mb, 1535Mb, 11.3Mb?
I'm working on WinXP with 2 GB of RAM. Help says the maximum obtainable
memory is usually 2Gb. Surely they mean GB?

The file I'm importing has about 3 million cases with 100 variables that
I
want to crosstabulate each with each. Is this completely unrealistic?

Thanks!

Maja
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Jim Holtman
Cincinnati, OH
+1 513 646 9390

What is the problem that you are trying to solve?

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