When calling x[1] x x head(x)
[1] 3 2 3 4 5 6 # works!
> sapply(1:length(x), function(i) {x
Hello,
Are you using r x64?
How many Ram do you have available?
I ran your code and it took a lot more RAM that 7.6 Mb.
Try saving your file as .RData, close useless applications, and restart R.
Check your memory limit with memory.limit()
You can also set a new limit, in Mb, with: memory.limit(size = )
You should take a look at this: http://stackoverflow.com/questions/5171593/r-memory-management-cannot-allocate-vector-of-size-n-mb
Thank you for getting to my question. This is the session info:
> sessionInfo()
R version 3.3.2 (2016-10-31)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 8.1 x64 (build 9600)
locale:
[1] LC_COLLATE=German_Germany.1252 LC_CTYPE=German_Germany.1252
[3] LC_MONETARY=German_Germany.1252 LC_NUMERIC=C
[5] LC_TIME=German_Germany.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
> memory.limit()
[1] 65361
So that should be ok. I nevertheless get the error message.
Jochen,
The short answer is you're allocating a 1E6x1E6 array.
I modified your code a little for demonstration:
n
Shane, thank you for your help.
I think you solved my problem. I simply was not aware that sapply first allocates the entire matrix.
The purpose of my code is NOT to actually do something sensible. It was an experiment to see how a direct call to "[
Jochen,
I don't think sapply preallocates the entire matrix. It's building the matrix one row at a time, and when memory is full you get "Error: cannot allocate vector of size 7.6 Mb."
If you try to allocate the array with array(0,c(1E6,1E6)), you would get "Error: cannot allocate vector of size 7450.6 Gb." I'm a bit curious how much RAM Thyago has that he got your example to execute.
To be honest, I've never seen a call to "[
Yes, you are right. I forgot my original posting. The error was on some Mb where there are Gb of RAM available. So there must be some hidden allocation up to a point where the additional allocation of a few more Mb is not possible.
Interestingly, R 3.2.1 gives me additional warnings:
Error: cannot allocate vector of size 7.6 Mb
In addition: Warning messages:
1: In FUN(X[[i]], ...) :
Reached total allocation of 7944Mb: see help(memory.size)
2: In FUN(X[[i]], ...) :
Reached total allocation of 7944Mb: see help(memory.size)
3: In FUN(X[[i]], ...) :
Reached total allocation of 7944Mb: see help(memory.size)
4: In FUN(X[[i]], ...) :
Reached total allocation of 7944Mb: see help(memory.size)
>
I thought calling "[
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