[R] Error: cannot allocate vector of size 3.4 Gb

[Benilton Carvalho]

you haven't answered how much resource you have available when you try  
reading in the data.

with the mouse exon chip, the math is the same i mentioned before.

having 8 GB, you should be able to read in 70 samples of this chip. if  
you can't, that's because you don't have enough resources when trying  
to read.

best,

b

On Nov 7, 2009, at 10:12 AM, Peng Yu wrote:

> On Fri, Nov 6, 2009 at 8:19 PM, Benilton Carvalho  
> <bcarvalh at jhsph.edu> wrote:
>> this is converging to bioc.
>>
>> let me know what your sessionInfo() is and what type of CEL files  
>> you're
>> trying to read, additionally provide exactly how you reproduce the  
>> problem.
>
>
> Here is my sessionInfo(). pname is 'moex10stv1cdf'.
>
>> for (f in list.celfiles('.',full.names=T,recursive=T)) {
> +   print(f)
> +   pname=cleancdfname(whatcdf(f))
> +   print(pname)
> + }
>
>
>> sessionInfo()
> R version 2.9.2 (2009-08-24)
> x86_64-unknown-linux-gnu
>
> locale:
> LC_CTYPE 
> = 
> en_US 
> .UTF 
> -8 
> ;LC_NUMERIC 
> = 
> C 
> ;LC_TIME 
> = 
> en_US 
> .UTF 
> -8 
> ;LC_COLLATE 
> = 
> en_US 
> .UTF 
> -8 
> ;LC_MONETARY 
> = 
> C 
> ;LC_MESSAGES 
> = 
> en_US 
> .UTF 
> -8 
> ;LC_PAPER 
> = 
> en_US 
> .UTF 
> -8 
> ;LC_NAME 
> = 
> C 
> ;LC_ADDRESS 
> =C;LC_TELEPHONE=C;LC_MEASUREMENT=en_US.UTF-8;LC_IDENTIFICATION=C
>
> attached base packages:
> [1] stats     graphics  grDevices utils     datasets  methods   base
>
> other attached packages:
> [1] pd.moex.1.0.st.v1_2.4.1 RSQLite_0.7-2           DBI_0.2-4
> [4] oligo_1.8.3             preprocessCore_1.6.0    oligoClasses_1.6.0
> [7] Biobase_2.4.1
>
> loaded via a namespace (and not attached):
> [1] affxparser_1.16.0 affyio_1.12.0     Biostrings_2.12.9  
> IRanges_1.2.3
> [5] splines_2.9.2
>
>
>> it appears to me, i'm not sure, that you start a fresh session of R  
>> and then
>> tries to read in the data - how much resource do you have available  
>> when you
>> try reading in the data? having 8GB RAM does not mean that you have  
>> 8GB when
>> you tried the task.
>>
>> b
>>
>> On Nov 7, 2009, at 12:08 AM, Peng Yu wrote:
>>
>>> On Fri, Nov 6, 2009 at 5:00 PM, Marc Schwartz <marc_schwartz at me.com>
>>> wrote:
>>>>
>>>> On Nov 6, 2009, at 4:19 PM, Peng Yu wrote:
>>>>
>>>>> On Fri, Nov 6, 2009 at 3:39 PM, Charlie Sharpsteen
>>>>> <chuck at sharpsteen.net>
>>>>> wrote:
>>>>>>
>>>>>> On Fri, Nov 6, 2009 at 1:30 PM, Peng Yu <pengyu.ut at gmail.com>  
>>>>>> wrote:
>>>>>>>
>>>>>>> I run R on a linux machine that has 8GB memory. But R gives me  
>>>>>>> an
>>>>>>> error "Error: cannot allocate vector of size 3.4 Gb". I'm  
>>>>>>> wondering
>>>>>>> why it can not allocate 3.4 Gb on a 8GB memory machine. How to  
>>>>>>> fix the
>>>>>>> problem?
>>>>>>
>>>>>> Is it 32-bit R or 64-bit R?
>>>>>>
>>>>>> Are you running any other programs besides R?
>>>>>>
>>>>>> How far into your data processing does the error occur?
>>>>>>
>>>>>> The more statements you execute, the more "fragmented" R's  
>>>>>> available
>>>>>> memory pool becomes.  A 3.4 Gb chunk may no longer be available.
>>>>>
>>>>> I'm pretty sure it is 64-bit R. But I need to double check. What
>>>>> command I should use to check?
>>>>>
>>>>> It seems that it didn't do anything but just read a lot of files
>>>>> before it showed up the above errors.
>>>>
>>>>
>>>> Check the output of:
>>>>
>>>> .Machine$sizeof.pointer
>>>>
>>>> If it is 4, R was built as 32 bit, if it is 8, R was built as 64  
>>>> bit.
>>>> See
>>>> ?.Machine for more information.
>>>
>>> It is 8. The code that give the error is listed below. There are 70
>>> celfiles. I'm wondering how to investigate what cause the problem  
>>> and
>>> fix it.
>>>
>>> library(oligo)
>>> cel_files = list.celfiles('.', full.names=T,recursive=T)
>>> data=read.celfiles(cel_files)
>>>
>>>> You can also check:
>>>>
>>>> R.version$arch
>>>>
>>>> and
>>>>
>>>> .Platform$r_arch
>>>>
>>>> which for 64 bit should show x86_64.
>>>>
>>>> HTH,
>>>>
>>>> Marc Schwartz
>>>>
>>>>
>>>
>>> ______________________________________________
>>> R-help at r-project.org 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 at r-project.org 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.