Most of the 8GB was available, when I run the code, because R was the
only computation session running.
On Sat, Nov 7, 2009 at 7:51 AM, Benilton Carvalho <bcarv...@jhsph.edu> wrote:
> 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 <bcarv...@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_schwa...@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
>>>>>> <ch...@sharpsteen.net>
>>>>>> wrote:
>>>>>>>
>>>>>>> On Fri, Nov 6, 2009 at 1:30 PM, Peng Yu <pengyu...@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@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@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.
>
>
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