Hi everyone, Any ideas on troubleshooting this memory issue:> d1<-read.csv("arrears.csv")Error: cannot allocate vector of size 77.3 Mb In addition: Warning messages: 1: In class(data) <- "data.frame" : Reached total allocation of 1535Mb: see help(memory.size) 2: In class(data) <- "data.frame" : Reached total allocation of 1535Mb: see help(memory.size) 3: In class(data) <- "data.frame" : Reached total allocation of 1535Mb: see help(memory.size) 4: In class(data) <- "data.frame" : Reached total allocation of 1535Mb: see help(memory.size) Thanks! Dan
Let's see... You could delete objects from your R session. You could buy more RAM. You could see help(memory.size). You could try googling to see how others have dealt with memory management in R, a process which turns up useful information like this: http://www.r-bloggers.com/memory-management-in-r-a-few-tips-and-tricks/ You could provide the information on your system requested in the posting guide. Sarah On Fri, Mar 2, 2012 at 9:57 AM, Dan Abner <dan.abner99 at gmail.com> wrote:> Hi everyone, > > Any ideas on troubleshooting this memory issue: > >> d1<-read.csv("arrears.csv") > Error: cannot allocate vector of size 77.3 Mb > In addition: Warning messages: > 1: In class(data) <- "data.frame" : > ?Reached total allocation of 1535Mb: see help(memory.size) > 2: In class(data) <- "data.frame" : > ?Reached total allocation of 1535Mb: see help(memory.size) > 3: In class(data) <- "data.frame" : > ?Reached total allocation of 1535Mb: see help(memory.size) > 4: In class(data) <- "data.frame" : > ?Reached total allocation of 1535Mb: see help(memory.size) > > > Thanks! > > Dan-- Sarah Goslee http://www.functionaldiversity.org
1. How much RAM do you have (looks like 2GB ) . If you have more than 2GB
then you can allocate
more memory with memory.size()
2. If you have 2GB or less then you have a couple options
a) make sure your session is clean of unnecessary objects.
b) Dont read in all the data if you dont need to ( see colClasses to
control this )
c) use the bigmemory package or ff package
d) buy more RAM
On Fri, Mar 2, 2012 at 6:57 AM, Dan Abner <dan.abner99@gmail.com> wrote:
> Hi everyone,
>
> Any ideas on troubleshooting this memory issue:
>
> > d1<-read.csv("arrears.csv")
> Error: cannot allocate vector of size 77.3 Mb
> In addition: Warning messages:
> 1: In class(data) <- "data.frame" :
> Reached total allocation of 1535Mb: see help(memory.size)
> 2: In class(data) <- "data.frame" :
> Reached total allocation of 1535Mb: see help(memory.size)
> 3: In class(data) <- "data.frame" :
> Reached total allocation of 1535Mb: see help(memory.size)
> 4: In class(data) <- "data.frame" :
> Reached total allocation of 1535Mb: see help(memory.size)
>
>
> Thanks!
>
> Dan
>
> ______________________________________________
> 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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On 02/03/2012 23:36, steven mosher wrote:> 1. How much RAM do you have (looks like 2GB ) . If you have more than 2GB > then you can allocate > more memory with memory.size()Actually, this looks like 32-bit Windows (unstated), so you cannot. See the rw-FAQ for things your sysadmin can do even there.> 2. If you have 2GB or less then you have a couple options > > a) make sure your session is clean of unnecessary objects. > b) Dont read in all the data if you dont need to ( see colClasses to > control this ) > c) use the bigmemory package or ff package > d) buy more RAMMost importantly, use a 64-bit OS to get a larger real address space. (bigmemory and ff are mainly palliative measures for those whose OS does not provide a good implementation of out-of-memory objects).> > On Fri, Mar 2, 2012 at 6:57 AM, Dan Abner<dan.abner99 at gmail.com> wrote: > >> Hi everyone, >> >> Any ideas on troubleshooting this memory issue: >> >>> d1<-read.csv("arrears.csv") >> Error: cannot allocate vector of size 77.3 Mb >> In addition: Warning messages: >> 1: In class(data)<- "data.frame" : >> Reached total allocation of 1535Mb: see help(memory.size) >> 2: In class(data)<- "data.frame" : >> Reached total allocation of 1535Mb: see help(memory.size) >> 3: In class(data)<- "data.frame" : >> Reached total allocation of 1535Mb: see help(memory.size) >> 4: In class(data)<- "data.frame" : >> Reached total allocation of 1535Mb: see help(memory.size) >> >> >> Thanks! >> >> Dan >> >> ______________________________________________ >> 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. >> > > [[alternative HTML version deleted]] > > ______________________________________________ > 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.-- Brian D. Ripley, ripley at stats.ox.ac.uk Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595