That's it! I was mounting /tmp with the noexec option. That was the
problem. Thanks!
On 2/24/2012 12:56 PM, Prof Brian Ripley wrote:
Guess: did you set TMPDIR to somewhere you are allowed to execute
scripts?
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h
This is in a 64 bit CentOS 5.6 instance at Amazon AWS with R version
2.14.1 (2011-12-22). It happens on several packages: RMySQL, RODBC,
FastICA. Many other packages install just fine.
Here's an example error message:
* installing *source* package 'RODBC' ...
** package 'RODBC' successfully
You're quite right; the problem lies in an SQL query ("LOAD DATA INFILE").
Thanks!
On 9/7/2010 6:50 AM, Duncan Murdoch wrote:
> Rob Steele wrote:
>> I run an external program a few hundred times via
>>
>> status <- system(command = "blah blah blah&quo
I run an external program a few hundred times via
status <- system(command = "blah blah blah")
and pretty soon Linux thinks R is using tons of memory. R doesn't think
so, at least not according to gc(). I'm also opening, reading and
closing files but I don't think that's where the problem lies.
Charles C. Berry wrote:
> On Thu, 26 Nov 2009, Rob Steele wrote:
>
>> Is there a faster way to get moving quantiles from a time series than to
>> run quantile() at each step in the series?
>
>
> Yes.
>
> Run
>
> help.request()
>
> Since
Charles C. Berry wrote:
> On Thu, 26 Nov 2009, Rob Steele wrote:
>
>> Is there a faster way to get moving quantiles from a time series than to
>> run quantile() at each step in the series?
>
>
> Yes.
>
> Run
>
> help.request()
>
> Since
Douglas Bates wrote:
> On Thu, Nov 26, 2009 at 10:03 AM, Rob Steele
> wrote:
>> These are the ways that occur to me.
>>
>> ## This produces a logical vector, which will get converted to a numeric
>> ## vector the first time a number is assigned to it. That seems
>
Douglas Bates wrote:
> On Thu, Nov 26, 2009 at 10:03 AM, Rob Steele
> wrote:
>> These are the ways that occur to me.
>>
>> ## This produces a logical vector, which will get converted to a numeric
>> ## vector the first time a number is assigned to it. That seems
>
These are the ways that occur to me.
## This produces a logical vector, which will get converted to a numeric
## vector the first time a number is assigned to it. That seems
## wasteful.
x <- rep(NA, n)
## This does the conversion ahead of time but it's still creating a
## logical vector first,
Is there a faster way to get moving quantiles from a time series than to
run quantile() at each step in the series?
Thanks,
Rob
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Rob Steele wrote:
> I'm finding that readLines() and read.fwf() take nearly two hours to
> work through a 3.5 GB file, even when reading in large (100 MB) chunks.
> The unix command wc by contrast processes the same file in three
> minutes. Is there a faster way to read files
meric? Are you keeping it in
> a dataframe? Have you considered using 'scan' to read in the data and to
> specify what the columns are? If you would like some more help, the answer
> to these questions will help.
>
> On Sat, May 9, 2009 at 10:09 PM, Rob Steele
>
Thanks guys, good suggestions. To clarify, I'm running on a fast
multi-core server with 16 GB RAM under 64 bit CentOS 5 and R 2.8.1.
Paging shouldn't be an issue since I'm reading in chunks and not trying
to store the whole file in memory at once. Thanks again.
Rob Steele wrote
I'm finding that readLines() and read.fwf() take nearly two hours to
work through a 3.5 GB file, even when reading in large (100 MB) chunks.
The unix command wc by contrast processes the same file in three
minutes. Is there a faster way to read files in R?
Thanks!
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