Displaying 20 results from an estimated 800 matches similar to: "Installation of bigmemory fails"
2011 Nov 30
1
Error adding Bigmemory package
I am trying to add the bigmemory packages but I get the following error
message:
In file included from bigmemory.cpp:14:0:
../inst/include/bigmemory/isna.hpp: In function 'bool neginf(double)':
../inst/include/bigmemory/isna.hpp:22:57: error: 'isinf' was not declared in
this scope
make: *** [bigmemory.o] Error 1
ERROR: compilation failed for package 'bigmemory'
* removing
2010 Aug 11
1
Bigmemory: Error Running Example
Hi,
I am trying to run the bigmemory example provided on the
http://www.bigmemory.org/
The example runs on the "airline data" and generates summary of the csv
files:-
library(bigmemory)
library(biganalytics)
x <- read.big.matrix("2005.csv", type="integer", header=TRUE,
backingfile="airline.bin",
descriptorfile="airline.desc",
2010 Feb 22
1
big panel: filehash, bigmemory or other
Dear R-list
I'm on my way to start a new project on a rather big panel, consisting
of approximately 8 million observations in 30 waves of data and about
15 variables. I have a similar data set that is approximately 7
gigabytes in size.
Until now I have done my data management in SAS, and Stata, mostly
identifying spells, counting events in intervals, and a like, but I
would like to
2012 May 11
1
bigmemory
To answer your first question about read.big.matrix(), we don't know what
your acc3.dat file is, but it doesn't appear to have been detected as a
standard file (like a CSV file) or -- perhaps -- doesn't even exist (or
doesn't exist in your current directory)?
Next:
> In addition, I am planning to do a multiple imputation with MICE package
> using the data read by bigmemory
2019 Jul 19
1
difficulty with sanitizer using bigmemory
Dear all,
bigKRLS, which has been on CRAN for a couple of years, had to be pulled
recently due to what seems to be a sanitizer issue stemming from its use of
bigmemory. bigKRLS works fine (we?ve used it ourselves on many different
platforms and have had over 15,000 downloads without an end user reporting
difficulties because of this issue). Unfortunately, we have been unable to
reproduce the
2012 May 05
2
looking for adice on bigmemory framework with C++ and java interoperability
I work with problems that have rather large data requirements -- typically
a bunch of multigig arrays. Given how generous R is with using memory, the
only way for me to work with R has been to use bigmatrices from bigmemory
package. One thing that is missing a bit is interoperability of bigmatrices
with C++ and possibly java. What i mean by that is API that would allow
read and write filebacked
2011 Sep 29
1
efficient coding with foreach and bigmemory
I recently learned about the bigmemory and foreach packages and am trying
to use them to help me create a very large matrix. Without those
packages, I can create the type of matrix that I want with 10 columns and
5e6 rows. I would like to be able to scale up to 5e9 rows, or more, if
possible.
I have created a simplified example of what I'm trying to do, below. The
first part of the
2010 Dec 17
1
[Fwd: adding more columns in big.matrix object of bigmemory package]
Hi,
With reference to the mail below, I have large datasets, coming from various
different sources, which I can read into filebacked big.matrix using library
bigmemory. I want to merge them all into one 'big.matrix' object. (Later, I
want to run regression using library 'biglm').
I am unsuccessfully trying to do this from quite some time now. Can you
please
2010 Apr 23
2
bigmemory package woes
I have pretty big data sizes, like matrices of .5 to 1.5GB so once i need to
juggle several of them i am in need of disk cache. I am trying to use
bigmemory package but getting problems that are hard to understand. I am
getting seg faults and machine just hanging. I work by the way on Red Hat
Linux, 64 bit R version 10.
Simplest problem is just saving matrices. When i do something like
2013 Apr 29
2
bigmemory and R 3.0
Dear helpers,
Does anyone have information on the status of bigmemory and R3.0? Will it
just take time for the devs to re-code for the new environment? Or is there
an alternative for this new version?
Thanks
Ben Caldwell
[[alternative HTML version deleted]]
2010 Sep 08
1
bigmemory doubt
Hi,
Is it possible for me to read data from shared memory created by a vc++ program into R using bigmemory?
[[alternative HTML version deleted]]
2011 Jul 18
5
[LLVMdev] dragonegg svn still broken
Despite the commit of...
------------------------------------------------------------------------
r135371 | lattner | 2011-07-18 00:25:32 -0400 (Mon, 18 Jul 2011) | 2 lines
untested patch to de-constify llvm::Type, patch by David Blaikie!
current dragonegg svn at r135391 still fails to compile against FSF gcc 4.5.3
with the failure...
In file included from
2011 Dec 01
1
bigmemory on Solaris
At one point we might have gotten something working (older version?) on
Solaris x86, but were never successful on Solaris sparc that I remember --
it isn't a platform we can test and support. We believe there are problems
with BOOST library compatibilities.
We'll try (again) to clear up the other warnings in the logs, though. !-)
We should also revisit the possibility of a CRAN BOOST
2012 Oct 18
3
bigmemory for dataframes?
Hi Folks,
I've been bumping my head against the 4GB limit for 32-bit R. I can't
go to 64-bit R due to package compatibility issues (ROBDC - possible but
painful, xlsReadWrite - not possible, and others). I have a number of
big dataframes whose columns all sorts of data types - factor,
character, integer, etc. I run and save models that keep copies of the
modeled data inside the model
2010 Feb 06
2
question about bigmemory: releasing RAM from a big.matrix that isn't used anymore
Hi all,
I'm on a Linux server with 48Gb RAM. I did the following:
x <- big.matrix(nrow=20000,ncol=500000,type='short',init=0,dimnames=list(1:20000,1:500000))
#Gets around the 2^31 issue - yeah!
in Unix, when I hit the "top" command, I see R is taking up about 18Gb
RAM, even though the object x is 0 bytes in R. That's fine: that's how
bigmemory is supposed to
2009 Jun 02
2
bigmemory - extracting submatrix from big.matrix object
I am using the library(bigmemory) to handle large datasets, say 1 GB,
and facing following problems. Any hints from anybody can be helpful.
_Problem-1:
_
I am using "read.big.matrix" function to create a filebacked big matrix
of my data and get the following warning:
> x =
read.big.matrix("/home/utkarsh.s/data.csv",header=T,type="double",shared=T,backingfile
2011 Apr 15
1
[LLVMdev] -fplugin-arg-dragonegg-enable-gcc-optzns impact
On Fri, Apr 15, 2011 at 08:53:19AM +0200, Duncan Sands wrote:
> Hi Jack,
>
> > Now that dragoneegg is robust in its default usage and the dragonegg svn
> > is moderately stable with -fplugin-arg-dragonegg-enable-gcc-optzns, it is
> > possible to gauge the impact of that feature. Comparing clang 2.9, FSF gcc 4.5.3svn,
> > FSF gcc 4.6.0 and dragonegg svn with FSF
2011 Apr 19
2
[LLVMdev] dragonegg bootstrap gcc 4.5.2
The current dragonegg trunk svn used under FSF gcc 4.5.2 with llvm 2.9
is able to bootstrap FSF gcc 4.5.2 itself on x86_64-apple-darwin10...
Using built-in specs.
COLLECT_GCC=gcc-mp-4.5
COLLECT_LTO_WRAPPER=/opt/local/libexec/gcc/x86_64-apple-darwin10/4.5.2/lto-wrapper
Target: x86_64-apple-darwin10
Configured with: ../gcc-4.5.2/configure --prefix=/opt/local --build=x86_64-apple-darwin10
2010 Mar 11
2
ANNOUNCE--Rdsm package, a threads-like environment for R
My long-promised Rdsm package is now on CRAN. Some of you may recall
that I made a prototype available on my own Web page last July. This is
the official version, much evolved since I released the prototype.
The CRAN description states:
Provides a threads-like programming environment for R, usable both on
a multicore machine and across a network of multiple machines. The
package
2008 Jun 25
0
Package bigmemory now available on CRAN
Package "bigmemory" is now available on CRAN. A brief abstract follows:
Multi-gigabyte data sets challenge and frustrate R users even on
well-equipped hardware.
C/C++ and Fortran programming can be helpful, but is cumbersome for interactive
data analysis and lacks the flexibility and power of R's rich
statistical programming environment.
The new package bigmemory bridges this gap,