Displaying 20 results from an estimated 5000 matches similar to: "dealing with large objects -- memory wasting ?"
2000 Feb 11
1
astonishing memory phenomenon
I have a question concerning memory.
I understood that R takes a fixed amount of memory at startup (which I can
influence with --vsize --nsize) and that gc() shows the memory still free of
the total memory reserved for R.
However, if I create a long vector of character data, gc() only seem to
reflect the space needed for a vector of pointers to char, the space used
for the character data itself
2002 Apr 29
1
Garbage collection: RW1041
Have searched through the archives but have been unable to find any related
issues - hopefully I'm not bringing up an old topic.
Am using RW1041 on a Windows NT on a machine with 1Gb of memory. Have a
function doit() that reads in a chunk of data using readBin, performs a
regression, saves out coeffs and then returns. When using Rgui with the
default memory limit of 256Mb I'm able to
2011 Nov 13
1
Understand Ncells and Vcells, from gc()
Dear all,
I am working on a 64 bits Linux system.
I issue the following R commands:
> rm(list=ls()) # To remove all objects in the workspace.
> gc() # To free memory.
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 124250 6.7 350000 18.7 350000 18.7
Vcells 124547 1.0 786432 6.0 476934 3.7
> gc() # I had to do it again, don't know why!
used (Mb) gc trigger (Mb) max used (Mb)
Ncells
2011 Nov 13
1
To moderator
No. But it has not been posted either.
You got that message because you sent your message to
the wrong address. You should have sent it to
r-help at r-project.org
You had probably sent it to
r-help-request at r-project.org
which would have had the effect that the server would have
tried to interpret the contents of you message as commands
(e.g. to unsubscribe, change your subscription
Unnecessary extra copy with matrix(..., dimnames=NULL) (Was: Re: modifying large R objects in place)
2007 Sep 27
0
Unnecessary extra copy with matrix(..., dimnames=NULL) (Was: Re: modifying large R objects in place)
As others already mentioned, in your example you are first creating an
integer matrix and the coercing it to a double matrix by assigning
(double) 1 to element [1,1]. However, even when correcting for this
mistake, there is an extra copy created when using matrix().
Try this in a fresh vanilla R session:
> print(gc())
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 136684 3.7
2001 Mar 13
3
gc() shrinks with multiple iterations
Is it expected behavior for gc() to return shrinking values as it gets
called multiple times? Here's what I've got:
> gc()
used (Mb) gc trigger (Mb)
Ncells 221754 6.0 467875 12.5
Vcells 3760209 28.7 14880310 113.6
> gc()
used (Mb) gc trigger (Mb)
Ncells 221760 6.0 467875 12.5
Vcells 3016206 23.1 11904247 90.9
> gc()
used (Mb) gc
2001 Nov 26
2
R not giving memory back to system?
This might be because I didn't get it right, but; I thought R would
release memory back to the system as (big) objects get removed?
Here is my platform (with 1Gb of RAM):
platform sparc-sun-solaris2.8
arch sparc
os solaris2.8
system sparc, solaris2.8
status
major 1
minor 3.1
year 2001
month 08
day 31
language R
A little example:
Start a new section of R, with
2004 Aug 18
1
Memory Problems in R
Hello everyone -
I have a couple of questions about memory management of large objects.
Thanks in advance for your response.
I'm running R version 1.9.1 on solaris 8, compiled as a 32 bit app.
My system has 12.0 GB of memory, with usually ~ 11GB free. I checked
system limits using ulimit, and there is nothing set that would limit
the maximum amount of memory for a process (with the
2008 Apr 07
0
Some memory questions: data.frame and lists.
Hi there,
I seek your expert opinion on the following memory related questions. The
output below was gotten from R-2.6.2, compiled with
--enable-memory-profiling on Ubuntu Linux.
=======================================================================
>>> Code and output 1:
> gc( )
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 131180 7.1 350000 18.7 350000 18.7
2004 Jan 14
2
R internal data types
I am trying to figure out R data types and/or storage mode. For example:
> #From a clean workspace
> gc()
used (Mb) gc trigger (Mb)
Ncells 415227 11.1 597831 16
Vcells 103533 0.8 786432 6
> x <- seq(0,100000,1)
> is.integer(x)
[1] FALSE
> is.double(x)
[1] TRUE
> object.size(x)
[1] 800036
> gc()
used (Mb) gc trigger (Mb)
Ncells 415247
2007 May 25
0
Recent changes in R related to CHARSXPs
Hello all,
I want to highlight a recent change in R-devel to the larger developeR
community. As of r41495, R maintains a global cache of CHARSXPs such
that each unique string is stored only once in memory. For many
common use cases, such as dimnames of matrices and keys in
environments, the result is a significant savings in memory (and time
under some circumstances).
A result of these changes
2008 Jul 20
2
Erro: cannot allocate vector of size 216.0 Mb
Please,
I have a 2GB computer and a huge time-series to embedd, and i tried
increasing memory.limit() and memory.size(max=TRUE), but nothing.
Just before the command:
> memory.size(max=TRUE)
[1] 13.4375
> memory.limit()
[1] 1535.875
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 209552 5.6 407500 10.9 350000 9.4
Vcells 125966 1.0 786432 6.0 496686 3.8
2005 Nov 15
1
cannot.allocate.memory.again and 32bit<--->64bit
hello!
------
i use 32bit.Linux(SuSe)Server, so i'm limited with 3.5Gb of memory
i demonstrate, that there is times to times a problem with allocating of
objects of large size, for example
0.state (no objects yet created)
------------------------------------
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 162070 4.4 350000 9.4 350000
2007 Jun 26
1
Memory Experimentation: Rule of Thumb = 10-15 Times the Memory
dear R experts:
I am of course no R experts, but use it regularly. I thought I would
share some experimentation with memory use. I run a linux machine
with about 4GB of memory, and R 2.5.0.
upon startup, gc() reports
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 268755 14.4 407500 21.8 350000 18.7
Vcells 139137 1.1 786432 6.0 444750 3.4
This is my baseline. linux
2005 Dec 14
2
The fastest way to select and execute a few selected functions inside a function
Dear useRs?
I have the following problem! I have a function that calls one or more
functions, depending on the input parameters. I am searching for the fastest
way to select and execute the selected functions and return their results in
a list. The number of possible functions is 10, however usually only 2 are
selected (although sometimes more, even all).
For examples, if I have function
2010 Jul 07
3
Large discrepancies in the same object being saved to .RData
Hi developers,
After some investigation I have found there can be large discrepancies in the same object being saved as an external "xx.RData" file. The immediate repercussion of this is the possible increased size of your .RData workspace for no apparent reason.
The function and its three scenarios below highlight these discrepancies. Note that the object being returned is exactly
2004 Aug 07
1
memory usage of S4 methods
Hi,
I have some problems with the memory usage of S4-generics. For example, I
observed the following behaviour:
> gc()
used (Mb) gc trigger (Mb)
Ncells 432091 11.6 531268 14.2
Vcells 116052 0.9 786432 6.0
> setClass("A",representation(x="numeric"));
[1] "A"
> setClass("B",representation(x="numeric"));
[1] "B"
2005 Jan 14
1
S3/S4 classes performance comparison
Hi R-devel,
If you did read my survey on Rhelp about reporting, you may have seen that
I am implementing a way to handle outputs for R (mainly target output
destinations: xHTML and TeX).
In fact: I does have something that works for basic objects, entirely done
with S4 classes, with the results visible at:
http://www.stat.ucl.ac.be/ROMA/sample.htm
http://www.stat.ucl.ac.be/ROMA/sample.pdf
To
2011 Jan 17
1
isoreg memory leak?
I believe there is a memory leak in isoreg in the current version of R,
as I believe the following shows
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 120405 3.3 350000 9.4 350000 9.4
Vcells 78639 0.6 786432 6.0 392463 3.0
> for(k in 1:100) {
+
+ y <- runif(10000)
+ isoreg(x,y)
+ }
> rm(x)
> rm(y)
> gc()
used (Mb) gc
2010 Nov 04
1
Memory Management under Linux
Dear all,
I am using ubuntu linux 32 with 4 Gb. I am running a very small script and I always got the same error message: CAN NOT ALLOCATE A VECTOR OF SIZE 231.8 Mb.
I have reading carefully the instruction in ?Memory. Using the function gc() I got very low numbers of memory (please sea below). I know that it has been posted several times at r-help