similar to: Solved Re: Garbage collection problem

Hello all, I am running into a problem with garbage collection not being able to free up all memory. Unfortunately I am unable to provide a minimal self-contained example, although I can provide a self contained example if anyone feels like wading through some 600 lines of code. I would love to isolate the relevant parts from the code but whenever I try to run a simpler example, the problem does

Full_Name: Ed Borasky Version: 1.8.1 OS: Windows XP Professional Submission from: (NULL) (208.252.96.195) R 1.8.1 seems to be running into a memory allocation problem in the "aggregate" function. I have a rather large dataset (14 columns by 223,000 rows -- almost 40 megabytes) and a script that performs some processing on it. The system is a 768 MB Pentium 4. Here's the console

[some de-capitalization of *SXP done manually by mailing list maintainer ; the originally was caught as potential spam. MM] I have a little R program that crashes with the message xmalloc: out of virtual memory The code has a repeat{} loop that watches the sizes of some files. When there's an increase it updates things by reading the last 65 lines of each file, doing some

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

Hello, After experiencing some difficulties with large arrays, I was surprised to see the apparent need for class to gc() after creating fairly large arrays. For example, calling a<-array(2, dim=c(10,10,10,10,10,100)) makes the memory usage of a fresh session of R jump from 13.8 Mb to 166.4 Mb. A call to gc() brought it down to 90.8 Mb, > gc() used (Mb) gc trigger (Mb)

Hi, I am trying to minimize a rather complex function of 5 parameters with gafit and nlm. Besides some problems with both optimization algorithms (with respect to consistantly generating similar results), I tried to run this optimization about a hundred times for yet two other parameters. Unfortunately, as the log below shows, during that batch process R starts to eat up all my RAM,

Hi, all; I know there has been a lot of discussions on memory usage in R. However, I have some odd situation here. Basically, I have a rare opportunity to run R in a system with 64GB memory without any limit on memory usage for any person or process. However, I encountered the memory problem error message like this: Error: cannot allocate vector of size 594075 Kb I got this error message while

Happy new year to all; A few days ago, I posted similar problem. At that time, I found out that our R program had been 32-bit compiled, not 64-bit compiled. So the R program has been re-installed in 64-bit and run the same job, reading in 150 Affymetrix U133A v2 CEL files and perform dChip processing. However, the memory problem happened again. Since the amount of physical memory is 64GB, I think

Dear all, Me and the Garbage Collector doesn't understand each other... I'm on R-1.0.1 (I have requested an upgrade to the right local people), an osf1 system with an alphaev6 CPU. I have fair amounts of memory to use, but it seems to be used up pretty fast nevertheless. I'm now trying to see what the garbage collector does, I have inserted a gc(v=T) call at a spot in my code. I

Dear all, I am processing a very long and complicated list using lapply through a custom function and I would like to generate some sort of progress report. For instance, print a dot on the screen every time 1000 item have been process. Or even better, reporting the percent of the list that have been process every 10%. However, I can't seem to figure out a way to achieve that. For instance,

Full_Name: Saket Joshi Version: 1.5.0 OS: Solaris 5.8 Submission from: (NULL) (128.193.38.91) According to the documentation obtained by entering: help.search("gc"), the command gc() forces garbage collection and gives the memory usage statistics along with the trigger values in bytes also interpretted in megabytes. However when I ran gc(), the result was a list giving the memory usage

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

Hi all I had written a gdb macro to dump the string representation of an SEXPREC type when I realised everything I needed was in inspect.c already in the typename() function. However, the typename function doesnt handle the RAWSXP type, so if possible, could the following patch be applied (I've just put in inline as it is a trivial 1-liner)? Index: src/main/inspect.c

Is it possible for S4 to (continue) dispatch to a class created during dispatching? The code below doesn't work; is this not possible or have I ommitted something? Concept was to create a SEXP with R_AllocatePtr, give it a class attribute, and continue dispatch. Example code below omits multiple parameters that can be different types. Essentially, any parameter would be converted to an

Hi Allessandro and all Bacula users and especially to (potential) Bacula contributors, On Mon, 11 May 2015 20:49:08 +0200 Alessandro Baggi <alessandro.baggi at gmail.com> wrote: > In my last request I have asked info about backuppc and other backup > solutions. After some test I have choosen bacula. Concerning the topic "Free Software" I read that the relations between

Allocating many small objects triggers numerous garbage collections as R grows its memory, seriously degrading performance. The specific use case is in creating a STRSXP of several 1,000,000's of elements of 60-100 characters each; a simplified illustration understating the effects (because there is initially little to garbage collect, in contrast to an R session with several packages

In the first paragraph of Sweave.Rnw (./src/library/utils/vignettes/Sweave.Rnw), it reads for literate programming \cite{fla:Knuth:1984}. but probably should be for literate programming \citep{fla:Knuth:1984}. ^ kind regards Enrico -- Enrico Schumann Lucerne, Switzerland http://enricoschumann.net

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

In R 3.5 and later you should not need to gc() -- that should happen automatically within the connections code. Nevertheless, I would recommend redesigning your approach to avoid hanging onto open file connections as these are a scarce resource. You can keep around your temporary files without having them open and only open/close them on access, with the close run in an on.exit or a

I currently have a program that automates 2-way ANOVA on a series of endpoints, but before the ANOVA is carried out I want the code to test the assumptions of normality and equal variance and report along with each anova result in the output file.  How can I do this? I have pasted below the code that I currently use.   library(car) numFiles = x #