similar to: going past restrictions on number of elements

Dear R-ers, somehow it is not possible to increase nsize to more than 20000k. When I specify e.g. > R --vsize=10M --nsize=21000K the result is: free total (Mb) Ncells 99658 350000 6.7 Vcells 1219173 1310720 10.0 Maybe I have overlooked s.th.... Marcus -- +------------------------------------------------------- | Marcus Eger | E-Mail: eger.m at gmx.de (NEW) |

I am running R version ??? under Redhat 5.2. It seems as though the --nsize object has no effct on the size of the allocated Ncells as determined using gc(). Yes, I have that much data.... That is if I envoke R with R --vsize 100 --nsize 5000000 then type gc() I get free total Ncells 92202 200000 Vcells 12928414 13107200 Thanks Tony Long Ecology and Evolutionary Biology Steinhaus

I am trying to use tree to partition a data set. The data set has 3924 observations. Partitioning seems to work for small subsets of the data, but when I use the entire data set, no partitioning occurs. The variables are: RESP respondent to a survey (0 = not a respondent, 1 = respondent) AGE_P Age (continuous) ORIGIN_I Hispanic Ethnicity (1 = Hispanic, 2 = non-Hispanic) RACRECI2 Race

I am trying to upload into R 143 Affymetrix chips onto using R on the NIH Nimbus server. I can load 10 chips without a problem, however, when I try to load 143 I receive a error message: cannot create a vector of 523263 KB. I have expanded the memory of R as follows: R --min-vsize=10M --max-vsize=2500M --min-nsize=10M -max-nsize=50M (as specified in help in R). After running this command the

Dear Group I'm still trying to bring many data into R (see older postings). After solving some troubles with the database I do most of the work in MySQL. But still I could be nice to work on some data using R. Therefore I can use a dedicated Server with Gentoo Linux as OS hosting only R. This Server is a nice machine with two CPU and 4GB RAM which should do the job: Dual Intel XEON 3.06 GHz

hi all i know that one should try and limit the amount of looping in R programs. i have supplied some code below. i am interested in seeing how the code cold be rewritten if we dont use the loops. a brief overview of what is done in the code. ============================================== ============================================== ============================================== 1. the input

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

Dear all, I don't get it: First of all, the help doesn't say what are the memory limits of R. Say, what's the max heap size for instance ???? Secondly, I invoke R with the following commands each time: rgui --vsize 30M --nsize 1000K rgui --vsize 30M --nsize 2000K rgui --vsize 30M --nsize 3000K rgui --vsize 30M --nsize 4000K I try to open a matrix 8000x8000 by issuing

My group is working with datasets between 100 Mb and 1 GB in size, using multiple log ins. From the documentation, it appears that vsize is limited to 2^30-1, which tends to prove too restrictive for our use. When we drop that restriction (set vsize = NA) we end up hanging the server, which requires a restart. Is there any way to increase the memory limits on R while keeping our jobs from

We have a project that calls for the creation of a list of many distribution objects. Distributions can be of various types, with various parameters, but we ran into some problems. I started testing on a simple list of rnorm-based objects. I was a little surprised at the RAM storage requirements, here's an example: N <- 10000 closureList <- vector("list", N) nsize = sample(x

Hi everyone, I have a problem that some people may have already encountered but i did not find the solution yet. As I use R to simulate several arrays of data, my workspace is now 35Mb big and I cannot launch R with it. An "xdr real data read error occured" and R tells me to delete .RData or increase memory. I WON'T delete this file and changing the max-nsize to 40600k did not

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

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

Just wanted to start a discussion on whether R could ship with more appropriate GC parameters. Right now, loading the recommended package Matrix leads to: > library(Matrix) > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 1076796 57.6 1368491 73.1 1198505 64.1 Vcells 1671329 12.8 2685683 20.5 1932418 14.8 Results may vary, but here R needed 64MB of N cells and 15MB

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

Sorry, but I lost this thread, so I sending this as a new message. This is really a follow-up to a post from a couple days ago saying that fisher.test from the ctest library crashed on the following data set: > T [,1] [,2] [1,] 2 1 [2,] 2 1 [3,] 4 0 [4,] 8 0 [5,] 6 0 [6,] 0 0 [7,] 1 0 [8,] 1 1 [9,] 7 1 [10,] 8 2 [11,]

Dear R-users, I am trying to run some simulations in batch mode. In an older version of the program, I used rterm --vsize=100M --nsize=5000K --restore --save <input file> output file, however, in the new version R 2.2.0 , the parameters vsize and nsize are ignored. I can use the command memory.limit to increase memory, but I am not sure if this corresponds to vsize and nsize.

Hi, Is the following command used to increase the memory or any other command when a background R job is run? R --min-vsize=vl --max-vsize=vu --min-nsize=nl --max-nsize=nu --max-ppsize=N source: http://stat.ethz.ch/R-manual/R-patched/library/base/html/Memory.html Thx Carol [[alternative HTML version deleted]]

Let me begin stating that I read all help files and faq's on the subject matter (there aren't more than about a dozen) but either did not find solutions or found them not to work. Here is the issue. I am trying to run a spatial regression on a medium-sized dataset. Part of the functions in the spdep package I use require me to allocate a vector of 1.1 Gb (mine is not a spatial SIG

Full_Name: Viktor Moravetski Version: Version 1.2.0 (2000-12-13) OS: Win-NT 4.0 SP5 Submission from: (NULL) (209.128.81.199) I've started R (v.1.20) with command: rgui --vsize 450M --nsize 40M Then at the command prompt: > gc() used (Mb) gc trigger (Mb) Ncells 358534 9.6 41943040 1120 Vcells 3469306 26.5 58982400 450 >df <- data.frame(x=1:30000,y=2,z=3)