similar to: Memory Management under Linux: Problems to allocate large amounts of data

Dear Group, Having a character vector like this one: [1] "03:38:55" "07:42:38" "08:04:27" "08:17:13" "08:41:14" "08:46:58" [7] "08:47:11" "08:53:51" "08:57:51" "08:58:56" I try to do a histogram over times of a day. All I want to know, if my solution is proper or if there is another

Dear List, I'm trying to use R under Windows on a huge database in MySQL via ODBC (technical reasons for this...). Now I want to read tables with some 160.000.000 entries into R. I would be lucky if anyone out there has some good hints what to consider concerning memory management. I'm not sure about the best methods reading such huge files into R. for the moment I spilt the whole

Dear Group, if anyone has experience with the RMySQL Package maybe this behaviour is know: Reading data from a table into R the fields with datatype bigint(20) unsigned are transformed in some way: e.g. the query "select * from orders where userid = 14929859848712890325" selects the correct case but in R the userid is changed to 14929859848712890368. What happened here? This

I have some time series data like 01/02/1990 0.531 0.479 01/03/1990 0.510 0.522 01/06/1990 0.602 0.604 there is no weekends and holidays. how do I graph them in a single plot that the x-axis is the dates and the y-axis is the time series? Thank you Regards, Jincai Jiang (Office) 212-761-3984 -------------------------------------------------------- This is not an offer (or solicitation

Dear List, I have two data.frame of the following form: A: n V1 V2 1 12 0 2 10 8 3 3 8 4 8 4 6 7 3 7 12 0 8 1 0 9 18 0 10 1 0 13 2 0 B: n V1 V2 1 0 2 2 0 3 3 1 9 4 12 8 5 2 9 6 2 9 8 2 0 10 4 1 11 7 1 12 0 1 Now I want to merge those frame to one data.frame with summing up the columns V1 and V2 but not the column n. So the result

In my (limited) experience R is more powerful concerning data manipulation. An example: I have a vector holding a user id. Some user ids can appear more than once. Doing SELECT COUNT(DISTINCT userid) on MySQL will take approx. 15 min. Doing length(unique(userid)) will take (almost) no time... So I think the other way round will serve best: Do everything in R and avoid using SQL on the database...

Dear R users, I have noticed that my R startup is extremely slow. It takes almost 3 minutes from "double-click" to R prompt. I have been running R-0.64.1 till recently and it took about 30 sec. I still have access to R-0.64.1. When I started it up, it took about 25 sec. Can anyone tell me if this is a bug in R or a problem with my machine? Note: This is after bootup with R being the

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

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

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) |

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

I am trying to translate code from S-PLUS to R and R really struggles! After starting R with the foll. R --vsize 50M --nsize 6M --no-restore on a 400 MHz Pentium with 192 MB of memory running Linux (RH 6.2), I run a function that essentially picks up an external dataset with 2121 rows and 30 columns and builds a lm() object and also runs step() ... the step() takes forever to run...(takes very

Martin M has suggested I widen this discussion to R-devel, and > I agree that we should increase them, > but I'm not sure at all about the amount. > > The default could even depend on the architecture (via "./configure").. Views, please. ------------- Begin Forwarded Message ------------- Is is not time we increased the defaults a bit? As the base gets bigger I hit

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]]

G'day R friends, I didn't get any replies on the main list so I thought I'd try with the experts. I was wondering if anyone's ported R to os390. If so, are the vsize and nsize limits the same as other platforms? I could really annoy those SAS guys then. thanks, John Strumila john.strumila@team.telstra.com

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

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

For anybody who uses ESS with R, how do you invoke the vsize and nsize options when you call R. I can't find any appropriate variables from an apropos. Thanks, Jord -- Jordan Howarth CSIRO Mathematical and Information Sciences mailto:jordan.howarth at cmis.csiro.au -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

hi- If I source the following for(k in seq(1:20)){ x<-runif(20000,min=-500,max=2000) y<-runif(20000,min=-500,max=2500) z<-runif(20000,min=-10,max=10) cat(k,"file",memory.size()) cc<-rainbow(11) plot(x,y,asp=1i,xlim=c(-500,2000),ylim=c(-500,2500),main=k,cex=1.0) for(i in seq(-10,10,2)){ points(x[z > i],y[z > i],col=cc[(12+i)/2],cex=1.0) } rm(x,y,z)

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.