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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 trigger (Mb) Ncells 221760 6.0 467875 12.5 Vcells 2420993 18.5 9523397 72.7 > gc()...

...s already a double, the object seems to be copied internally, doubling the memory requirement. See example below. Same for as.character() etc. Is this intended? Example: % R --vanilla > x <- double(1e7) > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 234019 6.3 467875 12.5 350000 9.4 Vcells 10103774 77.1 11476770 87.6 10104223 77.1 > x <- as.double(x) > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 234113 6.3 467875 12.5 350000 9.4 Vcells 10103790 77.1 21354156 163.0 20103818 153.4 However, couldn't this easily...

...o ------------------------------------------------ > dyn.load("crossprod2.so") > cp <- function(a, b) .Call("crossprod2", a, b) > gctorture() > a<-1:10000 > b<-1:1000 > gc() #i used (Mb) gc trigger (Mb) max used (Mb) Ncells 173527 4.7 467875 12.5 350000 9.4 Vcells 108850 0.9 786432 6.0 398019 3.1 > > c<-cp(a,b) > rm(c) > gc() #ii used (Mb) gc trigger (Mb) max used (Mb) Ncells 233998 6.3 467875 12.5 350000 9.4 Vcells 108866 0.9 12089861 92.3 10119856 77.3 > -----------------------------...

...o ------------------------------------------------ > dyn.load("crossprod2.so") > cp <- function(a, b) .Call("crossprod2", a, b) > gctorture() > a<-1:10000 > b<-1:1000 > gc() #i used (Mb) gc trigger (Mb) max used (Mb) Ncells 173527 4.7 467875 12.5 350000 9.4 Vcells 108850 0.9 786432 6.0 398019 3.1 > > c<-cp(a,b) > rm(c) > gc() #ii used (Mb) gc trigger (Mb) max used (Mb) Ncells 233998 6.3 467875 12.5 350000 9.4 Vcells 108866 0.9 12089861 92.3 10119856 77.3 > -----------------------------...

...r=.GlobalEnv)) / 1024^2 [1] 9.829926 N.B.!!! the "max used " is not put back > q() after having restarted R-prozess ------------------------------------- > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 302497 8.1 467875 12.5 350000 9.4 Vcells 785346 6.0 1193335 9.2 923612 7.1 thnks for hint ps: some more understandable information about how R manages the memory and to the output of gc(), specially about gc trigger would be helpful

...164 123 92 69 52 39 29 22 16 [25] 12 9 7 5 ...however, the error depends on the matrix size -- > rsvm_output <- RSVM(x=svm_num_mat[,5000:6000], y=m.cl.f, ladder=laddy[laddy gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 185948 10.0 467875 25.0 467875 25.0 Vcells 758060 5.8 2983420 22.8 2798915 21.4 > ..help? Thanks, -Ken _________________________________________________________________ 08

...m the matrix (* rcorr(matrix)*). During the calculation I get the error "*cannot allocate vector of size 6.7 GB*". When I check the memory allocation of my R session I get the following information *gc() used (Mb) gc trigger (Mb) limit (Mb) max used (Mb) Ncells 249638 13.4 467875 25.0 NA 407500 21.8 Vcells 1499217 11.5 2335949 17.9 7000 1970005 15.1 *Can someone please help me in finding a workaround to the problem. -Regards -- Swaraj Basu PhD Student (Bioinformatics - Functional Genomics) Animal Physiology and Evolution Stazione Zoologica Anton Doh...

...GB and with R 2.2.1 patched I can access only 1GB. Anyone have any suggestions that I can try. My machine has 4GB and I have modified the Boot.ini file. Thanks, Roger Here is the gc() on 2.2.1 patched: > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 252021 6.8 467875 12.5 379294 10.2 Vcells 71097226 542.5 140857919 1074.7 140597245 1072.7 > Here is the gc() output on 2.2.0 after I edited the header: > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 174118 4.7 350000 9.4 350000 9.4 Vcells 130065529 992.4 25...

...001, The R Development Core Team Version 1.4.0 (2001-12-19) n9<-read.table("n90000") Error: cannot allocate vector of size 75 Kb In addition: Warning message: Reached total allocation of 63Mb: see help(memory.size) > gc() used (Mb) gc trigger (Mb) Ncells 206781 5.6 467875 12.5 Vcells 109631 0.9 786432 6.0 On a machine with 512Mb it takes over 10 minutes before running out of memory On Version 1.3.1 (2001-08-31) it works fine date();n9<-read.table("n90000");date();str(n9) [1] "Tue Jan 29 20:41:30 2002" [1] "Tue Jan 29 20:43:29 20...

...gc() unix's top command reports that R has a memory stamp of roughly 2 gig (1.2 on the MacOS box), although R's gc() command reports for this 'empty' instance of R: > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 236823 12.7 467875 25.0 467875 25.0 Vcells 120446 1.0 109363282 834.4 155806232 1188.8 > As I said, if the matrix does not have the dimnames set, the same procedure will produce the same output from R's gc() command, though unix's top command reports that R's mem...

...gc() unix's top command reports that R has a memory stamp of roughly 2 gig (1.2 on the MacOS box), although R's gc() command reports for this 'empty' instance of R: > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 236823 12.7 467875 25.0 467875 25.0 Vcells 120446 1.0 109363282 834.4 155806232 1188.8 > As I said, if the matrix does not have the dimnames set, the same procedure will produce the same output from R's gc() command, though unix's top command reports that R's mem...

...;ls -s lm2.RData") 19324 lm2.RData ## A enormous increase in Vcells; .RData object is now 19Mb+ ###### 3. delete all objects in function call stack > lmtest3 <- lmfunc(add = TRUE, gr = TRUE) > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 210766 5.7 467875 12.5 467875 12.5 Vcells 3615863 27.6 6933688 52.9 6898609 52.7 > save(lmtest3, file = "lm3.RData") > system("ls -s lm3.RData") 320 lm3.RData ## A minimal increase in Vcells; .RData object is now 320Kb > sapply(ls(pattern = "lmtest*"), functio...

...memory limit of 256Mb I'm able to call this function twice before running out of memory. After the allocation fails the GC is called & everything is freed, ie we end up with the same memory as before. Here is an example: > gc() used (Mb) gc trigger (Mb) Ncells 217415 5.9 467875 12.5 Vcells 63668 0.5 786432 6.0 > doit() > gc() used (Mb) gc trigger (Mb) Ncells 342932 9.2 667722 17.9 Vcells 7966401 60.8 14760173 112.7 > doit() > gc() used (Mb) gc trigger (Mb) Ncells 468373 12.6 818163 21.9 Vcells 15869121 121.1 22...

...ithin the boundaries of the RAM. It may be a useful developer tool for big-data problems. ------------------------ R version 2.4.1 (linux): > x <- matrix(as.integer(0), 1e+08, 3) > x <- x + 1 > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 233754 12.5 467875 25 350000 18.7 Vcells 300119431 2289.8 787870506 6011 750119944 5723.0 ------------------------ R version 2.6.0 (linux): > x <- matrix(as.integer(0), 1e+08, 3) > x <- x + 1 > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 137931 7.4 350000 1...

...platform sparc-sun-solaris2.7 arch sparc os solaris2.7 system sparc, solaris2.7 status major 1 minor 6.0 year 2002 month 10 day 01 language R ----------------- At the beginning ------------- --- gc() returns: used (Mb) gc trigger (Mb) Ncells 254150 6.8 467875 12.5 Vcells 408499 3.2 886807 6.8 --- memory.profile() returns: NilSXP SymSXP ListSXP CloSXP EnvSXP PromSXP LangSXP SpecialSXP 1 4919 128880 1440 13 18 63607 59 BUILTINSXP CHARSXP LGLSXP - - INTSXP REALSXP CPLXSXP STRSXP 513 37178 1712 0 0 237...

...ample code: > xx <- matrix(rep(1e+10,1e7),nrow=1e4,ncol=1e3) > tmp.df <- as.data.frame(cbind(xx,xx,xx)) Error: cannot allocate vector of size 228.9 Mb > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 233035 6.3 467875 12.5 350000 9.4 Vcells 10104141 77.1 31854441 243.1 30104289 229.7 4) Used gcc-4.1.2; I have not tried the native compiler. Questions: 1) Are there suggestions on how to diagnose and resolve the memory issue? I'm still building my tool chain and I am in the midst...

...m the matrix (* rcorr(matrix)*). During the calculation I get the error "*cannot allocate vector of size 6.7 GB*". When I check the memory allocation of my R session I get the following information *gc() used (Mb) gc trigger (Mb) limit (Mb) max used (Mb) Ncells 249638 13.4 467875 25.0 NA 407500 21.8 Vcells 1499217 11.5 2335949 17.9 7000 1970005 15.1 *Can someone please help me in finding a workaround to the problem. -Regards -- Swaraj Basu PhD Student (Bioinformatics - Functional Genomics) Animal Physiology and Evolution Stazione Zoologica Anton Dohrn...

Has anyone figured out how to create a destructor in R.oo? How I'd like to use it: I have an object which opens a connection thru RODBC (held as a private member) It would be nice if the connection closes automatically (inside the destructor) when an object gets gc()'ed. Thanks in advance. Regards, Ken BTW, a >BIG< thanks to Henrik Bengtsson for creating the R.oo package! Lucky

I have a loop that processes all the raw data files in agiven directory. It should allocate only the memory to accomodate the filenames list. Each file is loaded into RAM one at a time and saved to another directory after processing. The R script runs fine but it had some memory problems so it was terminated before getting to the end of the list. This is a Windows XP desktop with ~ 1GB RAM In the

...s 17988 The current size of atot is 255404 a.eval.text is: -merge(atot, a10, all=T)- i is: 10 211376 178938 5.7 1.4 407500 786432 10.9 6 362507 786425 9.7 6 The size of object a11 is 17996 The current size of atot is 502540 a.eval.text is: -merge(atot, a11, all=T)- i is: 11 216497 225184 5.8 1.8 467875 889825 12.5 6.8 362507 888747 9.7 6.8 The size of object a12 is 17996 The current size of atot is 1015940 a.eval.text is: -merge(atot, a12, all=T)- i is: 12 226738 322626 6.1 2.5 531268 1577138 14.2 12.1 362507 1569929 9.7 12 The size of object a13 is 17996 The current size of atot is 2082284 a...