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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 124257 6.7 350000 18.7 350000 18.7 Vcells 124574 1.0 786432 6.0 476934 3.7 > gc() # Just to be sure things have stabilized. used (Mb) gc...

...Gb 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 9.4 Vcells 59921 0.5 786432 6.0 281974 2.2 1.state: let create now a vector of large size -------------------------------------------------- > my.vector<-rnorm(100000*500) > object.size(my.vector)/1024^2 [1] 381.4698 > 100000*500*8...

...eem to solve the problem. Can anyone explain why is this happening, and how to fix it? Thanks, Ronnen. P.S. E-mailed CCs of posted replies would be appreciated. > rm(list=ls(all=TRUE)) > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 143465 3.9 350000 9.4 350000 9.4 Vcells 88573 0.7 50380943 384.4 131023877 999.7 > memory.limit() [1] 1535.875 > n <- 8640 * 4320 > x=rep(1/3, n) > memory.size() [1] 578.8543 > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 143471 3.9...

...cing 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 350000 9.4 350000 9.4 Vcells 81026 0.7 786432 6.0 473127 3.7 > x <- matrix(1, nrow=5000, ncol=5000) > print(gc()) used (Mb) gc trigger (Mb) max used (Mb) Ncells 136793 3.7 350000 9.4 350000 9.4 Vcells 25081043 191.4 27989266 213.6 25081056 191.4 > x[...

...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 124257 6.7 350000 18.7 350000 18.7 >> Vcells 124574 1.0 786432 6.0 47693...

...I tried the following code just to see if I could work with 2 variables but it seems not possible: R : Copyright 2005, The R Foundation for Statistical Computing Version 2.2.1 (2005-12-20 r36812) ISBN 3-900051-07-0 > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 169011 4.6 350000 9.4 350000 9.4 Vcells 62418 0.5 786432 6.0 289957 2.3 > memory.limit(size=4090) NULL > memory.limit() [1] 4288675840 > system.time(a<-matrix(runif(1e6),nrow=1)) [1] 0.28 0.02 2.42 NA NA > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 171344 4.6...

...aries 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 18.7 350000...

...uble, 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 be avoided by...

...ase, it would be faster if I would compute all functions, even if I need only one: myf.all<-function(x){ list(mean=mean(x), max=max(x), sum=sum(x)) } > gc();system.time(for(i in 1:10000)myf.all(1:20)) used (Mb) gc trigger (Mb) max used (Mb) Ncells 165659 4.5 350000 9.4 350000 9.4 Vcells 61135 0.5 786432 6.0 283043 2.2 [1] 0.90 0.00 1.08 NA NA > gc();system.time(for(i in 1:10000)myf(FUN="mean",1:20)) used (Mb) gc trigger (Mb) max used (Mb) Ncells 165659 4.5 350000 9.4 350000 9.4 Vcells 61135 0.5 7864...

Dear All, I would like some advice on creating R packages, passing by reference and oo R. I have created a package that is neither elegant nor extensible and rather cumbersome (it works). I would like to re write the code to make the package distributable (should it be of interest) and easy to maintain. The package is for Bayesian model determination via a reversible jump algorithm and has

...uestions. 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 Vcells 136261 1.1 786432 6.0 573372 4.4 > nn <- 1000000 > ll <- list(xx = rnorm(nn), yy = rnorm(nn)) > tracemem(ll) [1] "<0x1e32c38>" > tracemem(ll$xx) [1] "<0x2af22e144010>" > tracemem(ll$yy) [1] "<0x2af22e8e6...

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 trigger (Mb) max used (Mb) Ncells 121637 3.3 350000 9.4 350000 9.4 Vcells 578615 4.5 1300...

...uge 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 > I increased the memory limit: > memory.limit(3000) NULL > memory.limit() [1] 3000 > memory.size() [1] 11.33070 > memory.size(max=TRUE) [1] 13.4375 > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 209552 5.6...

How do I convert a list to a matrix? --8<---------------cut here---------------start------------->8--- list(c(50000, 101), c(1e+05, 46), c(150000, 31), c(2e+05, 17), c(250000, 19), c(3e+05, 11), c(350000, 12), c(4e+05, 25), c(450000, 19), c(5e+05, 16)) as.matrix(a) [,1] [1,] Numeric,2 [2,] Numeric,2 [3,] Numeric,2 [4,] Numeric,2 [5,] Numeric,2 [6,] Numeric,2 [7,] Numeric,2 [8,] Numeric,2 [9,] Numeric,2 --8<---------------cut here---------------end--------------->8---...

...(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 257820332 1967.1 257565551 1965.1 > Here is the code that I used to fill my memory (nothing fancy): a <- diag(1000) b <-a for (i in 1:1000000) { a<- diag(1000) b <- rbind(b,a) } gc() [[alternative HTML version deleted]]

...he size of an R object exceed the amount of availlable RAM memory? Empirically my system with 4Gb RAM and ample Swap, is failing: > x <- integer(10^9) > object.size(x) 4000000040 bytes > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 121195 6.5 350000 18.7 350000 18.7 Vcells 500124024 3815.7 606849099 4629.9 550124408 4197.2 > matrix(x, ncol=16) Error: cannot allocate vector of size 3.7 Gb I don't understand how this operation violates the limits detailed in the Memory-limit help (above). Thank you! Derek Eder ----------...

...ality test data: ln.Mn.Total..ug.kg D = 0.0869, p-value = 0.002011 OK, next the data column: Mn-Total, ug/kg 460000 400000 510000 600000 770000 180000 210000 1000000 2600000 490000 260000 760000 840000 400000 430000 230000 660000 1200000 370000 230000 290000 320000 400000 660000 620000 1100000 350000 450000 880000 960000 570000 870000 820000 970000 1100000 450000 730000 390000 640000 380000 340000 1400000 870000 260000 430000 290000 290000 550000 540000 240000 470000 650000 390000 380000 410000 220000 400000 380000 500000 1000000 520000 690000 500000 520000 260000 630000 630000 410000 290000 13...

...ality test data: ln.Mn.Total..ug.kg D = 0.0869, p-value = 0.002011 OK, next the data column: Mn-Total, ug/kg 460000 400000 510000 600000 770000 180000 210000 1000000 2600000 490000 260000 760000 840000 400000 430000 230000 660000 1200000 370000 230000 290000 320000 400000 660000 620000 1100000 350000 450000 880000 960000 570000 870000 820000 970000 1100000 450000 730000 390000 640000 380000 340000 1400000 870000 260000 430000 290000 290000 550000 540000 240000 470000 650000 390000 380000 410000 220000 400000 380000 500000 1000000 520000 690000 500000 520000 260000 630000 630000 410000 290000 13...

I have many very large dataframes with 20 columns each. In order to conserve memory, I wish to separate the data frame into 20 vectors, each named the name of the dataframe followed by .1,.2,.3 .20. (For example purposes, one data frame is named ?testa?.) e.g. testa.1, testa.2, testa.3 I have written the code to do this (see below). I am trying to convert this into a function that I can reuse.

Hello, this is probably something silly which I am doing, but I cannot understand why this allocation is not happening. Here is a my C code which tries to allocate a list of size 333559, and then a matrix of size 8*333559 I thought I might be running into memory problems, but R is not even using that much (I start R with more memory and it stays constant) Also, I start R as I normally do and I