similar to: Some memory questions: data.frame and lists.

Hi, I am running R 2.13.0 on a Windows 7 machine. I ran the script: testInstalledBasic('devel') and received the following warning message: running tests of consistency of as/is.* creating ?isas-tests.R? running code in ?isas-tests.R? comparing ?isas-tests.Rout? to ?isas-tests.Rout.save? ...running tests of random deviate generation -- fails occasionally running code in

Hi, I'm currently in the process of writing an R-installation SOP for my company. As part of that process I'm using the recommendations from the 'R Installation and Administration' document, section 3.2, "Testing an installation". This is done on an XP machine, using the latest binary of 2.11.0. The binary is downloaded and then installed from the installer. I then

The Rprofmem facility is currently enabled only if the configuration option --enable-memory-profiling is used. However, the overhead of having it enabled is negligible when profiling is not actually being done, and can easily be made even smaller. So I think it ought to be enabled all the time. I've attached a patch doing this, which also makes a number of other improvements to Rprofmem,

OBJECTIVE: To update source(..., print.eval=FALSE) to not use withVisible() unless really needed. This avoids unnecessary increases of reference counts/NAMED introduced by withVisible(), which in turn avoids unnecessary memory allocations and garbage collection overhead. This has an impact on all source():ed scripts, e.g. pre-allocation of large matrices to save memory does *not always* help in

Hi All, i have a problem in understanding what the assignment operator '<-' really is doing. If i create two numeric arrays in R and copy one into the other with '<-' and afterwards change one array by calling a C function, both arrays are changed! The problem I am facing can easily be seen in the following example: (The following R code and the C function is attached and

Hi, I've noticed that as.vector() always allocates a new object, e.g. > x <- 1:10; > x <- as.vector(x); > tracemem(x); [1] "<0x0000000005622db8" > x <- as.vector(x); tracemem[0x0000000005622db8 -> 0x0000000005622ec0]: as.vector > x <- as.vector(x); tracemem[0x0000000005622ec0 -> 0x0000000005622f18]: as.vector > x <- as.vector(x);

On Fri, 5 Aug 2016, Winston Chang wrote: > My understanding is that R will not make copies of lists if there is > only one reference to the object. However, I've encountered a case > where R does make copies, even though (I think) there should be only > one reference to the object. I hope that someone could shed some light > on why this is happening. > > I'll start

Hi all, I've been trying to get a better handle on what manipulations lead R to duplicate a vector, creating small experiments and using tracemem to observe what happens (all in 2.15.1). That's lead me to a few questions, illustrated using the snippet below. x <- 1:10 tracemem(x) # [1] "<0x1058f8238>" x[5] <- 5 # tracemem[0x1058f8238 -> 0x105994ab0]: x[11] <-

My understanding is that R will not make copies of lists if there is only one reference to the object. However, I've encountered a case where R does make copies, even though (I think) there should be only one reference to the object. I hope that someone could shed some light on why this is happening. I'll start with a simple example. Below, x is a list with one element, and changing that

Hi, $ R --vanilla R version 2.14.1 (2011-12-22) Platform: i686-pc-linux-gnu (32-bit) > DF = data.frame(a=1:3,b=4:6) > DF a b 1 1 4 2 2 5 3 3 6 > tracemem(DF) [1] "<0x8898098>" > names(DF)[2]="B" tracemem[0x8898098 -> 0x8763e18]: tracemem[0x8763e18 -> 0x8766be8]: tracemem[0x8766be8 -> 0x8766b68]: > DF a B 1 1 4 2 2 5 3 3 6 > Are those 3

Hi Lille, Is it possible you're looking for tracemem() or inspect() ? > x <- data.frame(z = 1:10)> tracemem(x)[1] "<0x55aa743e0bc0>" > x[1] <- 2Ltracemem[0x55aa743e0bc0 -> 0x55aa778f6ad0]: tracemem[0x55aa778f6ad0 -> 0x55aa778f6868]: [<-.data.frame [<- tracemem[0x55aa778f6868 -> 0x55aa778f5b48]: [<-.data.frame [<- >

Is putting a variable into a list a deep copy (and is tracemem the correct way to confirm)? warmstrong at krypton:~/dvl/R.packages$ R > x <- rnorm(1000) > tracemem(x) [1] "<0x3214c90>" > x.list <- list(x.in.list=x) tracemem[0x3214c90 -> 0x2af0a20]: > Is it possible to put a variable into a list without causing a deep copy (i.e. if you _really_ want the

I was trying to use tracemem to look at mblk contents. First, I tried to use mblk->b_wptr - mblk->b_rptr as the size, and was told that it had to be a constant. Foo. (RFE #1). Then, I tried to use 8 as the size, and kept getting decimal numbers printed. Stumbled on #pragma D option rawbytes=true (is the =true necessary, btw?) and that didn''t help. Then, in desperation, I

Hi Expert I want to use dtrace to monitor the content change of one file. I made following scripts, #!/usr/sbin/dtrace -s inline int MYPID = $1; syscall::write:entry /pid == MYPID/ { tracemem(arg1, arg2); printf("\n"); } It always has an following error bash-3.00$ sudo dumpFIFO.dtrace 3836 dtrace: failed to compile script ./dumpFIFO.dtrace: line 19: tracemem( ) argument #2

N_conreq:entry { self->x=1; calledaddr=(struct xaddrf *)arg3; callingaddr=(struct xaddrf *)arg4; trace(calledaddr->link_id); tracemem(calledaddr->DTE_MAC.lsap_add, 80); trace(callingaddr->link_id); tracemem(callingaddr->DTE_MAC.lsap_add, 80); } 0 -> N_conreq 255

Hi, I am using tracemem() to dump some memory contents. When the contents of the memory contain a mix of binary and ascii, the output looks like: 0 1 2 3 4 5 6 7 8 9 a b c d e f 0123456789abcdef 0: 2f 79 2e 20 2e 9e 2e fc fe 2e 2e 38 2e 0a 34 38 /y. .......8..48 10: 34 32 35 2c 20 72 65 6d 6f 74 65 20 69 70 3a 20 425,

I'm interested in playing around with memory profiling in R-devel (as described at http://developer.r-project.org/memory-profiling.html) and was trying to figure out how to compile R-devel so that I can use the 'tracemem()' function. But I can't figure out how/where to set R_MEMORY_PROFILING. Is it on the configure command line? Thanks for any help, -roger -- Roger D. Peng

A number of as.data.frame methods do names(x) <- NULL Replacing that with if(!is.null(names(x))) names(x) <- NULL appears to save making one copy of the data (based on tracemem and Rprofmem in a copy of R compiled with --enable-memory-profiling) and gives a modest but consistent boost in speed, e.g.: # old new # user system

Dear R-devel, I have a class 'myClass' in R that is essentially a list with pre-specified structure. It has an assignment operator which is going to do some things and then should assign the value using the regular list assignment operator `$<-.myClass`<-function(x,i,value){ # do some pre-processing stuff # make the assignment using the default list assignment

Hi all, Where can I find an R binary version (>2.4.0 ) for windows that compiled with R_MEMORY_PROFILING? Within our application we are experiencing serious problems with memory usage. And being able to use "Rprofmem" and "tracemem" command seems like our best option. Thanks, Yoni [[alternative HTML version deleted]]