search for: rprofmem

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 at...

Hi all, When I run the example in RProfmem, I get: Rprofmem("Rprofmem.out", threshold=1000) example(glm) Rprofmem(NULL) noquote(readLines("Rprofmem.out", n=5)) ... [1] 1384 :5416 :5416 :1064 :1064 :"readRDS" "index.search" "example" [2] 1064 :"readRDS" &quot...

I'm picking up this 5-year old thread. 1. About the four memory allocations without a stacktrace I think the four memory allocations without a stacktrace reported by Rprofmem(): > Rprofmem(); x <- raw(2000); Rprofmem("") > cat(readLines("Rprofmem.out", n=5, warn=FALSE), sep="\n") 192 :360 :360 :1064 :2040 :"raw" are due to some initialization of R that is independent of Rprofmem(), because they can be avoided if one all...

...nce improvement you're looking for is implemented in the latest version of pqR (pqR-2016-10-24, see pqR-project.org), along with corresponding improvements in several other circumstances where unclass(x) does not create a copy of x. Here are some examples (starting with yours), using pqR's Rprofmemt function to get convenient traces of memory allocations: > Rprofmemt(nelem=1000) # trace allocations of vectors with >= 1000 elements > > x <- structure(double(1e6), class = c("foo", "numeric")) RPROFMEM: 8000040 (double 1000000):"double" &qu...

...- ?"Vcells"? (_vector cells_, 8 bytes each) (*Q2:* how are Ncells and Vcells related to small heap/large heap/memory in nodes?) And I guess the question that lead to these other questions is - *Q3:* I'd like to plot out the total amount of memory used over time, and I don't think Rprofmem() give me what I'd like to know because, as I'm understanding it, Rprofmem() records the amount of memory allocated with each call, but this doesn't tell me the total amount of memory R is using, or am I mistaken? Thanks in advance! Joy [[alternative HTML version deleted]]

...g from R 3.3.3 to R 3.4.0 when it comes to comparing an integer 'x' an double 'y' (either may be scalar or vector). For example, in R 3.3.3, I get: > getRversion() [1] '3.3.3' > x <- integer(1000) > y <- double(1000) > profmem::profmem(z <- (x < y)) Rprofmem memory profiling of: z <- (x < y) Memory allocations: bytes calls 1 8040 <internal> 2 4040 <internal> total 12080 > and in R 3.4.0, I get: > getRversion() [1] '3.4.0' > x <- integer(1000) > y <- double(1000) > profmem::profmem(z...

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]]

...(x) : integer overflow - use sum(as.numeric(.)) > y <- matrixStats::sum2(x, mode = "double") > y [1] 2147483648 > str(y) num 2.15e+09 No coercion is taking place, so the memory overhead is zero: > profmem::profmem(y <- matrixStats::sum2(x, mode = "double")) Rprofmem memory profiling of: y <- matrixStats::sum2(x, mode = "double") Memory allocations: bytes calls total 0 /Henrik On Fri, Jun 2, 2017 at 1:58 PM, Henrik Bengtsson <henrik.bengtsson at gmail.com> wrote: > I second this feature request (it's understandable that th...

...0.031 0.049 0.034 0.035 1.452 100 c(a, b, use.names = TRUE) 0.031 0.031 0.055 0.034 0.036 2.094 100 c(a, d, use.names = TRUE) 0.510 0.526 0.588 0.549 0.617 1.998 100 c(c, d, use.names = TRUE) 0.780 0.815 0.886 0.841 0.944 1.430 100 > profmem::profmem(c(c, d, use.names=FALSE)) Rprofmem memory profiling of: c(c, d, use.names = FALSE) Memory allocations: bytes calls 1 80040 <internal> total 80040 > profmem::profmem(c(c, d, use.names=TRUE)) Rprofmem memory profiling of: c(c, d, use.names = TRUE) Memory allocations: bytes calls 1 80040 <...

...04:59.000000000 +0200 +++ R-devel-cov/src/library/utils/NAMESPACE 2014-03-03 16:18:48.407430952 +0100 @@ -1,7 +1,7 @@ # Refer to all C routines by their name prefixed by C_ useDynLib(utils, .registration = TRUE, .fixes = "C_") -export("?", .DollarNames, CRAN.packages, Rprof, Rprofmem, RShowDoc, +export("?", .DollarNames, CRAN.packages, Rcov_start, Rcov_stop, Rprof, Rprofmem, RShowDoc, RSiteSearch, URLdecode, URLencode, View, adist, alarm, apropos, aregexec, argsAnywhere, assignInMyNamespace, assignInNamespace, as.roman, as.person, as.personList...

Dear all, Is there a way we can find the total object.size of all the objects in our R script? The reason we want to do this because we want to know how much memory does our R script require overall. Rprofmem(), doesn't seem to do it. and Unix 'top' command is dynamic and it doesn't give the exact byte size. - Gundala Viswanath Jakarta - Indonesia

...s is not as important of an issue to fix, because anyway linear memory is used to store the data in R. But since the other functions use constant memory, could write.csv also? Is there some copying happening that could be avoided? (this memory measurement uses bench::mark, which in turn uses utils::Rprofmem) https://github.com/tdhock/atime/issues/10 Sincerely, Toby Dylan Hocking [[alternative HTML version deleted]]

...TRUE) 0.031 0.031 0.055 0.034 0.036 2.094 100 >> c(a, d, use.names = TRUE) 0.510 0.526 0.588 0.549 0.617 1.998 100 >> c(c, d, use.names = TRUE) 0.780 0.815 0.886 0.841 0.944 1.430 100 >> >>> profmem::profmem(c(c, d, use.names=FALSE)) >> Rprofmem memory profiling of: >> c(c, d, use.names = FALSE) >> >> Memory allocations: >> bytes calls >> 1 80040 <internal> >> total 80040 >> >>> profmem::profmem(c(c, d, use.names=TRUE)) >> Rprofmem...

...gt; >> y > > [1] 2147483648 > >> str(y) > > num 2.15e+09 > > > No coercion is taking place, so the memory overhead is zero: > > >> profmem::profmem(y <- matrixStats::sum2(x, mode = "double")) > > Rprofmem memory profiling of: > > y <- matrixStats::sum2(x, mode = "double") > > > Memory allocations: > > bytes calls > > total 0 > > > /Henrik > > Thank you, Henrik, for the reminder. > > Back in June, I had ment...

...452 100 > c(a, b, use.names = TRUE) 0.031 0.031 0.055 0.034 0.036 2.094 100 > c(a, d, use.names = TRUE) 0.510 0.526 0.588 0.549 0.617 1.998 100 > c(c, d, use.names = TRUE) 0.780 0.815 0.886 0.841 0.944 1.430 100 > >> profmem::profmem(c(c, d, use.names=FALSE)) > Rprofmem memory profiling of: > c(c, d, use.names = FALSE) > > Memory allocations: > bytes calls > 1 80040 <internal> > total 80040 > >> profmem::profmem(c(c, d, use.names=TRUE)) > Rprofmem memory profiling of: > c(c, d, use.names = TRUE) > > Memor...

...;- matrixStats::sum2(x, mode = "double") >> y > [1] 2147483648 >> str(y) > num 2.15e+09 > No coercion is taking place, so the memory overhead is zero: >> profmem::profmem(y <- matrixStats::sum2(x, mode = "double")) > Rprofmem memory profiling of: > y <- matrixStats::sum2(x, mode = "double") > Memory allocations: > bytes calls > total 0 > /Henrik Thank you, Henrik, for the reminder. Back in June, I had mentioned to Herv? and R-devel that 'logical' should rem...

...ng build error: E:\biocbld\bbs-2.0-bioc\R\src\gnuwin32> make ... ... ---------- Making package utils ------------ adding build stamp to DESCRIPTION installing NAMESPACE file and metadata installing R files Error in namespaceExport(ns, exports) : undefined exports :?, CRAN.packages, Rprof, Rprofmem, RShowDo c, RSiteSearch, URLdecode, URLencode, alarm, apropos, argsAnywhere, assignInNamespace, as.roman, as.p erson, as.personList, available.packages, browseEnv, browseURL, bug.report, capture.output, checkCRAN , chooseCRANmirror, citation, citEntry, citHeader, citFooter, close.socket, combn, com...

Hola: Por lo visto tengo un problema de gestión de la memoria en R con un programa que trabaja con archivos por lotes (no sé si se dice así en castellano, en "batch" mode) para elaborar unos informes, etc. En el conjunto de datos de un año concreto, tengo 197 archivos xml que procesar, de entre 50 y 200Kb la mayoría, con un total de 28 Mb en total. Trabajo con Eclipse como IDE (lo

Hi, I have a long numeric vector 'xx' and I want to use sum() to count the number of elements that satisfy some criteria like non-zero values or values lower than a certain threshold etc... The problem is: sum() returns an NA (with a warning) if the count is greater than 2^31. For example: > xx <- runif(3e9) > sum(xx < 0.9) [1] NA Warning message: In sum(xx

...gt; [1] 2147483648 >> >> str(y) >> > num 2.15e+09 >> >> > No coercion is taking place, so the memory overhead is zero: >> >> >> profmem::profmem(y <- matrixStats::sum2(x, mode = "double")) >> > Rprofmem memory profiling of: >> > y <- matrixStats::sum2(x, mode = "double") >> >> > Memory allocations: >> > bytes calls >> > total 0 >> >> > /Henrik >> >> Thank you, Henrik, for th...