Re: [R] Windows Memory Issues
On Wed, 10 Dec 2003 10:43:12 -0500, "JFRI (Jesper Frickmann)" <[EMAIL PROTECTED]> wrote : >I recommend you get the latest version 1.8.1 beta. I also had some >memory problems and that fixed it. 1.8.1 has been released, so there's no more beta. The release is available on CRAN (see http://cran.r-project.org/bin/windows/base for the Windows binary build). A patched version, occasionally updated on my web site (binary occasionally updated as http://www.stats.uwo.ca/faculty/murdoch/software/r-devel/rw1081pat.exe) is also worth looking at if the release still has the bug. Duncan Murdoch __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
RE: [R] Windows Memory Issues
I recommend you get the latest version 1.8.1 beta. I also had some memory problems and that fixed it. Kind regards, Jesper Frickmann Statistician, Quality Control Novozymes North America Inc. Tel. +1 919 494 3266 Fax +1 919 494 3460 __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
RE: [R] Windows Memory Issues
On Tue, 9 Dec 2003, Thomas Lumley wrote: > On Tue, 9 Dec 2003 [EMAIL PROTECTED] wrote: > > > Thanks for the reply. So are you saying that multiple calls to gc() frees > > up memory to Windows and then other processes can use that newly freed > > memory? > > No. You typically can't free memory back to Windows (or many other OSes). At least using R under Windows NT/2000/XP you can. I've watched it do so whilst fixing memory leaks. There is another complication here: R for Windows uses a third-party malloc, and you can free memory back to that if not to the OS. The reason Windows is special is the issue of fragmentation, which OSes using mmap (and R-devel under Windows) typically do not suffer. -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UKFax: +44 1865 272595 __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
RE: [R] Windows Memory Issues
On Tue, 9 Dec 2003 [EMAIL PROTECTED] wrote: > Thanks for the reply. So are you saying that multiple calls to gc() frees > up memory to Windows and then other processes can use that newly freed > memory? So multiple calls to gc() does not actually make more memory That is what I said. Why do people expect me to repeat myself? > available to new R objects that I might create. -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UKFax: +44 1865 272595 __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
RE: [R] Windows Memory Issues
On Tue, 9 Dec 2003 [EMAIL PROTECTED] wrote: > Thanks for the reply. So are you saying that multiple calls to gc() frees > up memory to Windows and then other processes can use that newly freed > memory? No. You typically can't free memory back to Windows (or many other OSes). >So multiple calls to gc() does not actually make more memory > available to new R objects that I might create. Yes and no. It makes more memory available, but only memory that would have been made available in any case if you had tried to use it. R calls the garbage collector before requesting more memory from the operating system and before running out of memory. > The reason I ask is because > I want to know how to use all the available memory that I can to store > object in R. ?gc says that garbage collection is run without user > intervention so there is really nothing I can do to improve memory under > Windows except increase the --max-mem-size at startup You can't do anything else to make more memory available, only to use less. -thomas __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
RE: [R] Windows Memory Issues
Thanks for the reply. So are you saying that multiple calls to gc() frees up memory to Windows and then other processes can use that newly freed memory? So multiple calls to gc() does not actually make more memory available to new R objects that I might create. The reason I ask is because I want to know how to use all the available memory that I can to store object in R. ?gc says that garbage collection is run without user intervention so there is really nothing I can do to improve memory under Windows except increase the --max-mem-size at startup (which is limited to 1.7GB under the current version of R for Windows and will be greater ~3GB for R 1.9). Thanks again. Ben Stabler >-Original Message- >From: Prof Brian Ripley [mailto:[EMAIL PROTECTED] >Sent: Tuesday, December 09, 2003 9:29 AM >To: STABLER Benjamin >Cc: [EMAIL PROTECTED] >Subject: Re: [R] Windows Memory Issues > > >On Tue, 9 Dec 2003 [EMAIL PROTECTED] wrote: > >> I would also like some clarification about R memory >management. Like Doug, >> I didn't find anything about consecutive calls to gc() to >free more memory. > >It was a statement about Windows, and about freeing memory *to >Windows*. >Douglas Grove apparently had misread both the subject line and the >sentence. > >> We run into memory limit problems every now and then and a better >> understanding of R's memory management would go a long way. >I am interested >> in learning more and was wondering if there is any specific >R documentation >> that explains R's memory usage? Or maybe some good links >about memory and >> garbage collection. Thanks. > >There are lots of comments in the source files. And as I already said >(but has been excised below), this is not relevant to the next >version of >R anyway. > >BTW, the message below has been selectively edited, so please >consult the >original. > >> Message: 21 >> Date: Mon, 8 Dec 2003 09:51:12 -0800 (PST) >> From: Douglas Grove <[EMAIL PROTECTED]> >> Subject: Re: [R] Windows Memory Issues >> To: Prof Brian Ripley <[EMAIL PROTECTED]> >> Cc: [EMAIL PROTECTED] >> Message-ID: >> <[EMAIL PROTECTED]> >> Content-Type: TEXT/PLAIN; charset=US-ASCII >> >> On Sat, 6 Dec 2003, Prof Brian Ripley wrote: >> >> > I think you misunderstand how R uses memory. gc() does >not free up all >> > the memory used for the objects it frees, and repeated >calls will free >> > more. Don't speculate about how memory management works: do your >> > homework! >> >> Are you saying that consecutive calls to gc() will free more >memory than >> a single call, or am I misunderstanding? Reading ?gc and >?Memory I don't >> see anything about this mentioned. Where should I be >looking to find >> more comprehensive info on R's memory management?? I'm not >writing any >> packages, just would like to have a better handle on >efficiently using >> memory as it is usually the limiting factor with R. FYI, I'm running >> R1.8.1 and RedHat9 on a P4 with 2GB of RAM in case there is >any platform >> specific info that may be applicable. >> >> Thanks, >> >> Doug Grove >> Statistical Research Associate >> Fred Hutchinson Cancer Research Center >> >> >> > In any case, you are using an outdated version of R, and your first >> > course of action should be to compile up R-devel and try >that, as there >> > has been improvements to memory management under Windows. >You could also >> > try compiling using the native malloc (and that *is* >described in the >> > INSTALL file) as that has different compromises. >> > >> > >> > On Sat, 6 Dec 2003, Richard Pugh wrote: >> > >> > > Hi all, >> > > >> > > I am currently building an application based on R 1.7.1 >(+ compiled >> > > C/C++ code + MySql + VB). I am building this >application to work on 2 >> > > different platforms (Windows XP Professional (500mb >memory) and Windows >> > > NT 4.0 with service pack 6 (1gb memory)). This is a very memory >> > > intensive application performing sophisticated >operations on "large" >> > > matrices (typically 5000x1500 matrices). >> > > >> > > I have run into some issues regarding the way R handles >its memory, >> > > especially on NT. In particular, R does not seem able >to recollect some >> > > of the memory used following the creation and >manipulatio
RE: [R] Windows Memory Issues
> [snipped] Or maybe some good links > about memory and > garbage collection. As is mentioned time-to-time on this list when the above subject comes up, Windows memory is a complicated topic. One open-source utility I have found helpful to monitor memory when I work under XP is called RAMpage, authored by John Fitzgibbon, and is available at http://www.jfitz.com/software/RAMpage/ In its FAQ / Help, it touches on a lot of general memory and resource issues, which I found helpful to learn about. http://www.jfitz.com/software/RAMpage/RAMpage_FAQS.html (Though the author clearly warns that its usefulness for "freeing memory" may not be anymore than cosmetic on NT / 2000 / XP systems.) Hope that helps. Bill Bill Pikounis, Ph.D. Biometrics Research Department Merck Research Laboratories PO Box 2000, MailDrop RY33-300 126 E. Lincoln Avenue Rahway, New Jersey 07065-0900 USA Phone: 732 594 3913 Fax: 732 594 1565 > -Original Message- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of > [EMAIL PROTECTED] > Sent: Tuesday, December 09, 2003 12:09 PM > To: [EMAIL PROTECTED] > Subject: Re: [R] Windows Memory Issues > > > I would also like some clarification about R memory > management. Like Doug, > I didn't find anything about consecutive calls to gc() to > free more memory. > We run into memory limit problems every now and then and a better > understanding of R's memory management would go a long way. > I am interested > in learning more and was wondering if there is any specific R > documentation > that explains R's memory usage? Or maybe some good links > about memory and > garbage collection. Thanks. > > Benjamin Stabler > Transportation Planning Analysis Unit > Oregon Department of Transportation > 555 13th Street NE, Suite 2 > Salem, OR 97301 Ph: 503-986-4104 > > ------- > > Message: 21 > Date: Mon, 8 Dec 2003 09:51:12 -0800 (PST) > From: Douglas Grove <[EMAIL PROTECTED]> > Subject: Re: [R] Windows Memory Issues > To: Prof Brian Ripley <[EMAIL PROTECTED]> > Cc: [EMAIL PROTECTED] > Message-ID: > <[EMAIL PROTECTED]> > Content-Type: TEXT/PLAIN; charset=US-ASCII > > On Sat, 6 Dec 2003, Prof Brian Ripley wrote: > > > I think you misunderstand how R uses memory. gc() does not > free up all > > the memory used for the objects it frees, and repeated > calls will free > > more. Don't speculate about how memory management works: do your > > homework! > > Are you saying that consecutive calls to gc() will free more > memory than > a single call, or am I misunderstanding? Reading ?gc and > ?Memory I don't > see anything about this mentioned. Where should I be looking to find > more comprehensive info on R's memory management?? I'm not > writing any > packages, just would like to have a better handle on efficiently using > memory as it is usually the limiting factor with R. FYI, I'm running > R1.8.1 and RedHat9 on a P4 with 2GB of RAM in case there is > any platform > specific info that may be applicable. > > Thanks, > > Doug Grove > Statistical Research Associate > Fred Hutchinson Cancer Research Center > > > > In any case, you are using an outdated version of R, and your first > > course of action should be to compile up R-devel and try > that, as there > > has been improvements to memory management under Windows. > You could also > > try compiling using the native malloc (and that *is* > described in the > > INSTALL file) as that has different compromises. > > > > > > On Sat, 6 Dec 2003, Richard Pugh wrote: > > > > > Hi all, > > > > > > I am currently building an application based on R 1.7.1 > (+ compiled > > > C/C++ code + MySql + VB). I am building this application > to work on 2 > > > different platforms (Windows XP Professional (500mb > memory) and Windows > > > NT 4.0 with service pack 6 (1gb memory)). This is a very memory > > > intensive application performing sophisticated operations > on "large" > > > matrices (typically 5000x1500 matrices). > > > > > > I have run into some issues regarding the way R handles > its memory, > > > especially on NT. In particular, R does not seem able to > recollect some > > > of the memory used following the creation and > manipulation of large data > > > objects. For example, I have a function which receives a (large) > > > numeric matrix, matches against more data (mayb
Re: [R] Windows Memory Issues
On Tue, 9 Dec 2003 [EMAIL PROTECTED] wrote: > I would also like some clarification about R memory management. Like Doug, > I didn't find anything about consecutive calls to gc() to free more memory. It was a statement about Windows, and about freeing memory *to Windows*. Douglas Grove apparently had misread both the subject line and the sentence. > We run into memory limit problems every now and then and a better > understanding of R's memory management would go a long way. I am interested > in learning more and was wondering if there is any specific R documentation > that explains R's memory usage? Or maybe some good links about memory and > garbage collection. Thanks. There are lots of comments in the source files. And as I already said (but has been excised below), this is not relevant to the next version of R anyway. BTW, the message below has been selectively edited, so please consult the original. > Message: 21 > Date: Mon, 8 Dec 2003 09:51:12 -0800 (PST) > From: Douglas Grove <[EMAIL PROTECTED]> > Subject: Re: [R] Windows Memory Issues > To: Prof Brian Ripley <[EMAIL PROTECTED]> > Cc: [EMAIL PROTECTED] > Message-ID: > <[EMAIL PROTECTED]> > Content-Type: TEXT/PLAIN; charset=US-ASCII > > On Sat, 6 Dec 2003, Prof Brian Ripley wrote: > > > I think you misunderstand how R uses memory. gc() does not free up all > > the memory used for the objects it frees, and repeated calls will free > > more. Don't speculate about how memory management works: do your > > homework! > > Are you saying that consecutive calls to gc() will free more memory than > a single call, or am I misunderstanding? Reading ?gc and ?Memory I don't > see anything about this mentioned. Where should I be looking to find > more comprehensive info on R's memory management?? I'm not writing any > packages, just would like to have a better handle on efficiently using > memory as it is usually the limiting factor with R. FYI, I'm running > R1.8.1 and RedHat9 on a P4 with 2GB of RAM in case there is any platform > specific info that may be applicable. > > Thanks, > > Doug Grove > Statistical Research Associate > Fred Hutchinson Cancer Research Center > > > > In any case, you are using an outdated version of R, and your first > > course of action should be to compile up R-devel and try that, as there > > has been improvements to memory management under Windows. You could also > > try compiling using the native malloc (and that *is* described in the > > INSTALL file) as that has different compromises. > > > > > > On Sat, 6 Dec 2003, Richard Pugh wrote: > > > > > Hi all, > > > > > > I am currently building an application based on R 1.7.1 (+ compiled > > > C/C++ code + MySql + VB). I am building this application to work on 2 > > > different platforms (Windows XP Professional (500mb memory) and Windows > > > NT 4.0 with service pack 6 (1gb memory)). This is a very memory > > > intensive application performing sophisticated operations on "large" > > > matrices (typically 5000x1500 matrices). > > > > > > I have run into some issues regarding the way R handles its memory, > > > especially on NT. In particular, R does not seem able to recollect some > > > of the memory used following the creation and manipulation of large data > > > objects. For example, I have a function which receives a (large) > > > numeric matrix, matches against more data (maybe imported from MySql) > > > and returns a large list structure for further analysis. A typical call > > > may look like this . > > > > > > > myInputData <- matrix(sample(1:100, 750, T), nrow=5000) > > > > myPortfolio <- createPortfolio(myInputData) > > > > > > It seems I can only repeat this code process 2/3 times before I have to > > > restart R (to get the memory back). I use the same object names > > > (myInputData and myPortfolio) each time, so I am not create more large > > > objects .. > > > > > > I think the problems I have are illustrated with the following example > > > from a small R session . > > > > > > > # Memory usage for Rui process = 19,800 > > > > testData <- matrix(rnorm(1000), 1000) # Create big matrix > > > > # Memory usage for Rgui process = 254,550k > > > > rm(testData) > > > > # Memory usage for Rgui process = 254,550k > > > > gc() > > > used (Mb) gc trigger (Mb) > > > Ncells 369277 9.9 667
Re: [R] Windows Memory Issues
I would also like some clarification about R memory management. Like Doug, I didn't find anything about consecutive calls to gc() to free more memory. We run into memory limit problems every now and then and a better understanding of R's memory management would go a long way. I am interested in learning more and was wondering if there is any specific R documentation that explains R's memory usage? Or maybe some good links about memory and garbage collection. Thanks. Benjamin Stabler Transportation Planning Analysis Unit Oregon Department of Transportation 555 13th Street NE, Suite 2 Salem, OR 97301 Ph: 503-986-4104 --- Message: 21 Date: Mon, 8 Dec 2003 09:51:12 -0800 (PST) From: Douglas Grove <[EMAIL PROTECTED]> Subject: Re: [R] Windows Memory Issues To: Prof Brian Ripley <[EMAIL PROTECTED]> Cc: [EMAIL PROTECTED] Message-ID: <[EMAIL PROTECTED]> Content-Type: TEXT/PLAIN; charset=US-ASCII On Sat, 6 Dec 2003, Prof Brian Ripley wrote: > I think you misunderstand how R uses memory. gc() does not free up all > the memory used for the objects it frees, and repeated calls will free > more. Don't speculate about how memory management works: do your > homework! Are you saying that consecutive calls to gc() will free more memory than a single call, or am I misunderstanding? Reading ?gc and ?Memory I don't see anything about this mentioned. Where should I be looking to find more comprehensive info on R's memory management?? I'm not writing any packages, just would like to have a better handle on efficiently using memory as it is usually the limiting factor with R. FYI, I'm running R1.8.1 and RedHat9 on a P4 with 2GB of RAM in case there is any platform specific info that may be applicable. Thanks, Doug Grove Statistical Research Associate Fred Hutchinson Cancer Research Center > In any case, you are using an outdated version of R, and your first > course of action should be to compile up R-devel and try that, as there > has been improvements to memory management under Windows. You could also > try compiling using the native malloc (and that *is* described in the > INSTALL file) as that has different compromises. > > > On Sat, 6 Dec 2003, Richard Pugh wrote: > > > Hi all, > > > > I am currently building an application based on R 1.7.1 (+ compiled > > C/C++ code + MySql + VB). I am building this application to work on 2 > > different platforms (Windows XP Professional (500mb memory) and Windows > > NT 4.0 with service pack 6 (1gb memory)). This is a very memory > > intensive application performing sophisticated operations on "large" > > matrices (typically 5000x1500 matrices). > > > > I have run into some issues regarding the way R handles its memory, > > especially on NT. In particular, R does not seem able to recollect some > > of the memory used following the creation and manipulation of large data > > objects. For example, I have a function which receives a (large) > > numeric matrix, matches against more data (maybe imported from MySql) > > and returns a large list structure for further analysis. A typical call > > may look like this . > > > > > myInputData <- matrix(sample(1:100, 750, T), nrow=5000) > > > myPortfolio <- createPortfolio(myInputData) > > > > It seems I can only repeat this code process 2/3 times before I have to > > restart R (to get the memory back). I use the same object names > > (myInputData and myPortfolio) each time, so I am not create more large > > objects .. > > > > I think the problems I have are illustrated with the following example > > from a small R session . > > > > > # Memory usage for Rui process = 19,800 > > > testData <- matrix(rnorm(1000), 1000) # Create big matrix > > > # Memory usage for Rgui process = 254,550k > > > rm(testData) > > > # Memory usage for Rgui process = 254,550k > > > gc() > > used (Mb) gc trigger (Mb) > > Ncells 369277 9.9 667722 17.9 > > Vcells 87650 0.7 24286664 185.3 > > > # Memory usage for Rgui process = 20,200k > > > > In the above code, R cannot recollect all memory used, so the memory > > usage increases from 19.8k to 20.2. However, the following example is > > more typical of the environments I use . > > > > > # Memory 128,100k > > > myTestData <- matrix(rnorm(1000), 1000) > > > # Memory 357,272k > > > rm(myTestData) > > > # Memory 357,272k > > > gc() > > used (Mb) gc trigger (Mb) > >
Re: [R] Windows Memory Issues
On Sat, 6 Dec 2003, Prof Brian Ripley wrote: > I think you misunderstand how R uses memory. gc() does not free up all > the memory used for the objects it frees, and repeated calls will free > more. Don't speculate about how memory management works: do your > homework! Are you saying that consecutive calls to gc() will free more memory than a single call, or am I misunderstanding? Reading ?gc and ?Memory I don't see anything about this mentioned. Where should I be looking to find more comprehensive info on R's memory management?? I'm not writing any packages, just would like to have a better handle on efficiently using memory as it is usually the limiting factor with R. FYI, I'm running R1.8.1 and RedHat9 on a P4 with 2GB of RAM in case there is any platform specific info that may be applicable. Thanks, Doug Grove Statistical Research Associate Fred Hutchinson Cancer Research Center > In any case, you are using an outdated version of R, and your first > course of action should be to compile up R-devel and try that, as there > has been improvements to memory management under Windows. You could also > try compiling using the native malloc (and that *is* described in the > INSTALL file) as that has different compromises. > > > On Sat, 6 Dec 2003, Richard Pugh wrote: > > > Hi all, > > > > I am currently building an application based on R 1.7.1 (+ compiled > > C/C++ code + MySql + VB). I am building this application to work on 2 > > different platforms (Windows XP Professional (500mb memory) and Windows > > NT 4.0 with service pack 6 (1gb memory)). This is a very memory > > intensive application performing sophisticated operations on "large" > > matrices (typically 5000x1500 matrices). > > > > I have run into some issues regarding the way R handles its memory, > > especially on NT. In particular, R does not seem able to recollect some > > of the memory used following the creation and manipulation of large data > > objects. For example, I have a function which receives a (large) > > numeric matrix, matches against more data (maybe imported from MySql) > > and returns a large list structure for further analysis. A typical call > > may look like this . > > > > > myInputData <- matrix(sample(1:100, 750, T), nrow=5000) > > > myPortfolio <- createPortfolio(myInputData) > > > > It seems I can only repeat this code process 2/3 times before I have to > > restart R (to get the memory back). I use the same object names > > (myInputData and myPortfolio) each time, so I am not create more large > > objects .. > > > > I think the problems I have are illustrated with the following example > > from a small R session . > > > > > # Memory usage for Rui process = 19,800 > > > testData <- matrix(rnorm(1000), 1000) # Create big matrix > > > # Memory usage for Rgui process = 254,550k > > > rm(testData) > > > # Memory usage for Rgui process = 254,550k > > > gc() > > used (Mb) gc trigger (Mb) > > Ncells 369277 9.9 667722 17.9 > > Vcells 87650 0.7 24286664 185.3 > > > # Memory usage for Rgui process = 20,200k > > > > In the above code, R cannot recollect all memory used, so the memory > > usage increases from 19.8k to 20.2. However, the following example is > > more typical of the environments I use . > > > > > # Memory 128,100k > > > myTestData <- matrix(rnorm(1000), 1000) > > > # Memory 357,272k > > > rm(myTestData) > > > # Memory 357,272k > > > gc() > > used (Mb) gc trigger (Mb) > > Ncells 478197 12.8 818163 21.9 > > Vcells 9309525 71.1 31670210 241.7 > > > # Memory 279,152k > > > > Here, the memory usage increases from 128.1k to 279.1k > > > > Could anyone point out what I could do to rectify this (if anything), or > > generally what strategy I could take to improve this? > > > > Many thanks, > > Rich. > > > > Mango Solutions > > Tel : (01628) 418134 > > Mob : (07967) 808091 > > > > > > [[alternative HTML version deleted]] > > > > __ > > [EMAIL PROTECTED] mailing list > > https://www.stat.math.ethz.ch/mailman/listinfo/r-help > > > > > > -- > Brian D. Ripley, [EMAIL PROTECTED] > Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ > University of Oxford, Tel: +44 1865 272861 (self) > 1 South Parks Road, +44 1865 272866 (PA) > Oxford OX1 3TG, UKFax: +44 1865 272595 > > __ > [EMAIL PROTECTED] mailing list > https://www.stat.math.ethz.ch/mailman/listinfo/r-help > __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] Windows Memory Issues
Richard Pugh wrote: ... I have run into some issues regarding the way R handles its memory, especially on NT. ... Actually, you've run into NT's nasty memory management. Welcome! :) R-core have worked very hard to work around Windows memory issues, so they've probably got a better answer than I can give. I'll give you a few quick answers, and then wait for correction when one them replies. A typical call may look like this . myInputData <- matrix(sample(1:100, 750, T), nrow=5000) myPortfolio <- createPortfolio(myInputData) It seems I can only repeat this code process 2/3 times before I have to restart R (to get the memory back). I use the same object names (myInputData and myPortfolio) each time, so I am not create more large objects .. Actually, you do. Re-using a name does not re-use the same blocks of memory. The size of the object may change, for example. I think the problems I have are illustrated with the following example from a small R session . # Memory usage for Rui process = 19,800 testData <- matrix(rnorm(1000), 1000) # Create big matrix # Memory usage for Rgui process = 254,550k rm(testData) # Memory usage for Rgui process = 254,550k gc() used (Mb) gc trigger (Mb) Ncells 369277 9.9 667722 17.9 Vcells 87650 0.7 24286664 185.3 # Memory usage for Rgui process = 20,200k In the above code, R cannot recollect all memory used, so the memory usage increases from 19.8k to 20.2. However, the following example is more typical of the environments I use . # Memory 128,100k myTestData <- matrix(rnorm(1000), 1000) # Memory 357,272k rm(myTestData) # Memory 357,272k gc() used (Mb) gc trigger (Mb) Ncells 478197 12.8 818163 21.9 Vcells 9309525 71.1 31670210 241.7 # Memory 279,152k R can return memory to Windows, but it cannot *make* Windows take it back. Exiting the app is the only guaranteed way to do this, for any application. The fact that you get this with matricies makes me suspect fragmentation issues with memory, rather than pure lack of memory. Here, the memory is disorganised, thanks to some programmers in Redmond. When a matrix gets assigned, it needs all its memory to be contiguous. If the memory on your machine has, say, 250 MB free, but only in 1 MB chunks, and you need to build a 2 MB matrix, you're out of luck. From the sounds of your calculations, they *must* be done as big matricies (true?). If not, try a data structure that isn't a matrix or array; these require *contiguous* blocks of memory. Lists, by comparison, can store their components in separate blocks. Would a list of smaller matricies work? Could anyone point out what I could do to rectify this (if anything), or generally what strategy I could take to improve this? Some suggestions: 1) call gc() somewhere inside your routines regularly. Not guaranteed to help, but worth a try. 2) Get even more RAM, and hope it stabilises. 3) Change data structures to something other than one huge matrix. Matricies have huge computational advantages, but are pigs for memory. 4) Export the data crunching part of the application to an operating system that isn't notorious for bad memory management. I've almost never had anguish from Solaris. Linux and FreeBSD are not bad. Have you considered running the results on a different machine, and storing the results in a fresh table on the same database as where you get the raw data? Hope that helps. Jason -- Indigo Industrial Controls Ltd. http://www.indigoindustrial.co.nz 64-21-343-545 [EMAIL PROTECTED] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] Windows Memory Issues
I think you misunderstand how R uses memory. gc() does not free up all the memory used for the objects it frees, and repeated calls will free more. Don't speculate about how memory management works: do your homework! In any case, you are using an outdated version of R, and your first course of action should be to compile up R-devel and try that, as there has been improvements to memory management under Windows. You could also try compiling using the native malloc (and that *is* described in the INSTALL file) as that has different compromises. On Sat, 6 Dec 2003, Richard Pugh wrote: > Hi all, > > I am currently building an application based on R 1.7.1 (+ compiled > C/C++ code + MySql + VB). I am building this application to work on 2 > different platforms (Windows XP Professional (500mb memory) and Windows > NT 4.0 with service pack 6 (1gb memory)). This is a very memory > intensive application performing sophisticated operations on "large" > matrices (typically 5000x1500 matrices). > > I have run into some issues regarding the way R handles its memory, > especially on NT. In particular, R does not seem able to recollect some > of the memory used following the creation and manipulation of large data > objects. For example, I have a function which receives a (large) > numeric matrix, matches against more data (maybe imported from MySql) > and returns a large list structure for further analysis. A typical call > may look like this . > > > myInputData <- matrix(sample(1:100, 750, T), nrow=5000) > > myPortfolio <- createPortfolio(myInputData) > > It seems I can only repeat this code process 2/3 times before I have to > restart R (to get the memory back). I use the same object names > (myInputData and myPortfolio) each time, so I am not create more large > objects .. > > I think the problems I have are illustrated with the following example > from a small R session . > > > # Memory usage for Rui process = 19,800 > > testData <- matrix(rnorm(1000), 1000) # Create big matrix > > # Memory usage for Rgui process = 254,550k > > rm(testData) > > # Memory usage for Rgui process = 254,550k > > gc() > used (Mb) gc trigger (Mb) > Ncells 369277 9.9 667722 17.9 > Vcells 87650 0.7 24286664 185.3 > > # Memory usage for Rgui process = 20,200k > > In the above code, R cannot recollect all memory used, so the memory > usage increases from 19.8k to 20.2. However, the following example is > more typical of the environments I use . > > > # Memory 128,100k > > myTestData <- matrix(rnorm(1000), 1000) > > # Memory 357,272k > > rm(myTestData) > > # Memory 357,272k > > gc() > used (Mb) gc trigger (Mb) > Ncells 478197 12.8 818163 21.9 > Vcells 9309525 71.1 31670210 241.7 > > # Memory 279,152k > > Here, the memory usage increases from 128.1k to 279.1k > > Could anyone point out what I could do to rectify this (if anything), or > generally what strategy I could take to improve this? > > Many thanks, > Rich. > > Mango Solutions > Tel : (01628) 418134 > Mob : (07967) 808091 > > > [[alternative HTML version deleted]] > > __ > [EMAIL PROTECTED] mailing list > https://www.stat.math.ethz.ch/mailman/listinfo/r-help > > -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UKFax: +44 1865 272595 __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
