David Jones
2020-Sep-02 21:31 UTC
[R] Why does a 2 GB RData file exceed my 16GB memory limit when reading it in?
Thank you Uwe, John, and Bert - this is very helpful context. If it helps inform the discussion, to address John and Bert's questions - I actually had less memory free when I originally ran the analyses and saved the workspace, than when I read in the data back in later on (I rebooted in an attempt to free all possible memory before rereading the workspace back in). On Wed, Sep 2, 2020 at 1:27 PM John via R-help <r-help using r-project.org> wrote:>> On Wed, 2 Sep 2020 13:36:43 +0200 >> Uwe Ligges <ligges using statistik.tu-dortmund.de> wrote: >> >> > On 02.09.2020 04:44, David Jones wrote: >> > > I ran a number of analyses in R and saved the workspace, which >> > > resulted in a 2GB .RData file. When I try to read the file back >> > > into R >> > >> > Compressed in RData but uncompressed in main memory.... >> > >> > >> > > later, it won't read into R and provides the error: "Error: cannot >> > > allocate vector of size 37 Kb" >> > > >> > > This error comes after 1 minute of trying to read things in - I >> > > presume a single vector sends it over the memory limit. But, >> > > memory.limit() shows that I have access to a full 16gb of ram on my >> > > machine (12 GB are free when I try to load the RData file). >> > >> > But the data may need more.... >> > >> > >> > > gc() shows the following after I receive this error: >> > > >> > > used (Mb) gc trigger (Mb) max used (Mb) >> > > Ncells 623130 33.3 4134347 220.8 5715387 305.3 >> > > Vcells 1535682 11.8 883084810 6737.5 2100594002 16026.3 >> > >> > So 16GB were used when R gave up. >> > >> > Best, >> > Uwe Ligges >> >> For my own part, looking at the OP's question, it does seem curious >> that R could write that .RData file, but on the same system not be able >> to reload something it created. How would that work. Wouldn't the >> memory limit have been exceeded BEFORE the the .RData file was written >> the FIRST time? >> >> JDougherty>R experts may give you a detailed explanation, but it is certainly possible >that the memory available to R when it wrote the file was different than >when it tried to read it, is it not?>Bert Gunter>"The trouble with having an open mind is that people keep coming along and >sticking things into it." >-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
Leandro Marino
2020-Sep-02 23:21 UTC
[R] Why does a 2 GB RData file exceed my 16GB memory limit when reading it in?
David, If the ".Rdata" contains more than one object you could (and maybe should use) the SOAR package (from Venables). This package helps you to split the objects over multiple RData files. It's useful when you have numerous medium-large objects in the workspace but doesn't use then at the same time. When use SOAR::Attach(), for instance, it loads the current name of all the objects and retain than available in the searchpath but without load then to the memory. As you call, they will be loaded into the memory. If needed, you can update the object and then store it again with the SOAR::Store() For my use, this package is terrific! I use it with an analysis that I need to repeat over medium-large similars datasets. Best Leandro Em qua., 2 de set. de 2020 ?s 18:33, David Jones <david.tn.jones at gmail.com> escreveu:> Thank you Uwe, John, and Bert - this is very helpful context. > > If it helps inform the discussion, to address John and Bert's > questions - I actually had less memory free when I originally ran the > analyses and saved the workspace, than when I read in the data back in > later on (I rebooted in an attempt to free all possible memory before > rereading the workspace back in). > > > > On Wed, Sep 2, 2020 at 1:27 PM John via R-help <r-help using > r-project.org> wrote: > > >> On Wed, 2 Sep 2020 13:36:43 +0200 > >> Uwe Ligges <ligges using statistik.tu-dortmund.de> wrote: > >> > >> > On 02.09.2020 04:44, David Jones wrote: > >> > > I ran a number of analyses in R and saved the workspace, which > >> > > resulted in a 2GB .RData file. When I try to read the file back > >> > > into R > >> > > >> > Compressed in RData but uncompressed in main memory.... > >> > > >> > > >> > > later, it won't read into R and provides the error: "Error: cannot > >> > > allocate vector of size 37 Kb" > >> > > > >> > > This error comes after 1 minute of trying to read things in - I > >> > > presume a single vector sends it over the memory limit. But, > >> > > memory.limit() shows that I have access to a full 16gb of ram on my > >> > > machine (12 GB are free when I try to load the RData file). > >> > > >> > But the data may need more.... > >> > > >> > > >> > > gc() shows the following after I receive this error: > >> > > > >> > > used (Mb) gc trigger (Mb) max used (Mb) > >> > > Ncells 623130 33.3 4134347 220.8 5715387 305.3 > >> > > Vcells 1535682 11.8 883084810 6737.5 2100594002 16026.3 > >> > > >> > So 16GB were used when R gave up. > >> > > >> > Best, > >> > Uwe Ligges > >> > >> For my own part, looking at the OP's question, it does seem curious > >> that R could write that .RData file, but on the same system not be able > >> to reload something it created. How would that work. Wouldn't the > >> memory limit have been exceeded BEFORE the the .RData file was written > >> the FIRST time? > >> > >> JDougherty > > > >R experts may give you a detailed explanation, but it is certainly > possible > >that the memory available to R when it wrote the file was different than > >when it tried to read it, is it not? > > >Bert Gunter > > >"The trouble with having an open mind is that people keep coming along and > >sticking things into it." > >-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >[[alternative HTML version deleted]]
Jeff Newmiller
2020-Sep-02 23:51 UTC
[R] Why does a 2 GB RData file exceed my 16GB memory limit when reading it in?
You need more RAM to load this file. As the memory was being used in your original file, certain objects (such as numeric columns) were being shared among different higher-level objects (such as data frames). When serialized into the file those optimizations were lost, and now those columns are stored separately. Search [1] for "shared" to learn more about measuring object memory requirements. [1] http://adv-r.had.co.nz/memory.html On September 2, 2020 2:31:53 PM PDT, David Jones <david.tn.jones at gmail.com> wrote:>Thank you Uwe, John, and Bert - this is very helpful context. > >If it helps inform the discussion, to address John and Bert's >questions - I actually had less memory free when I originally ran the >analyses and saved the workspace, than when I read in the data back in >later on (I rebooted in an attempt to free all possible memory before >rereading the workspace back in). > > > >On Wed, Sep 2, 2020 at 1:27 PM John via R-help <r-help using >r-project.org> wrote: > >>> On Wed, 2 Sep 2020 13:36:43 +0200 >>> Uwe Ligges <ligges using statistik.tu-dortmund.de> wrote: >>> >>> > On 02.09.2020 04:44, David Jones wrote: >>> > > I ran a number of analyses in R and saved the workspace, which >>> > > resulted in a 2GB .RData file. When I try to read the file back >>> > > into R >>> > >>> > Compressed in RData but uncompressed in main memory.... >>> > >>> > >>> > > later, it won't read into R and provides the error: "Error: >cannot >>> > > allocate vector of size 37 Kb" >>> > > >>> > > This error comes after 1 minute of trying to read things in - I >>> > > presume a single vector sends it over the memory limit. But, >>> > > memory.limit() shows that I have access to a full 16gb of ram on >my >>> > > machine (12 GB are free when I try to load the RData file). >>> > >>> > But the data may need more.... >>> > >>> > >>> > > gc() shows the following after I receive this error: >>> > > >>> > > used (Mb) gc trigger (Mb) max used (Mb) >>> > > Ncells 623130 33.3 4134347 220.8 5715387 305.3 >>> > > Vcells 1535682 11.8 883084810 6737.5 2100594002 16026.3 >>> > >>> > So 16GB were used when R gave up. >>> > >>> > Best, >>> > Uwe Ligges >>> >>> For my own part, looking at the OP's question, it does seem curious >>> that R could write that .RData file, but on the same system not be >able >>> to reload something it created. How would that work. Wouldn't the >>> memory limit have been exceeded BEFORE the the .RData file was >written >>> the FIRST time? >>> >>> JDougherty > > >>R experts may give you a detailed explanation, but it is certainly >possible >>that the memory available to R when it wrote the file was different >than >>when it tried to read it, is it not? > >>Bert Gunter > >>"The trouble with having an open mind is that people keep coming along >and >>sticking things into it." >>-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) > >______________________________________________ >R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >https://stat.ethz.ch/mailman/listinfo/r-help >PLEASE do read the posting guide >http://www.R-project.org/posting-guide.html >and provide commented, minimal, self-contained, reproducible code.-- Sent from my phone. Please excuse my brevity.
John
2020-Sep-03 01:32 UTC
[R] Why does a 2 GB RData file exceed my 16GB memory limit when reading it in?
On Wed, 2 Sep 2020 16:31:53 -0500 David Jones <david.tn.jones at gmail.com> wrote:> Thank you Uwe, John, and Bert - this is very helpful context. > > If it helps inform the discussion, to address John and Bert's > questions - I actually had less memory free when I originally ran the > analyses and saved the workspace, than when I read in the data back in > later on (I rebooted in an attempt to free all possible memory before > rereading the workspace back in). >I assumed that, though I shouldn't have. Nice to know. Were you working from a terminal or through a GUI like RStudio? You will need to provide a really clear description of the initial and later conditions. Your step to reboot and then load is exactly what I would have done, I would also have killed any network connection temporarily to see if there are other things going on that caused the problem out side of R. You should also let any potential helper know what OS you are using, and what hardware configuration you have. Since you rebooted you are probably not working across a network, but ... JWDougherty
Ista Zahn
2020-Sep-03 13:54 UTC
[R] Why does a 2 GB RData file exceed my 16GB memory limit when reading it in?
On Wed, Sep 2, 2020 at 7:22 PM Leandro Marino <leandromarino at leandromarino.com.br> wrote:> > David, > > If the ".Rdata" contains more than one object you could (and maybe should > use) the SOAR package (from Venables). This package helps you to split the > objects over multiple RData files. It's useful when you have numerous > medium-large objects in the workspace but doesn't use then at the same > time. > > When use SOAR::Attach(), for instance, it loads the current name of all the > objects and retain than available in the searchpath but without load then > to the memory. As you call, they will be loaded into the memory. > > If needed, you can update the object and then store it again with the > SOAR::Store() > > For my use, this package is terrific! I use it with an analysis that I need > to repeat over medium-large similars datasets. >The qs package might also be worth a try. I don't have a specific reason for thinking it will avoid the original problem, but in general qs uses lots of fancy compression and memory management features. --Ista> Best > Leandro > > Em qua., 2 de set. de 2020 ?s 18:33, David Jones <david.tn.jones at gmail.com> > escreveu: > > > Thank you Uwe, John, and Bert - this is very helpful context. > > > > If it helps inform the discussion, to address John and Bert's > > questions - I actually had less memory free when I originally ran the > > analyses and saved the workspace, than when I read in the data back in > > later on (I rebooted in an attempt to free all possible memory before > > rereading the workspace back in). > > > > > > > > On Wed, Sep 2, 2020 at 1:27 PM John via R-help <r-help using > > r-project.org> wrote: > > > > >> On Wed, 2 Sep 2020 13:36:43 +0200 > > >> Uwe Ligges <ligges using statistik.tu-dortmund.de> wrote: > > >> > > >> > On 02.09.2020 04:44, David Jones wrote: > > >> > > I ran a number of analyses in R and saved the workspace, which > > >> > > resulted in a 2GB .RData file. When I try to read the file back > > >> > > into R > > >> > > > >> > Compressed in RData but uncompressed in main memory.... > > >> > > > >> > > > >> > > later, it won't read into R and provides the error: "Error: cannot > > >> > > allocate vector of size 37 Kb" > > >> > > > > >> > > This error comes after 1 minute of trying to read things in - I > > >> > > presume a single vector sends it over the memory limit. But, > > >> > > memory.limit() shows that I have access to a full 16gb of ram on my > > >> > > machine (12 GB are free when I try to load the RData file). > > >> > > > >> > But the data may need more.... > > >> > > > >> > > > >> > > gc() shows the following after I receive this error: > > >> > > > > >> > > used (Mb) gc trigger (Mb) max used (Mb) > > >> > > Ncells 623130 33.3 4134347 220.8 5715387 305.3 > > >> > > Vcells 1535682 11.8 883084810 6737.5 2100594002 16026.3 > > >> > > > >> > So 16GB were used when R gave up. > > >> > > > >> > Best, > > >> > Uwe Ligges > > >> > > >> For my own part, looking at the OP's question, it does seem curious > > >> that R could write that .RData file, but on the same system not be able > > >> to reload something it created. How would that work. Wouldn't the > > >> memory limit have been exceeded BEFORE the the .RData file was written > > >> the FIRST time? > > >> > > >> JDougherty > > > > > > >R experts may give you a detailed explanation, but it is certainly > > possible > > >that the memory available to R when it wrote the file was different than > > >when it tried to read it, is it not? > > > > >Bert Gunter > > > > >"The trouble with having an open mind is that people keep coming along and > > >sticking things into it." > > >-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) > > > > ______________________________________________ > > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > > http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.