I previously saved a 2.8G RData file and now I'm trying to load it so I can work on it again, but weirdly, I can't. It's giving the error
Error: vector memory exhausted (limit reached?)
This is weird since I was working with it fine before. One thing that changed though is I upgraded to the latest version of R 3.5.0. I saw a previous post with the same error like this but it wasn't resolved. I was hopeful with this solution which increases the memory.limit() but unfortunately, it's only available for Windows.
Can anyone help? I don't really understand what's the problem here since I was able to work with my dataset before the update so it shouldn't be throwing this error.
Did the update somehow decreased the RAM allocated to R? Can we manually increase the memory.limit() in Mac to solve this error?
This change was necessary to deal with operating system memory over-commit issues on Mac OS. From the NEWS file:
\item The environment variable \env{R_MAX_VSIZE} can now be used
to specify the maximal vector heap size. On macOS, unless specified
by this environment variable, the maximal vector heap size is set to
the maximum of 16GB and the available physical memory. This is to
avoid having the \command{R} process killed when macOS over-commits
memory.
Set the environment variable R_MAX_VSIZE to an appropriate value for your system before starting R and you should be able to read your file.
Related
I am trying to deal with issues of memory limitation in R. I was running a code that would generate monthly data output. It was all going fine, R saved all monthly csv data in the computer as expected but seemed the have the console frozen (although the code ran entirely). When I restarted it, it did not launch as expected, I had to wipe everything and reinstall windows. I downloaded the new version of R (version 4.2.1) and my code no longer runs because of memory limitation. I get the error message below.
Error: cannot allocate vector of size 44.2 Gb
I tried increasing the memory with memory.limit() as I did before but it seems like it is no longer supported by R (memory.limit() bug: "memory.limit() is not longer supported". Increasing memory).
How to deal with this?
I have an .RData file that is rather large. It takes up 1.10 GB on my hard drive, it contains a data frame with 100 variables and 12 million observations. Now when I try to load it, I can open the task manager and watch the memory usage go all the way up to 7450 MB; at which point my RAM is completely exhausted, and I get "Error reading from connection." I'm pretty sure this memory deficiency is the problem, but how can that be? Like I said, the .RData is only 1.10 GB.
I'm using R x64 4.0.5. If it's any clue, when I open the 32-Bit version of R (4.0.5) it tells me "Error: memory exhausted (limit reached?)", reinforcing my suspicion that this is a memory issue.
I am unable to access the data any other way, I have to make the .RData file work or it's gone. Why does R require more than 8 GB of RAM to load a 1GB workspace?
I'm running RStudio x64 on Windows 10 with 16GB of RAM. RStudio seems to be running out of memory for allocating large vectors, in this case a 265MB one. I've gone through multiple tests and checks to identify the problem:
Memory limit checks via memory.limit() and memory.size(). Memory limit is ~16GB and size of objects stored in environment is ~5.6GB.
Garbage collection via gc(). This removes some 100s of MBs.
Upped priority of rsession.exe and rstudio.exe via Task Manager to real-time.
Ran chkdsk and RAM diagnostics on system restart. Both returned no errors.
But the problem persists. It seems to me that R can access 16GB of RAM (and shows 16GB committed on Resource Monitor), but somehow is still unable to make a large vector. My main confusion is this: the problem only begins appearing if I run code on multiple datasets consecutively, without restarting RStudio in between. If I do restart RStudio, the problem doesn't show up anymore, not for a few runs.
The error should be replicable with any large R vector allocation (see e.g. the code here). I'm guessing the fault is software, some kind of memory leak, but I'm not sure where or how, or how to automate a fix.
Any thoughts? What have I missed?
I am running some basic data manipulation on a Macbook Air (4GB Memory, 120GB HD with 8GB available). My input file is about 40 MB, and I don't write anything to the disk until end of the process. However, in the middle of my process, my Mac says there's no memory to run. I checked hard drive and found there's about 500MB left.
So here are my questions:
How is it possible that R filled up my disk so quickly? My understanding is that R store everything in memory (unless I explicitly write something out to disk).
If R does write temporary files on the disk, how can I find these files to delete them?
Thanks a lot.
Update 1: error message I got:
Force Quit Applications: Your Mac OS X startup disk has no more space available for
application memory
Update 2: I checked tempdir() and it shows "var/folders/k_xxxxxxx/T//Rtmpdp9GCo". But I can't locate this director from my Finder
Update 3: After unlink(tempdir(),recursive=TRUE) in R and restarting my computer, I got my disk space back. I still would like to know if R write on my hard drive to avoid similar situations in the future.
Update 4: My main object is about 1GB. I use Activity Monitor to track process, and while Memory usage is about 2GB, Disk activity is extremely high: Data read: 14GB, data write, 44GB. I have no idea what R is writing.
R writes to a temporary per-session directory which it also cleans up at exit.
It follows convention and respects TMP and related environment variables.
What makes you think that disk space has anything to do with this? R needs all objects held in memory, not off disk (by default; there are add-on packages that allow a subset of operations on on-disk stored files too big to fit into RAM).
One of the steps in the "process" is causing R to request a chunk of RAM from the OS to enable it to continue. The OS could not comply and thus R terminated the "process" that you were running with the error message you failed to give us. [Hint, it would help if you showed the actual error not your paraphrasing thereof. Some inkling of the code you were running would also help. 40MB on-disk sounds like a reasonably large file; how many rows/columns etc.? How big is the object within R; object.size()?
I am executing a sql query in R using sqldf package to create a data frame in R. But, it is throwing an error:
Error: cannot allocate vector of size 3.9 Gb
I have gone through various threads with a similar issue but I could not find a suitable answer.
Can anyone please help me out on this.
I am using R 2.15.1 version on 64-bit linux machine with 32 GB RAM.
The error is often misunderstood. It means that R is unable to allocate an additional chunk of 3.9Gb of memory space. If you were to look at the R process, it would have been using a very large amount of the available RAM before it issued the error you saw and you'd have realised that the error meant additional RAM.
You will have to expand upon this in another question to explain what it is you are trying to do as if you can't read data into R with 32Gb of RAM available you will probably need to look at incremental processing of that data. For that we need details of what you are trying to achieve.
It's just may be the memory limit in R is too low. First try memory.size() then use memory.limit() to know limit and set new one. I'm not sure if it help. Just let us all know.