How do I clean up R memory without restarting my PC?

Question

I am running my code in R (under Windows) which involves a lot of in-memory data. I tried to use rm(list=ls()) to clean up memory, but seems the memory is still occupied and I cannot rerun my code. I tried to close the R and restart R again, but it is the same, seems memory is still occupied as when I run the codes it says it can't allocate memory (but it could at the first time). The memory seems only cleaned up after I restart my PC.

Is there any way to clean up the memory so that I can rerun my code without restarting my PC every time?

Can you provide more information about what your code is doing? If you're opening and not closing a lot of text connections, that could be a problem. — Eli Sander, Jul 20 '12 at 12:58
Open your Task Manager and under Processses sort according to Memory. That way you'll see if R is hogging up RAM. I suspect you have a rogue process, maybe you're running something in parallel? — Roman Luštrik, Jul 20 '12 at 13:08
Thanks, it is the R occupying about 1GB, so how can I clean up memory without shutting down R? I do have read.table and read.zoo in my codes which read quite large files... but after rm(list=ls()), why the memory is still not yet cleaned up? — Joyce, Jul 20 '12 at 14:01
R's garbage collection "marks" the RAM as available. Up to your OS to reclaim that. — Gavin Simpson, Jul 20 '12 at 14:10
Thank you. In that case, why when I run the codes for first time, there is no memory allocation warning, but when I run the same set of code the second time after run rm(list=ls()) and restart my R, there is memory allocation warning? — Joyce, Jul 20 '12 at 14:24
Could you create a reproducible example? For instance, create a very big matrix of random numbers and run the script twice to see if you get the same behavior. This could serve as a benchmark of other users to see if they experience the same problem. — Paul Hiemstra, Jul 23 '12 at 08:53

Alan · Accepted Answer · 2012-07-23T09:15:59.870

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Maybe you can try to use the function gc(). A call of gc() causes a garbage collection to take place. It can be useful to call gc() after a large object has been removed, as this may prompt R to return memory to the operating system. gc() also return a summary of the occupy memory.

edited Jul 23 '12 at 09:15

answered Jul 23 '12 at 08:31

Alan

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Could you expand a bit on what `gc` does. The answer is valid, but a bit short. – Paul Hiemstra Jul 23 '12 at 08:52
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+1, however the OP experiences the problem that even after closing R and restarting it, the memory is still not freed. Closing R altogether should be just as effective as calling `gc`. – Paul Hiemstra Jul 23 '12 at 09:27
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I've posted my answer to clear memory occupied by R. I would also like to point you to - http://stackoverflow.com/questions/8813753/what-is-the-difference-between-gc-and-rm – Kumar Vaibhav Oct 18 '14 at 10:28

score 36 · Answer 2 · edited Nov 18 '17 at 15:20

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I came under the same problem with R. I dig a bit and come with a solution, that we need to restart R session to fully clean the memory/RAM. For this, you can use a simple code after removing everything from your workspace. the code is as follows :

rm(list = ls())

.rs.restartR()

edited Nov 18 '17 at 15:20

Prradep

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answered Apr 14 '16 at 08:49

Anup Tirpude

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I guess this an internal function of RStudio and does not work with "plain vanilla" R. Good to know anyhow :-) – R Yoda Jul 05 '18 at 15:40
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The namespace of this function is attached to the search path in RStudio - see `search()`): `e – R Yoda Jul 05 '18 at 15:47
Does this happen automatically when restarting an R Session? – Cauder Sep 11 '20 at 05:04

score 13 · Answer 3 · edited Nov 18 '17 at 15:22

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Use ls() function to see what R objects are occupying space. use rm("objectName") to clear the objects from R memory that is no longer required. See this too.

edited Nov 18 '17 at 15:22

Prradep

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answered Oct 18 '14 at 10:27

Kumar Vaibhav

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score 6 · Answer 4 · answered Sep 11 '17 at 11:56

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memory.size(max=T) # gives the amount of memory obtained by the OS
[1] 1800
memory.size(max=F) # gives the amount of memory being used
[1] 261.17

Using Paul's example,

m = matrix(runif(10e7), 10000, 1000)

Now

memory.size(max=F)
[1] 1024.18

To clear up the memory

gc()
memory.size(max=F)
[1] 184.86

In other words, the memory should now be clear again. If you loop a code, it is a good idea to add a gc() as the last line of your loop, so that the memory is cleared up before starting the next iteration.

answered Sep 11 '17 at 11:56

Gabriel123

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Note that memory.size() is Windows specific and will return value of "Inf" if run on a Linux platform. The function gc() will still work with either. – Isaac Freitas Sep 07 '18 at 19:05
Perfect explanation and the Windows part is true, but useful function for cleaning up memory inside apply family functions and loops. – patL Apr 07 '21 at 18:12

score 3 · Answer 5 · answered Jul 23 '12 at 09:04

An example under Linux (Fedora 16) shows that memory is freed when R is closed:

$ free -m                                                                                                                                                                                                                                    
             total       used       free     shared    buffers     cached                                                                                                                                                                    
Mem:          3829       2854        974          0        344       1440                                                                                                                                                                    
-/+ buffers/cache:       1069       2759                                                                                                                                                                                                     
Swap:         4095         85       4010

2854 megabytes is used. Next I open an R session and create a large matrix of random numbers:

m = matrix(runif(10e7), 10000, 1000)

when the matrix is created, 3714 MB is used:

$ free -m                                                                                                                                                                                                                                    
             total       used       free     shared    buffers     cached                                                                                                                                                                    
Mem:          3829       3714        115          0        344       1442                                                                                                                                                                    
-/+ buffers/cache:       1927       1902                                                                                                                                                                                                     
Swap:         4095         85       4010

After closing the R session, I nicely get back the memory I used (2856 MB free):

$ free -m                                                                                                                                                                                                                                    
             total       used       free     shared    buffers     cached                                                                                                                                                                    
Mem:          3829       2856        972          0        344       1442                                                                                                                                                                    
-/+ buffers/cache:       1069       2759                                                                                                                                                                                                     
Swap:         4095         85       4010

Ofcourse you use Windows, but you could repeat this excercise in Windows and report how the available memory develops before and after you create this large dataset in R.

score 2 · Answer 6 · answered Sep 20 '18 at 10:00

Just adding this for reference in case anybody needs to restart and immediatly run a command.

I'm using this approach just to clear RAM from the system. Make sure you have deleted all objects no longer required. Maybe gc() can also help before hand. But nothing will clear RAM better as restarting the R session.

library(rstudioapi)
restartSession(command = "print('x')")

score 1 · Answer 7 · answered Jul 02 '19 at 15:07

There is only so much you can do with rm() and gc(). As suggested by Gavin Simpson, even if you free the actual memory in R, Windows often won't reclaim it until you close R or it is needed because all the apparent Windows memory fills up.

This usually isn't a problem. However, if you are running large loops this can sometimes lead to fragmented memory in the long term, such that even if you free the memory and restart R - the fragmented memory may prevent you allocating large chunks of memory. Especially if other applications were allocated fragmented memory while you were running R. rm() and gc() may delay the inevitable, but more RAM is better.

score 0 · Answer 8 · answered Jun 21 '18 at 14:02

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I've found it helpful to go into my "tmp" folder and delete all hanging rsession files. This usually frees any memory that seems to be "stuck".

answered Jun 21 '18 at 14:02

sehock

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How do I clean up R memory without restarting my PC?

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