[Rd] [External] Re: .Internal(quit(...)): system call failed: Cannot allocate memory

iuke-tier@ey m@iii@g oii uiow@@edu iuke-tier@ey m@iii@g oii uiow@@edu
Fri Nov 27 21:18:35 CET 2020

On Thu, 26 Nov 2020, Jan Gorecki wrote:

> Thank you Luke for looking into it. Your knowledge of gc is definitely
> helpful here. I put comments inline below.
> Best,
> Jan
> On Wed, Nov 25, 2020 at 10:38 PM <luke-tierney using uiowa.edu> wrote:
>> On Tue, 24 Nov 2020, Jan Gorecki wrote:
>>> As for other calls to system. I avoid calling system. In the past I
>>> had some (to get memory stats from OS), but they were failing with
>>> exactly the same issue. So yes, if I would add call to system before
>>> calling quit, I believe it would fail with the same error.
>>> At the same time I think (although I am not sure) that new allocations
>>> made in R are working fine. So R seems to reserve some memory and can
>>> continue to operate, while external call like system will fail. Maybe
>>> it is like this by design, don't know.
>> Thanks for the report on quit(). We're exploring how to make the
>> cleanup on exit more robust to low memory situations like these.
>>> Aside from this problem that is easy to report due to the warning
>>> message, I think that gc() is choking at the same time. I tried to
>>> make reproducible example for that, multiple times but couldn't, let
>>> me try one more time.
>>> It happens to manifest when there is 4e8+ unique characters/factors in
>>> an R session. I am able to reproduce it using data.table and dplyr
>>> (0.8.4 because 1.0.0+ fails even sooner), but using base R is not easy
>>> because of the size. I described briefly problem in:
>>> https://github.com/h2oai/db-benchmark/issues/110
>> Because of the design of R's character vectors, with each element
>> allocated separately, R is never going to be great at handling huge
>> numbers of distinct strings. But it can do an adequate job given
>> enough memory to work with.
>> When I run your GitHub issue example on a machine with around 500 Gb
>> of RAM it seems to run OK; /usr/bin/time reports
>> 2706.89user 161.89system 37:10.65elapsed 128%CPU (0avgtext+0avgdata 92180796maxresident)k
>> 0inputs+103450552outputs (0major+38716351minor)pagefaults 0swaps
>> So the memory footprint is quite large. Using gc.time() it looks like
>> about 1/3 of the time is in GC. Not ideal, and maybe could be improved
>> on a bit, but probably not by much. The GC is basically doing an
>> adequate job, given enough RAM.
> Agree, 1/3 is a lot but still acceptable. So this strictly is not
> something that requires intervention.
> PS. I wasn't aware of gc.time(), it may be worth linking it from
> SeeAlso in gc() manual.
>> If you run this example on a system without enough RAM, or with other
>> programs competing for RAM, you are likely to end up fighting with
>> your OS/hardware's virtual memory system. When I try to run it on a
>> 16Gb system it churns for an hour or so before getting killed, and
>> /usr/bin/time reports a huge number of page faults:
>> 312523816inputs+0outputs (24761285major+25762068minor)pagefaults 0swaps
>> You are probably experiencing something similar.
> Yes, this is exactly what I am experiencing.
> The machine is a bare metal machine of 128GB mem, csv size 50GB,
> data.frame size 74GB.
> In my case it churns for ~3h before it gets killed with SIGINT from
> the parent R process which uses 3h as a timeout for this script.
> This is something I would like to be addressed because gc time is far
> bigger than actual computation time. This is not really acceptable, I
> would prefer to raise an exception instead.
>> There may be opportunities for more tuning of the GC to better handle
>> running this close to memory limits, but I doubt the payoff would be
>> worth the effort.
> If you don't have plans/time to work on that anytime soon, then I can
> fill bugzilla for this problem so it won't get lost in the mailing
> list.

I'm not convinced anything useful can be done that would work well for
your application without working badly for others.

If you want to drive this close to your memory limits you are probably
going to have to take responsibility for some tuning at your end. One
option in ?Memory you might try is the R_MAX_VSIZE environment
variable. On my 16Gb machine with R_MAX_VSIZE=16Gb your example fails
very quickly with

Error: vector memory exhausted (limit reached?)

rather than churning for an hour trying to make things work. Setting
memory and/or virtual memory limits in your shell is another option.



>> Best,
>> luke
>>> It would help if gcinfo() could take FALSE/TRUE/2L where 2L will print
>>> even more information about gc, like how much time the each gc()
>>> process took, how many objects it has to check on each level.
>>> Best regards,
>>> Jan
>>> On Tue, Nov 24, 2020 at 1:05 PM Tomas Kalibera <tomas.kalibera using gmail.com> wrote:
>>>> On 11/24/20 11:27 AM, Jan Gorecki wrote:
>>>>> Thanks Bill for checking that.
>>>>> It was my impression that warnings are raised from some internal
>>>>> system calls made when quitting R. At that point I don't have much
>>>>> control over checking the return status of those.
>>>>> Your suggestion looks good to me.
>>>>> Tomas, do you think this could help? could this be implemented?
>>>> I think this is a good suggestion. Deleting files on Unix was changed
>>>> from system("rm") to doing that in C, and deleting the session directory
>>>> should follow.
>>>> It might also help diagnosing your problem, but I don't think it would
>>>> solve it. If the diagnostics in R works fine and the OS was so
>>>> hopelessly out of memory that it couldn't run any more external
>>>> processes, then really this is not a problem of R, but of having
>>>> exhausted the resources. And it would be a coincidence that just this
>>>> particular call to "system" at the end of the session did not work.
>>>> Anything else could break as well close to the end of the script. This
>>>> seems the most likely explanation to me.
>>>> Do you get this warning repeatedly, reproducibly at least in slightly
>>>> different scripts at the very end, with this warning always from quit()?
>>>> So that the "call" part of the warning message has .Internal(quit) like
>>>> in the case you posted? Would adding another call to "system" before the
>>>> call to "q()" work - with checking the return value? If it is always
>>>> only the last call to "system" in "q()", then it is suspicious, perhaps
>>>> an indication that some diagnostics in R is not correct. In that case, a
>>>> reproducible example would be the key - so either if you could diagnose
>>>> on your end what is the problem, or create a reproducible example that
>>>> someone else can use to reproduce and debug.
>>>> Best
>>>> Tomas
>>>>> On Mon, Nov 23, 2020 at 7:10 PM Bill Dunlap <williamwdunlap using gmail.com> wrote:
>>>>>> The call to system() probably is an internal call used to delete the session's tempdir().  This sort of failure means that a potentially large amount of disk space is not being recovered when R is done.  Perhaps R_CleanTempDir() could call R_unlink() instead of having a subprocess call 'rm -rf ...'.  Then it could also issue a specific warning if it was impossible to delete all of tempdir().  (That should be very rare.)
>>>>>>> q("no")
>>>>>> Breakpoint 1, R_system (command=command using entry=0x7fffffffa1e0 "rm -Rf /tmp/RtmppoKPXb") at sysutils.c:311
>>>>>> 311     {
>>>>>> (gdb) where
>>>>>> #0  R_system (command=command using entry=0x7fffffffa1e0 "rm -Rf /tmp/RtmppoKPXb") at sysutils.c:311
>>>>>> #1  0x00005555557c30ec in R_CleanTempDir () at sys-std.c:1178
>>>>>> #2  0x00005555557c31d7 in Rstd_CleanUp (saveact=<optimized out>, status=0, runLast=<optimized out>) at sys-std.c:1243
>>>>>> #3  0x00005555557c593d in R_CleanUp (saveact=saveact using entry=SA_NOSAVE, status=status using entry=0, runLast=<optimized out>) at system.c:87
>>>>>> #4  0x00005555556cc85e in do_quit (call=<optimized out>, op=<optimized out>, args=0x555557813f90, rho=<optimized out>) at main.c:1393
>>>>>> -Bill
>>>>>> On Mon, Nov 23, 2020 at 3:15 AM Tomas Kalibera <tomas.kalibera using gmail.com> wrote:
>>>>>>> On 11/21/20 6:51 PM, Jan Gorecki wrote:
>>>>>>>> Dear R-developers,
>>>>>>>> Some of the more fat scripts (50+ GB mem used by R) that I am running,
>>>>>>>> when they finish they do quit with q("no", status=0)
>>>>>>>> Quite often it happens that there is an extra stderr output produced
>>>>>>>> at the very end which looks like this:
>>>>>>>> Warning message:
>>>>>>>> In .Internal(quit(save, status, runLast)) :
>>>>>>>>     system call failed: Cannot allocate memory
>>>>>>>> Is there any way to avoid this kind of warnings? I am using stderr
>>>>>>>> output for detecting failures in scripts and this warning is a false
>>>>>>>> positive of a failure.
>>>>>>>> Maybe quit function could wait little bit longer trying to allocate
>>>>>>>> before it raises this warning?
>>>>>>> If you see this warning, some call to system() or system2() or similar,
>>>>>>> which executes an external program, failed to even run a shell to run
>>>>>>> that external program, because there was not enough memory. You should
>>>>>>> be able to find out where it happens by checking the exit status of
>>>>>>> system().
>>>>>>> Tomas
>>>>>>>> Best regards,
>>>>>>>> Jan Gorecki
>>>>>>>> ______________________________________________
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>>>>>>>> https://stat.ethz.ch/mailman/listinfo/r-devel
>>>>>>> ______________________________________________
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>> --
>> Luke Tierney
>> Ralph E. Wareham Professor of Mathematical Sciences
>> University of Iowa                  Phone:             319-335-3386
>> Department of Statistics and        Fax:               319-335-3017
>>     Actuarial Science
>> 241 Schaeffer Hall                  email:   luke-tierney using uiowa.edu
>> Iowa City, IA 52242                 WWW:  http://www.stat.uiowa.edu

Luke Tierney
Ralph E. Wareham Professor of Mathematical Sciences
University of Iowa                  Phone:             319-335-3386
Department of Statistics and        Fax:               319-335-3017
    Actuarial Science
241 Schaeffer Hall                  email:   luke-tierney using uiowa.edu
Iowa City, IA 52242                 WWW:  http://www.stat.uiowa.edu

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