Because If my bitcoin price checker built on electron will start allocating all memory on the machine, then some arbitrary process (e.g. systemd) can get malloc error. But it's not systemd's fault the memory got eaten; so why it's being punished for low memory conditions?
It's like choosing a random person to be ejected from the plane.
The Linux kernel supports the following overcommit handling modes
0 - Heuristic overcommit handling. Obvious overcommits of address space are refused. Used for a typical system. It ensures a seriously wild allocation fails while allowing overcommit to reduce swap usage. root is allowed to allocate slightly more memory in this mode. This is the default.
1 - Always overcommit. Appropriate for some scientific applications. Classic example is code using sparse arrays and just relying on the virtual memory consisting almost entirely of zero pages.
2 - Don't overcommit. The total address space commit for the system is not permitted to exceed swap + a configurable amount (default is 50%) of physical RAM. Depending on the amount you use, in most situations this means a process will not be killed while accessing pages but will receive errors on memory allocation as appropriate. Useful for applications that want to guarantee their memory allocations will be available in the future without having to initialize every page.
Naive question: why is this default 50%, and more generally why is this not the entire RAM, what happens to the rest?
I can understand leaving some amount free in case the kernel needs to allocate additional memory in the future, but anything near half seems like a lot!
If successful, calloc(), malloc(), realloc(), reallocf(), valloc(), and aligned_alloc() functions return a pointer to allocated memory. If there is an error, they return a NULL pointer and set errno to ENOMEM.
In practice, I find a lot of code that does not check for NULL, which is rather distressing.
Usefully handling allocation errors is very hard to do well, since it infects literally every error handling path in your codebase. Any error handling that calls a function that might return an indirect allocation error needs to not allocate itself. Even if you have a codepath that speculatively allocates and can fallback, the process is likely so close to ruin that some other function that allocates will fail soon.
It’s almost universally more effective (not to mention easier) to keep track of your large/variable allocations proactively, and then maintain a buffer for little “normal” allocations that should have an approximate constant bound.
This is just a Linux ecosystem thing. Other full size operating systems do memory accounting differently, and are able to correctly communicate when more memory is not available.
As an aside: To me, checking malloc() for NULL is easier than checking a pointer returned by malloc on first use. That's what you're supposed to do in the presence of overcommit.
Instead, you want to kill the process that's hogging all the memory.
The OOM killer heuristic is not perfect, but it will generally avoid killing critical processes and is fairly good at identifying memory hogs.
And if you agree that using the OOM killer is better than returning failure to a random unlucky process, then there's no reason not to use overcommit.
Besides, overcommit is useful. Virtual-memory-based copy-on-write, allocate-on-write, sparse arrays, etc. are all useful and widely-used.
You can and maybe even should disable overcommit this way when running postgres on the server (and only a minimum of what you would these days call sidecar processes (monitoring and backup agents, etc.) on the same host/kernel), but once you have a typical zoo of stuff using dynamic languages living there, you WILL blow someone's leg off.
In fairness, i don't know what else general purpose software is supposed to do here other than die. Its not like there is a graceful way to handle insufficient memory to run the program.
For cleanly surfacing errors, overcommit=2 is a bad choice. For most servers, it's much better to leave overcommit on, but make the OOM killer always target your primary service/container, using oom-score-adj, and/or memory.oom.group to take out the whole cgroup. This way, you get to cleanly combine your OOM condition handling with the general failure case and can restart everything from a known foundation, instead of trying to soldier on while possibly lacking some piece of support infrastructure that is necessary but usually invisible.
Taken from a SO post:
# Create a cgroup
mkdir /sys/fs/cgroup/memory/my_cgroup
# Add the process to it
echo $PID > /sys/fs/cgroup/memory/my_cgroup/cgroup.procs
# Set the limit to 40MB
echo $((40 \* 1024 \* 1024)) > /sys/fs/cgroup/memory/my_cgroup/memory.limit_in_bytes
have you checked what your `vm.overcommit_ratio` is? If its < 100%, then you will get OOM kills even if plenty of RAM is free since the default is 50 i.e. 50% of RAM can be COMMITTED and no more.
curious what kind of failures you are alluding to.
Thanks for the tip about vm.overcommit_ratio though, I think it's set to the default.
Secondly, memory is a global resource so you don't get local failures when it's exhausted, whoever allocates first after memory has been exhausted will get an error they might be the application responsible for the exhaustion or they might not be. They might crash on the error or they might "handle it", keep going and render the system completely unusable.
No, exact accounting is not a solution. Ulimits and configuring the OOM killer are solutions.
fork(2) has been copy-on-write for decades and does not copy the entire process address space. Thread stacks are a non-sequitur either as stack uses the data pages, the thread stacks are rather small in size in most scanarios, hence the thread stacks are also subject to copy-on-write.
The only overhead that the use of fork(2) incurs is an extra copy of process' memory descriptior pages, which is a drop in the ocean for modern systems for large amounts of RAM.
Thread stacks come up because reserving them completely ahead of time would incur large amounts of memory usage. Typically they start small and grow when you touch the guards. This is a form of overcommit. Even windows dynamically grows stacks like this
> Thread stacks come up because reserving them completely ahead of time would incur large amounts of memory usage. Typically they start small and grow when you touch the guards. This is a form of overcommit.
Ahead of the time memory reservation entails a page entry being allocated in the process’s page catalogue («logical» allocation), and the page «sits» dormant until it is accessed and causes a memory access fault – that is the moment when the physical allocation takes place. So copying reserved but not accessed yet pages has zero effect on the physical memory consumption of the process.
What actually happens to the thread stacks depends on the actual number of active threads. In modern designs, threads are consumed from thread pools that implement some sort of a run queue where the threads sit idle until they get assigned a unit of work. So if a thread is idle, it does not use its own stack thread and, consequently, there is no side effect on the child's COW address space.
Granted, if the child was copied with a large number of active threads, the impact will be very different.
> Even windows dynamically grows stacks like this
Windows employs a distinct process/thread design, making the UNIX concept of a process foreign. Threads are the primary construct in Windows and the kernel is highly optimised for thread management rather than processes. Cygwin has outlined significant challenges in supporting fork(2) semantics on Windows and has extensively documented the associated difficulties. However, I am veering off-topic.
Idle threads do increase the amount of committed stack. Once their stack grows it stays grown, it's not common to unmap the end and shrink the stacks. In a system without overcommit these stacks will contribute to total reserved phys/swap in the child, though ofc the pages will be cow.
> Windows employs a distinct process/thread design, making the UNIX concept of a process foreign. Threads are the primary construct in Windows and the kernel is highly optimised for thread management rather than processes. Cygwin has outlined significant challenges in supporting fork(2) semantics on Windows and has extensively documented the associated difficulties. However, I am veering off-topic.
The nt kernel actually works similarly to Linux w.r.t. processes and threads. Internally they are the same thing. The userspace is what makes process creation slow. Actually thread creation is also much slower than on Linux, but it's better than processes. Defender also contributes to the problems here.
Windows can do cow mappings, fork might even be implementable with undocumented APIs. Exec is essentially impossible though. You can't change the identity of a process like that without changing the PID and handles.
Fun fact: the clone syscall will let you create a new task that both shares VM and keeps the same stack as the parent. Chaos results, but it is fun. You used to be able to share your PID with the parent too, which also caused much destruction.
This is largely not true for most processes. For a child process to start writing into its own data pages en masse, there has to exist a specific code path that causes such behaviour. Processes do not randomly modify their own data space – it is either a bug or a peculiar workload that causes it.
You would have a stronger case if you mentioned, e.g., the JVM, which has a high complexity garbage collector (rather, multiple types of garbage collectors – each with its own behaviour), but the JVM ameliorates the problem by attempting to lock in the entire heap size at startup or bailing if it fails to do so.
In most scenarios, forking a process has a negligible effect on the overall memory consumption in the system.
> In most scenarios, forking a process has a negligible effect on the overall memory consumption in the system.
Yes, that’s what they’re getting at. It’s good overcommitment. It’s still overcommitment, because the OS has no way of knowing whether the process has the kind of rare path you’re talking about for the purposes of memory accounting. They said that disabling overcommit is wasteful, not that fork is wasteful.
For modern (post-x86_64) memory allocators a common strategy is to allocate hundreds of gigabytes of virtual memory and let the kernel handle deal with actually swapping in physical memory pages upon use.
This way you can partition the virtual memory space into arenas as you like. This works really well.
Obviously you don't want to have to octuple your physical memory for pages that will never be used, especially these days, so the typical way around that is to allocate a lot of swap. Then the allocations that aren't actually used can be backed by swap instead of RAM.
Except then you've essentially reimplemented overcommit. Allocations report success because you have plenty of swap but if you try to really use that much the system grinds to a halt.
Then your memory requirements always were potentially 512GB. It may just happen to be even with that amount of allocation you may only need 64GB of actual physical storage; however, there is clearly a path for your application to suddenly require 512GB of storage. Perhaps when it's under an attack or facing misconfigured clients.
If your failure strategy is "just let the server fall over under pressure" then this might be fine for you.
If an allocator unconditionally maps in 512GB at once to minimize expensive reallocations, that doesn't inherently have any relationship to the maximum that could actually be used in the program.
Or suppose a generic library uses buffers that are ten times bigger than the maximum message supported by your application. Your program would deterministically never access 90% of the memory pages the library allocated.
> If your failure strategy is "just let the server fall over under pressure" then this might be fine for you.
The question is, what do you intend to happen when there is memory pressure?
If you start denying allocations, even if your program is designed to deal with that, so many others aren't that your system is likely to crash, or worse, take a trip down rarely-exercised code paths into the land of eldritch bugs.
One would be where you have frequent large mallocs which get freed fast. Another would be where you have written a garbage collected language in C/C++.
When calling free, delete or letting your GC do that for you the memory isn't actually given back immediately, glibc has malloc_trim(0) for that, which tries it's best to give back as much unused memory to the OS as possible.
Then you can retry your call to malloc and see if it fails and then just let your supervisor restart your service/host/whatever or not.
- https://github.com/torvalds/linux/blob/master/mm/util.c#L753
Fact is that by the time small allocations are failing you are almost no better off handling the null than you would be handling segfaults and the sigterms from the killer.
Often for servers performance will fall off a cliff long before the oom killer is needed, too.
The redis engineers KNOW fork-to-save will at most result in few tens of MBs of extra memory used in vast majority of cases and benefit of seamless saving. Like, there is a theoretical where it uses double the memory but it would require all the data in database be replaced during short interval snapshot is saved and that's just unrealistic
Memory allocation is a highly non-deterministic process which highly depends on the code path, and it is generally impossible to predict how the child will handle its own memory space – it can be little or it can be more (relatively to the parent), and it is usually somewhere in the middle. Most daemons, for example, consuming next to zero extra memory after forking.
The Ruby garbage collector «mark-and-sweep» (old versions of Ruby – 1.8 and 1.9) and Python reference counting (the Instagram case) bugs are prime examples of pathological cases when a child would walk over its data pages, making each dirty and causing a system collapse, but the bugs have been fixed or workarounds have been applied. Honourable mention goes to Redis in a situation when THP (transparent huge pages) are enabled.
No heuristics exist out there that would turn memory allocation into a deterministic process.
> In mode 2 the MAP_NORESERVE flag is ignored.
https://www.kernel.org/doc/Documentation/vm/overcommit-accou...
POSIX not so much.
We may be entering an era when everyone in computing has to get serious about resource consumption. NVidia says GPUs are going to get more expensive for the next five years. DRAM prices are way up, and Samsung says it's not getting better for the next few years. Bulk electricity prices are up due to all those AI data centers. We have to assume for planning purposes that computing gets a little more expensive each year through at least 2030.
Somebody may make a breakthrough, but there's nothing in the fab pipeline likely to pay off before 2030, if then.
I'm not disabling overcommit for now, but maybe I should.
I recommend everyone to enable linux's new multi-generational LRU, that can be configured to trigger the OOM when the workingset of the last N deciseconds doesn't fit in memory. And <https://github.com/hakavlad/nohang> has some more suggestions.
Memory overcommit means that once you run out of physical memory, the OOM killer will forcefully terminate your processes with no way to handle the error. This is fundamentally incompatible with the goal of writing robust and stable software which should handle out-of-memory situations gracefully.
But it feels like a lost cause these days...
So much software breaks once you turn off overcommit, even in situations where you're nowhere close to running out of physical memory.
What's not helping the situation is the fact that the kernel has no good page allocation API that differentiates between reserving and committing memory. Large virtual memory buffers that aren't fully committed can be very useful in certain situations. But it should be something a program has to ask for, not the default behavior.
Having an assumption that your process will never crash is not safe. There will always be freak things like CPUs taking the wrong branch or bits randomly flipping. Parting of design a robust system is being tolerant to things like this.
Another point also mentioned is this thread is that by the time you run out of memory the system already is going to be in a bad state and now you probably don't have enough memory to even get out of it. Memory should have been freed already by telling programs to lighten up on their memory usage or by killing them and reclaiming the resources.
> Memory overcommit means that once you run out of physical memory, the OOM killer will forcefully terminate your processes with no way to handle the error. This is fundamentally incompatible with the goal of writing robust and stable software which should handle out-of-memory situations gracefully.
The big software is not written that way. In fact, writing software that way means you will have to sacrifice performance, memory usage, or both because you either * need to allocate exactly what you always need and free it when it gets smaller (if you want to keep memory footprint similar)m and that will add latency * over-allocate, and waste RAM
And you'd end up with MORE memory related issues, not less. Writing app where every allocation can fail is just nightmarish waste of time for 99% of the apps that are not "onboard computer of a space ship/plane"
mmap with PROT_NONE is such a reservation and doesn't count towards the commit limit. A later mmap with MAP_FIXED and PROT_READ | PROT_WRITE can commit parts of the reserved region, and mmap calls with PROT_NONE and MAP_FIXED will decommit.
I want to agree with the locality of errors argument, and while in simple cases, yes, it holds true, it isn't necessarily true. If we don't overcommit, the allocation that kills us is simply the one that fails. Whether this allocation is the problematic one is a different question: if we have a slow leak that, every 10k allocation allocs and leaks, we're probably (9999 / 10k, assuming spherical allocations) going to fail on one that isn't the problem. We get about as much info as the oom-killer would have, anyways: this program is allocating too much.
Has malloc ever returned zero since then? Or has somebody undone this, erm, feature at times?
The allocation site is not necessarily what is leaking memory. What you actually want in either case is a memory dump where you can tell what is leaking or using the memory.
which is elegant and completely legitimate
A forked process would assume memory is already allocated, but I guess it would fail when writing to it as if vm.overcommit is set to 0 or 1.
On the other hand, if you have a pretty good idea that the child will finish persisting and exit before the cache is fully rewritten, double is too much. There's not really a mechanism for that though. Even if you could set an optimistic multiplier for multiple mapped CoW pages, you're back to demand paging failures --- although maybe it's still worthwhile.
It's wrong 99.99999% of the time. Because alternative is either "make it take double and waste half the RAM" or "write in memory data in a way that allows for snapshotting, throwing a bunch of performance into the trash"
the author says it's bad design, but has entirely missed WHY it wants overcommit
Two reasons why overcommit is a good idea:
- It lets you reserve memory and use the dirtying of that memory to be the thing that commits it. Some algorithms and data structures rely on this strongly (i.e. you would have to use a significantly different algorithm, which is demonstrably slower or more memory intensive, if you couldn't rely on overcommit).
- Many applications have no story for out-of-memory other halting. You can scream and yell at them to do better, but that won't help, because those apps that find themselves in that supposedly-bad situation ended up there for complex and well-considered reasons. My favorite: having complex OOM error handling paths is the worst kind of attack surface, since it's hard to get test coverage for it. So, it's better to just have the program killed instead, because that nixes the untested code path. For those programs, there's zero value in having the memory allocator be able to report OOM conditions other than by asserting in prod that mmap/madvise always succeed, which then means that the value of not overcommitting is much smaller.
Are there server apps where the value of gracefully handling out of memory errors outweighs the perf benefits of overcommit and the attack surface mitigation of halting on OOM? Yeah! But I bet that not all server apps fall into that bucket
Advertising for 2 with "but apps should handle it" is utter ignorance, and redis example shows that, the database is using the COW fork feature for basically the reason it exists, as do many, many servers and the warning is pretty much tailored for people thinking they are clever and not understanding memory subsystem
This is one of those classic money vs idealism things. In my experience, the money always wins this particular argument: nobody is going to buy more RAM for you so you can do this.
The difference is that you'll fail allocations, where there's a reasonable interface for errors, rather than failing at demand paging when writing to previously unused pages where there's not a good interface.
Of course, there are many software patterns where excessive allocations are made without any intent of touching most of the pages; that's fine with overcommit, but it will lead to allocation failures when you disable overcommit.
Disabling overcommit does make fork in a large process tricky; I don't think the rant about redis in the article is totally on target; fork to persist is a pretty good solution, copy on write is a reasonable cost to pay while dumping the data to disk and then it returns to normal when the dump is done. But without overcommit, it doubles the memory commitment while the dump is running, and that's likely to cause issues if redis is large relative to memory and that's worth checking for and warning about. The linked jemalloc issue seems like it could be problematic too, but I only skimmed; seems like that's worth warning about as well.
For the fork path, it might be nice if you could request overcommit in certain circumstances... fork but only commit X% rather than the whole memory space.
Doesn't really change the point. The RAM might not be completely wasted, but given that near every app will over-allocate and just use the pooled memory, you will waste memory that could otherwise be used to run more stuff.
And it can be quite significant, like it's pretty common for server apps to start a big process and then have COWed thread per connection in a pool, so your apache2 eating maybe 60MB per thread in pool is now in gigabytes range at very small pool sizes.
Blog is essentially call to "let's make apps like we did in the DOS era" which is ridiculus
Remember, the limit is artificial and defined by the user with overcommit=2, by overcommit_ratio and user_reserve_kbytes. Using overcommit=2 necessarily wastes RAM (renders a larger portion of it unusable).
The RAM is not unusable, it will be used. Some portion of ram may be unallocatable, but that doesn't mean it's wasted.
There's a tradeoff. With overcommit disabled, you will get allocation failure rather than OOM killer. But you'll likely get allocation failures at memory pressure below that needed to trigger the OOM killer. And if you're running a wide variety of software, you'll run into problems because overcommit is the mainstream default for Linux, so many things are only widely tested with it enabled.
I think that's a meaningless distinction: if userspace can't allocate it, it is functionally wasted.
I completely agree with your second paragraph, but again, some portion of RAM obtainable with overcommit=0 will be unobtainable with overcommit=2.
Maybe a better way to say it is that a system with overcommit=2 will fail at a lower memory pressure than one with overcommit=0. Additional RAM would have to be added to the former system to successfully run the same workload. That RAM is waste.
You can have simple web server that took less than 100MB of RAM take gigabytes, just because it spawned few COW-ed threads
- Apache2 runs. - Apache2 takes 50MB. - Apache2 spawns 32 threads. - Apache2 takes 50MB + (per-thread vars * 32)
overcommit 2
- Apache2 runs. - Apache2 takes 50MB. - Apache2 spawns 32 threads. - Apache2 takes 50MB + (5032) + (per-thread vars 32)
Boom, Now your simple apache server serving some static files can't fit on 512MB VM and needs in excess of 1.7GB of memory just to allocate
That "waste" (that overcommit turns into "not a waste") means you can do far less allocations, with overcommit you can just allocate a bunch of memory and use it gradually, instead of having to do malloc() every time you need a bit of memory and free() every time you get rid of it.
You'd also increase memory fragmentation that way possibly hitting performance.
It's also pretty much required for GCed languages to work sensibly
And even if it's not COW, there's nothing wrong or inefficient about opportunistically allocating pages ahead of time to avoid syscall latency. Or mmapping files and deciding halfway through you don't need the whole thing.
There are plenty of reasons overcommit is the default.