We are writing a real-time game in EventMachine/Ruby. We're using ActiveRecord with MySQL for storing the game objects.
When we start the server we plan to load all the game objects into memory. This will allow for us to avoid any blocking/slow SQL queries with ActiveRecord.
However, we still need to persist the data in the database in case the server crashes, of course.
What are our options for doing so? I could use EM.Defer but I have no idea how many concurrent players that could handle since the thread pool is limited to 20.
Currently I'm thinking using Resque with Redis would be the best bet. Do everything with the objects in memory, and whenever there is a save that needs to occur for the database, fire off a job and add it to the Resque queue.
Any advice?
Threadpool size can be tweaked - see EventMachine.threadpool_size
Each server process (apache...) will spawn its own EventMachine reactor and its own EM.defer threadpool, so if you use a forking server (a mongrel farm, passenger, ...) you don't need to go crazy on the threadpool size
See EM-Synchrony by Ilja Grigorik (https://github.com/igrigorik/em-synchrony) - you should be able to simplify your code with it
Afaik, mysql has a non-blocking driver that you can use freely with EM, EM::Synchrony supports it http://www.igvita.com/2010/04/15/non-blocking-activerecord-rails/ - this would mean you don't need EM.defer at all!
Take a look at Thin - https://github.com/macournoyer/thin/ - it's non-blocking EM-based webserver that supports Rails
Having said all this, writing evented code is a bitch - forget about stack traces and make sure you're running benchmark tests often as anything blocking your reactor will block the entire application.
Also, this all applies to MRI Ruby ONLY. If you mean to use jruby... You're bound to get into trouble as thread-safety of eventmachine seems to be largely due to GIL of MRI Ruby and standard patterns don't work (many aspects of it can be made to work with this fork https://github.com/WebtehHR/eventmachine/tree/v1.0.3_w_fix which fixes some issues EM has with JRuby)
Unfortunately, guys from https://github.com/eventmachine/eventmachine are kind of not very active, the project currently has 200+ issues and almost 60 open pull requests which is why I've had to use a separate fork to continue playing with my current project - this still means EM is an awesome project just don't expect problems you encounter to be quickly fixed so do your best to not go out of the trodden path of EM use.
Another problem with JRuby is that EM::Synchrony imposes a heavy performance penalty because JRuby doesn't have implemented fibers as of 1.7.8 but rather maps them to Java native threads which are MUCH slower
Also, have you considered messaging with something like RabbitMQ (it has a synchronous https://github.com/ruby-amqp/bunny, and evented driver https://github.com/ruby-amqp/amqp) as a possibility to communicate game objects between clients and perhaps reduce overhead on the database / distributed memory store that you had in mind?
Redis/Resque seem good, but if all the jobs will need to do is simple persistance, and if there will be A LOT of such calls, you might want to consider beanstalkd - it has A LOT faster but simpler queue then Resque and you can probably make this even faster if you don't really need activerecord to dump attribute hashes into the database, see delayed_jobs vs resque vs beanstalkd?
A couple years and a failed project later, some thoughts:
avoid eventmachine if any way possible, there's a plethora of opportunities to peg your CPU nowadays with YARV/MRI Ruby on a IO constrained application and without wasting memory.
My favorite approach for a web application at this time is use Puma with multiple processes and threads.
Have in mind that GIL in YARV only affects the Ruby interpreter code, not the IO operations, meaning that on a IO constrained application you can add threads and see better utilization of a single core,
add more processes and you see better utilization of many cores :) On Heroku 1x worker we run 2 processes with 4 threads each and this pegs our CPU potential to the top in benchmark meaning the application is no longer IO bound, but CPU bound and doing so without unacceptable memory losses.
When we needed super-fast responses we were troubled by the DB write operation times which did not affect the response to client, so we did asynchronous database writes using sidekiq / resque,
In hindsight you could even do celluloid or concurrent-ruby for asynchronous IO reads/writes (think DB writes, cache visits etc), it's less overhead and infrastructure but harder to debug and problem solve in production - my worst nightmare being an async operation failing silently with no error trace in our Errors console (an exception in exception handling for example)
End result is that your application experiences the same sort of benefits you used to get from using eventmachine (elimination of the IO bound, full utilization of CPU without huge memory footprint, parallel non-blocking IO) without resorting to writing reactor code which is a complete bitch to do as explained in my 2013 post
As always after some research I was unable to find anything of real value. My question is how does one go about handling exceptions in a real time system? As program failure generally is not the best case i.e. nuclear reactor/ heart monitor.
Ok since everyone got lost on the second piece of this, which had NOTHING to do with the main question. I had it in there to show how I normally escape code blocks.
Exception handling in real-time/embedded systems has several layers. Not just the language supported options, but also MMU, CPU exceptions and one of my favorites: watchdogs.
Language exceptions (C/C++)
- not often used, beause it is hard to prove that all exceptions are handled at the right level. Also it is pretty hard to determine what threat/process should be responsible. Instead, programming by contract is preferred.
Programming style:
- i.e. programming by contract. Additional constraints : Misra/C Misra/C++. This can be checked to unsure that all possible cases are somehow handled. (i.e. no if without else)
Hardware support:
- MMU : use of multiple processes which are protected against each other. This allows
- watchdog
- CPU exceptions
- multi core: use of multiple cores to separate cricical processes from the rest. Also allows to have voting mechanisms (you want this and more for your nuclear reactor).
- multi-system
Most important is to define a strategy. Depending on the other nonfunctional requirements (safety, reliability, security) a strategy needs to be thought of. Can be graceful degradation to partial system reboot.
In a 'real-time', 'nuclear reactor' type system, chances are the exception handling allows the system to instead of fail, do the next best thing.
Let's say that we have a heart monitor. If it isn't receiving a signal, that might trigger an exception. In that case, the heart monitor might handle the exception by waiting a few seconds and trying again.
In a nuclear reactor, getting to a certain temperature might trigger an exception. In that case, the handling might shut off various parts of the reactor to start to cool it down, and then start them back up when it gets to a reasonable temperature.
Exceptions are meant to have a lower-level system say that it doesn't know what to do, and to have a higher level system handle it. Like in the nuclear reactor, the system that measures temperature probably doesn't know how to turn on parts of the reactor, so it triggers an exception so that some higher-level system can handle it.
A critical system is like any other system, except it's specified more clearly, passes through more testing phases, and is generally will fail-safe.
Regarding your form, yes it's pretty bad. I do mind the lack of {} very much; and it's been said so-often that this is just plain bad style, and leads to confusion when adding new code.
It just hit me the other day. What actually happens when I tell the computer to go into Stand-By or to Hibernate?
More spesifically, what implications, if any, does it have on code that is running? For example if an application is compressing some files, encoding video files, checking email, running a database query, generating reports or just processing lots of data or doing complicated math stuff. What happens? Can you end up with a bug in your video? Can the database query fail? Can data processing end up containing errors?
I'm asking this both out of general curiosity, but also because I started to wonder if this is something I should think about when I program myself.
You should remember that the OS (scheduler) freezes your program about a gazillion times each second. This means that your program can already function pretty well when the operating system freezes it. There isn't much difference, from your point of view, between stand-by, hibernate and context switching.
What is different is that you'll be frozen for a long time. And this is the only thing you need to think about. In most cases, this shouldn't be a problem.
If you have a network connection you'll probably need to re-establish it, and similar issues. But this just means checking for errors in all IO operations, which I'm sure you're already doing... :-)
My initial thought is that as long as your program and its eco-system is contained within the pc that is going on stand - by or hibernation, then, upon resume your program should not be affected.
However, if you are say updating a record in some database hosted on a separate machine then hibernation / stand - by will be treated as a timeout.
If your program is dependent on such a change in "power status" you can listen to WM_POWERBROADCAST Message as mentioned on msdn
Stand-By keeps your "state" alive by keeping it in RAM. As a consequence if you lose power you'll lose your stored "state".
But it makes it quicker to achieve.
Hibernation stores your "state" in virtual RAM on the hard disk, so if you lose power you can still come back three days later. But it's slower.
I guess a limitation with Stand-By is how much RAM you've got, but I'm sure virtual RAM must be employed by Stand-By when it runs out of standard RAM. I'll look that up though and get back!
The Wikipedia article on ACPI contains the details about the different power savings modes which are present in modern PCs.
Here's the basic idea, from how I understand things:
The basic idea is to keep the current state of the system persisted, so when the machine is brought back into operation, it can resume at the state it was before the machine was put into sleep/standby/hibernation, etc. Think of it as serialization for your PC.
In standby, the computer will keep feeding power to the RAM, as the main memory is volatile memory that needs constant refreshing to hold on to its state. This means that the hard drives, CPU, and other components can be turned off, as long as there is enough power to keep the DRAM refreshed to keep its contents from disappearing.
In hibernation, the main memory will also be turned off, so the contents must be copied to permanent storage, such as a hard drive, before the system power is turned off. Other than that, the basic premise of hiberation is no different from standby -- to store the current state of the machine to restore at a later time.
With that in mind, it's probably not too likely that going into standby or hibernate will cause problems with tasks that are executing at the moment. However, it may not be a good idea to allow network activity to stop in the middle of execution, as depending on the protocol, your network connection could timeout and be unable to resume upon returning the system to its running state.
Also, there may be some machines that just have flaky power-savings drivers which may cause it to go to standby and never come back, but that's completely a different issue.
There are some implications for your code. Hibernation is more than just a context switch from the scheduler. Network connections will be closed, network drives or removable media might be disconnected during the hibernation, ...
I dont think your application can be notified of hibernation (but I might be wrong). What you should do is handle error scenarios (loss of network connectivity for example) as gracefully as possible. And note that those error scenario can occur during normal operation as well, not only when going into hibernation ...
I've been programming a long time, and the programs I see, when they run out of memory, attempt to clean up and exit, i.e. fail gracefully. I can't remember the last time I saw one actually attempt to recover and continue operating normally.
So much processing relies on being able to successfully allocate memory, especially in garbage collected languages, it seems that out of memory errors should be classified as non-recoverable. (Non-recoverable errors include things like stack overflows.)
What is the compelling argument for making it a recoverable error?
It really depends on what you're building.
It's not entirely unreasonable for a webserver to fail one request/response pair but then keep on going for further requests. You'd have to be sure that the single failure didn't have detrimental effects on the global state, however - that would be the tricky bit. Given that a failure causes an exception in most managed environments (e.g. .NET and Java) I suspect that if the exception is handled in "user code" it would be recoverable for future requests - e.g. if one request tried to allocate 10GB of memory and failed, that shouldn't harm the rest of the system. If the system runs out of memory while trying to hand off the request to the user code, however - that kind of thing could be nastier.
In a library, you want to efficiently copy a file. When you do that, you'll usually find that copying using a small number of big chunks is much more effective than copying a lot of smaller ones (say, it's faster to copy a 15MB file by copying 15 1MB chunks than copying 15'000 1K chunks).
But the code works with any chunk size. So while it may be faster with 1MB chunks, if you design for a system where a lot of files are copied, it may be wise to catch OutOfMemoryError and reduce the chunk size until you succeed.
Another place is a cache for Object stored in a database. You want to keep as many objects in the cache as possible but you don't want to interfere with the rest of the application. Since these objects can be recreated, it's a smart way to conserve memory to attach the cache to an out of memory handler to drop entries until the rest of the app has enough room to breathe, again.
Lastly, for image manipulation, you want to load as much of the image into memory as possible. Again, an OOM-handler allows you to implement that without knowing in advance how much memory the user or OS will grant your code.
[EDIT] Note that I work under the assumption here that you've given the application a fixed amount of memory and this amount is smaller than the total available memory excluding swap space. If you can allocate so much memory that part of it has to be swapped out, several of my comments don't make sense anymore.
Users of MATLAB run out of memory all the time when performing arithmetic with large arrays. For example if variable x fits in memory and they run "x+1" then MATLAB allocates space for the result and then fills it. If the allocation fails MATLAB errors and the user can try something else. It would be a disaster if MATLAB exited whenever this use case came up.
OOM should be recoverable because shutdown isn't the only strategy to recovering from OOM.
There is actually a pretty standard solution to the OOM problem at the application level.
As part of you application design determine a safe minimum amount of memory required to recover from an out of memory condition. (Eg. the memory required to auto save documents, bring up warning dialogs, log shutdown data).
At the start of your application or at the start of a critical block, pre-allocate that amount of memory. If you detect an out of memory condition release your guard memory and perform recovery. The strategy can still fail but on the whole gives great bang for the buck.
Note that the application need not shut down. It can display a modal dialog until the OOM condition has been resolved.
I'm not 100% certain but I'm pretty sure 'Code Complete' (required reading for any respectable software engineer) covers this.
P.S. You can extend your application framework to help with this strategy but please don't implement such a policy in a library (good libraries do not make global decisions without an applications consent)
I think that like many things, it's a cost/benefit analysis. You can program in attempted recovery from a malloc() failure - although it may be difficult (your handler had better not fall foul of the same memory shortage it's meant to deal with).
You've already noted that the commonest case is to clean up and fail gracefully. In that case it's been decided that the cost of aborting gracefully is lower than the combination of development cost and performance cost in recovering.
I'm sure you can think of your own examples of situations where terminating the program is a very expensive option (life support machine, spaceship control, long-running and time-critical financial calculation etc.) - although the first line of defence is of course to ensure that the program has predictable memory usage and that the environment can supply that.
I'm working on a system that allocates memory for IO cache to increase performance. Then, on detecting OOM, it takes some of it back, so that the business logic could proceed, even if that means less IO cache and slightly lower write performance.
I also worked with an embedded Java applications that attempted to manage OOM by forcing garbage collection, optionally releasing some of non-critical objects, like pre-fetched or cached data.
The main problems with OOM handling are:
1) being able to re-try in the place where it happened or being able to roll back and re-try from a higher point. Most contemporary programs rely too much on the language to throw and don't really manage where they end up and how to re-try the operation. Usually the context of the operation will be lost, if it wasn't designed to be preserved
2) being able to actually release some memory. This means a kind of resource manager that knows what objects are critical and what are not, and the system be able to re-request the released objects when and if they later become critical
Another important issue is to be able to roll back without triggering yet another OOM situation. This is something that is hard to control in higher level languages.
Also, the underlying OS must behave predictably with regard to OOM. Linux, for example, will not, if memory overcommit is enabled. Many swap-enabled systems will die sooner than reporting the OOM to the offending application.
And, there's the case when it is not your process that created the situation, so releasing memory does not help if the offending process continues to leak.
Because of all this, it's often the big and embedded systems that employ this techniques, for they have the control over OS and memory to enable them, and the discipline/motivation to implement them.
It is recoverable only if you catch it and handle it correctly.
In same cases, for example, a request tried to allocate a lot memory. It is quite predictable and you can handle it very very well.
However, in many cases in multi-thread application, OOE may also happen on background thread (including created by system/3rd-party library).
It is almost imposable to predict and you may unable to recover the state of all your threads.
No.
An out of memory error from the GC is should not generally be recoverable inside of the current thread. (Recoverable thread (user or kernel) creation and termination should be supported though)
Regarding the counter examples: I'm currently working on a D programming language project which uses NVIDIA's CUDA platform for GPU computing. Instead of manually managing GPU memory, I've created proxy objects to leverage the D's GC. So when the GPU returns an out of memory error, I run a full collect and only raise an exception if it fails a second time. But, this isn't really an example of out of memory recovery, it's more one of GC integration. The other examples of recovery (caches, free-lists, stacks/hashes without auto-shrinking, etc) are all structures that have their own methods of collecting/compacting memory which are separate from the GC and tend not to be local to the allocating function.
So people might implement something like the following:
T new2(T)( lazy T old_new ) {
T obj;
try{
obj = old_new;
}catch(OutOfMemoryException oome) {
foreach(compact; Global_List_Of_Delegates_From_Compatible_Objects)
compact();
obj = old_new;
}
return obj;
}
Which is a decent argument for adding support for registering/unregistering self-collecting/compacting objects to garbage collectors in general.
In the general case, it's not recoverable.
However, if your system includes some form of dynamic caching, an out-of-memory handler can often dump the oldest elements in the cache (or even the whole cache).
Of course, you have to make sure that the "dumping" process requires no new memory allocations :) Also, it can be tricky to recover the specific allocation that failed, unless you're able to plug your cache dumping code directly at the allocator level, so that the failure isn't propagated up to the caller.
It depends on what you mean by running out of memory.
When malloc() fails on most systems, it's because you've run out of address-space.
If most of that memory is taken by cacheing, or by mmap'd regions, you might be able to reclaim some of it by freeing your cache or unmmaping. However this really requires that you know what you're using that memory for- and as you've noticed either most programs don't, or it doesn't make a difference.
If you used setrlimit() on yourself (to protect against unforseen attacks, perhaps, or maybe root did it to you), you can relax the limit in your error handler. I do this very frequently- after prompting the user if possible, and logging the event.
On the other hand, catching stack overflow is a bit more difficult, and isn't portable. I wrote a posixish solution for ECL, and described a Windows implementation, if you're going this route. It was checked into ECL a few months ago, but I can dig up the original patches if you're interested.
Especially in garbage collected environments, it's quote likely that if you catch the OutOfMemory error at a high level of the application, lots of stuff has gone out of scope and can be reclaimed to give you back memory.
In the case of single excessive allocations, the app may be able to continue working flawlessly. Of course, if you have a gradual memory leak, you'll just run into the problem again (more likely sooner than later), but it's still a good idea to give the app a chance to go down gracefully, save unsaved changes in the case of a GUI app, etc.
Yes, OOM is recoverable. As an extreme example, the Unix and Windows operating systems recover quite nicely from OOM conditions, most of the time. The applications fail, but the OS survives (assuming there is enough memory for the OS to properly start up in the first place).
I only cite this example to show that it can be done.
The problem of dealing with OOM is really dependent on your program and environment.
For example, in many cases the place where the OOM happens most likely is NOT the best place to actually recover from an OOM state.
Now, a custom allocator could possibly work as a central point within the code that can handle an OOM. The Java allocator will perform a full GC before is actually throws a OOM exception.
The more "application aware" that your allocator is, the better suited it would be as a central handler and recovery agent for OOM. Using Java again, it's allocator isn't particularly application aware.
This is where something like Java is readily frustrating. You can't override the allocator. So, while you could trap OOM exceptions in your own code, there's nothing saying that some library you're using is properly trapping, or even properly THROWING an OOM exception. It's trivial to create a class that is forever ruined by a OOM exception, as some object gets set to null and "that never happen", and it's never recoverable.
So, yes, OOM is recoverable, but it can be VERY hard, particularly in modern environments like Java and it's plethora of 3rd party libraries of various quality.
The question is tagged "language-agnostic", but it's difficult to answer without considering the language and/or the underlying system. (I see several toher hadns
If memory allocation is implicit, with no mechanism to detect whether a given allocation succeeded or not, then recovering from an out-of-memory condition may be difficult or impossible.
For example, if you call a function that attempts to allocate a huge array, most languages just don't define the behavior if the array can't be allocated. (In Ada this raises a Storage_Error exception, at least in principle, and it should be possible to handle that.)
On the other hand, if you have a mechanism that attempts to allocate memory and is able to report a failure to do so (like C's malloc() or C++'s new), then yes, it's certainly possible to recover from that failure. In at least the cases of malloc() and new, a failed allocation doesn't do anything other than report failure (it doesn't corrupt any internal data structures, for example).
Whether it makes sense to try to recover depends on the application. If the application just can't succeed after an allocation failure, then it should do whatever cleanup it can and terminate. But if the allocation failure merely means that one particular task cannot be performed, or if the task can still be performed more slowly with less memory, then it makes sense to continue operating.
A concrete example: Suppose I'm using a text editor. If I try to perform some operation within the editor that requires a lot of memory, and that operation can't be performed, I want the editor to tell me it can't do what I asked and let me keep editing. Terminating without saving my work would be an unacceptable response. Saving my work and terminating would be better, but is still unnecessarily user-hostile.
This is a difficult question. On first sight it seems having no more memory means "out of luck" but, you must also see that one can get rid of many memory related stuff if one really insist. Let's just take the in other ways broken function strtok which on one hand has no problems with memory stuff. Then take as counterpart g_string_split from the Glib library, which heavily depends on allocation of memory as nearly everything in glib or GObject based programs. One can definitly say in more dynamic languages memory allocation is much more used as in more inflexible languages, especially C. But let us see the alternatives. If you just end the program if you run out of memory, even careful developed code may stop working. But if you have a recoverable error, you can do something about it. So the argument, making it recoverable means that one can choose to "handle" that situation differently (e.g putting aside a memory block for emergencies, or degradation to a less memory extensive program).
So the most compelling reason is. If you provide a way of recovering one can try the recoverying, if you do not have the choice all depends on always getting enough memory...
Regards
It's just puzzling me now.
At work, we have a bundle of applications working together, and memory is running low. While the problem is either make the application bundle go 64-bit (and so, be able to work beyond the 2 Go limits we have on a normal Win32 OS), and/or reduce our use of memory, this problem of "How to recover from a OOM" won't quit my head.
Of course, I have no solution, but still play at searching for one for C++ (because of RAII and exceptions, mainly).
Perhaps a process supposed to recover gracefully should break down its processing in atomic/rollback-able tasks (i.e. using only functions/methods giving strong/nothrow exception guarantee), with a "buffer/pool of memory" reserved for recovering purposes.
Should one of the task fails, the C++ bad_alloc would unwind the stack, free some stack/heap memory through RAII. The recovering feature would then salvage as much as possible (saving the initial data of the task on the disk, to use on a later try), and perhaps register the task data for later try.
I do believe the use of C++ strong/nothrow guanrantees can help a process to survive in low-available-memory conditions, even if it would be akin memory swapping (i.e. slow, somewhat unresponding, etc.), but of course, this is only theory. I just need to get smarter on the subject before trying to simulate this (i.e. creating a C++ program, with a custom new/delete allocator with limited memory, and then try to do some work under those stressful condition).
Well...
Out of memory normally means you have to quit whatever you were doing. If you are careful about cleanup, though, it can leave the program itself operational and able to respond to other requests. It's better to have a program say "Sorry, not enough memory to do " than say "Sorry, out of memory, shutting down."
Out of memory can be caused either by free memory depletion or by trying to allocate an unreasonably big block (like one gig). In "depletion" cases memory shortage is global to the system and usually affects other applications and system services and the whole system might become unstable so it's wise to forget and reboot. In "unreasonably big block" cases no shortage actually occurs and it's safe to continue. The problem is you can't automatically detect which case you're in. So it's safer to make the error non-recoverable and find a workaround for each case you encounter this error - make your program use less memory or in some cases just fix bugs in code that invokes memory allocation.
There are already many good answers here. But I'd like to contribute with another perspective.
Depletion of just about any reusable resource should be recoverable in general. The reasoning is that each and every part of a program is basically a sub program. Just because one sub cannot complete to it's end at this very point in time, does not mean that the entire state of the program is garbage. Just because the parking lot is full of cars does not mean that you trash your car. Either you wait a while for a booth to be free, or you drive to a store further away to buy your cookies.
In most cases there is an alternative way. Making an out of error unrecoverable, effectively removes a lot of options, and none of us like to have anyone decide for us what we can and cannot do.
The same applies to disk space. It's really the same reasoning. And contrary to your insinuation about stack overflow is unrecoverable, i would say that it's and arbitrary limitation. There is no good reason that you should not be able to throw an exception (popping a lot of frames) and then use another less efficient approach to get the job done.
My two cents :-)
If you are really out of memory you are doomed, since you can not free anything anymore.
If you are out of memory, but something like a garbage collector can kick in and free up some memory you are non dead yet.
The other problem is fragmentation. Although you might not be out of memory (fragmented), you might still not be able to allocate the huge chunk you wanna have.
I know you asked for arguments for, but I can only see arguments against.
I don't see anyway to achieve this in a multi-threaded application. How do you know which thread is actually responsible for the out-of-memory error? One thread could allocating new memory constantly and have gc-roots to 99% of the heap, but the first allocation that fails occurs in another thread.
A practical example: whenever I have occurred an OutOfMemoryError in our Java application (running on a JBoss server), it's not like one thread dies and the rest of the server continues to run: no, there are several OOMEs, killing several threads (some of which are JBoss' internal threads). I don't see what I as a programmer could do to recover from that - or even what JBoss could do to recover from it. In fact, I am not even sure you CAN: the javadoc for VirtualMachineError suggests that the JVM may be "broken" after such an error is thrown. But maybe the question was more targeted at language design.
uClibc has an internal static buffer of 8 bytes or so for file I/O when there is no more memory to be allocated dynamically.
What is the compelling argument for making it a recoverable error?
In Java, a compelling argument for not making it a recoverable error is because Java allows OOM to be signalled at any time, including at times where the result could be your program entering an inconsistent state. Reliable recoery from an OOM is therefore impossible; if you catch the OOM exception, you can not rely on any of your program state. See
No-throw VirtualMachineError guarantees
I'm working on SpiderMonkey, the JavaScript VM used in Firefox (and gnome and a few others). When you're out of memory, you may want to do any of the following things:
Run the garbage-collector. We don't run the garbage-collector all the time, as it would kill performance and battery, so by the time you're reaching out of memory error, some garbage may have accumulated.
Free memory. For instance, get rid of some of the in-memory cache.
Kill or postpone non-essential tasks. For instance, unload some tabs that haven't be used in a long time from memory.
Log things to help the developer troubleshoot the out-of-memory error.
Display a semi-nice error message to let the user know what's going on.
...
So yes, there are many reasons to handle out-of-memory errors manually!
I have this:
void *smalloc(size_t size) {
void *mem = null;
for(;;) {
mem = malloc(size);
if(mem == NULL) {
sleep(1);
} else
break;
}
return mem;
}
Which has saved a system a few times already. Just because you're out of memory now, doesn't mean some other part of the system or other processes running on the system have some memory they'll give back soon. You better be very very careful before attempting such tricks, and have all control over every memory you do allocate in your program though.