Related
Consider this simple example program that puts ints into a list:
void Main()
{
Experiment experiment = new();
var task = Task.Run(experiment.Start);
}
public class Experiment
{
public async Task Start()
{
List<int> values = new();
for (int i = 0; i < 1000000000; i++)
values.Add(i);
await Task.CompletedTask;
}
}
When run this uses about 7 GB of memory. But then that data just stays there. Even if I clear the list or set it to null, the program still takes up 7 GB. When I run it again, the RAM usage suddenly goes down to 10 MB and then shoots up to 7 GB again, making me think that only if I start a new tasks with this method, the data is actually released.
Why does the memory not get released when the task is done? I don't understand why the list is not temporary and keeps occupying memory. What am I doing wrong?
.NET uses garbage collection to release unused memory.
Garbage collection is more likely to run when memory is getting low. But other than that, there is no way to predict when it will run, or when your memory will be released.
In either case, garbage collection does not run as soon as the memory is no longer needed (or when the task is done in your case).
This is normal behavior. When you're running low on memory, garbage collection should take care of it soon enough.
Maybe add task.Wait() in the main program. I think as written the main program exits before the the task is complete. Maybe the task still is referenced when it exits therefore slowing down the gc.
The general advice is that you should not call GC.Collect from your code, but what are the exceptions to this rule?
I can only think of a few very specific cases where it may make sense to force a garbage collection.
One example that springs to mind is a service, that wakes up at intervals, performs some task, and then sleeps for a long time. In this case, it may be a good idea to force a collect to prevent the soon-to-be-idle process from holding on to more memory than needed.
Are there any other cases where it is acceptable to call GC.Collect?
If you have good reason to believe that a significant set of objects - particularly those you suspect to be in generations 1 and 2 - are now eligible for garbage collection, and that now would be an appropriate time to collect in terms of the small performance hit.
A good example of this is if you've just closed a large form. You know that all the UI controls can now be garbage collected, and a very short pause as the form is closed probably won't be noticeable to the user.
UPDATE 2.7.2018
As of .NET 4.5 - there is GCLatencyMode.LowLatency and GCLatencyMode.SustainedLowLatency. When entering and leaving either of these modes, it is recommended that you force a full GC with GC.Collect(2, GCCollectionMode.Forced).
As of .NET 4.6 - there is the GC.TryStartNoGCRegion method (used to set the read-only value GCLatencyMode.NoGCRegion). This can itself, perform a full blocking garbage collection in an attempt to free enough memory, but given we are disallowing GC for a period, I would argue it is also a good idea to perform full GC before and after.
Source: Microsoft engineer Ben Watson's: Writing High-Performance .NET Code, 2nd Ed. 2018.
See:
https://msdn.microsoft.com/en-us/library/system.runtime.gclatencymode(v=vs.110).aspx
https://msdn.microsoft.com/en-us/library/dn906204(v=vs.110).aspx
I use GC.Collect only when writing crude performance/profiler test rigs; i.e. I have two (or more) blocks of code to test - something like:
GC.Collect(GC.MaxGeneration, GCCollectionMode.Forced);
TestA(); // may allocate lots of transient objects
GC.Collect(GC.MaxGeneration, GCCollectionMode.Forced);
TestB(); // may allocate lots of transient objects
GC.Collect(GC.MaxGeneration, GCCollectionMode.Forced);
...
So that TestA() and TestB() run with as similar state as possible - i.e. TestB() doesn't get hammered just because TestA left it very close to the tipping point.
A classic example would be a simple console exe (a Main method sort-enough to be posted here for example), that shows the difference between looped string concatenation and StringBuilder.
If I need something precise, then this would be two completely independent tests - but often this is enough if we just want to minimize (or normalize) the GC during the tests to get a rough feel for the behaviour.
During production code? I have yet to use it ;-p
The best practise is to not force a garbage collection in most cases. (Every system I have worked on that had forced garbage collections, had underlining problems that if solved would have removed the need to forced the garbage collection, and speeded the system up greatly.)
There are a few cases when you know more about memory usage then the garbage collector does. This is unlikely to be true in a multi user application, or a service that is responding to more then one request at a time.
However in some batch type processing you do know more then the GC. E.g. consider an application that.
Is given a list of file names on the command line
Processes a single file then write the result out to a results file.
While processing the file, creates a lot of interlinked objects that can not be collected until the processing of the file have complete (e.g. a parse tree)
Does not keep match state between the files it has processed.
You may be able to make a case (after careful) testing that you should force a full garbage collection after you have process each file.
Another cases is a service that wakes up every few minutes to process some items, and does not keep any state while it’s asleep. Then forcing a full collection just before going to sleep may be worthwhile.
The only time I would consider forcing
a collection is when I know that a lot
of object had been created recently
and very few objects are currently
referenced.
I would rather have a garbage collection API when I could give it hints about this type of thing without having to force a GC my self.
See also "Rico Mariani's Performance Tidbits"
These days I consider same of the above cases would be better to use a short lived worker process to do each batch of work and let the OS do the resource recovery.
One case is when you are trying to unit test code that uses WeakReference.
In large 24/7 or 24/6 systems -- systems that react to messages, RPC requests or that poll a database or process continuously -- it is useful to have a way to identify memory leaks. For this, I tend to add a mechanism to the application to temporarily suspend any processing and then perform full garbage collection. This puts the system into a quiescent state where the memory remaining is either legitimately long lived memory (caches, configuration, &c.) or else is 'leaked' (objects that are not expected or desired to be rooted but actually are).
Having this mechanism makes it a lot easier to profile memory usage as the reports will not be clouded with noise from active processing.
To be sure you get all of the garbage, you need to perform two collections:
GC.Collect();
GC.WaitForPendingFinalizers();
GC.Collect();
As the first collection will cause any objects with finalizers to be finalized (but not actually garbage collect these objects). The second GC will garbage collect these finalized objects.
You can call GC.Collect() when you know something about the nature of the app the garbage collector doesn't.
As the author, it's often tempting to think this is likely or normal. However, the truth is the GC amounts to a pretty well-written and tested expert system, and it's rare you'll know something about the low level code paths it doesn't.
The best example I can think of where you might have some extra information is an app that cycles between idle periods and very busy periods. You want the best performance possible for the busy periods and therefore want to use the idle time to do some clean up.
However, most of the time the GC is smart enough to do this anyway.
One instance where it is almost necessary to call GC.Collect() is when automating Microsoft Office through Interop. COM objects for Office don't like to automatically release and can result in the instances of the Office product taking up very large amounts of memory. I'm not sure if this is an issue or by design. There's lots of posts about this topic around the internet so I won't go into too much detail.
When programming using Interop, every single COM object should be manually released, usually though the use of Marshal.ReleseComObject(). In addition, calling Garbage Collection manually can help "clean up" a bit. Calling the following code when you're done with Interop objects seems to help quite a bit:
GC.Collect()
GC.WaitForPendingFinalizers()
GC.Collect()
In my personal experience, using a combination of ReleaseComObject and manually calling garbage collection greatly reduces the memory usage of Office products, specifically Excel.
As a memory fragmentation solution.
I was getting out of memory exceptions while writing a lot of data into a memory stream (reading from a network stream). The data was written in 8K chunks. After reaching 128M there was exception even though there was a lot of memory available (but it was fragmented). Calling GC.Collect() solved the issue. I was able to handle over 1G after the fix.
Have a look at this article by Rico Mariani. He gives two rules when to call GC.Collect (rule 1 is: "Don't"):
When to call GC.Collect()
I was doing some performance testing on array and list:
private static int count = 100000000;
private static List<int> GetSomeNumbers_List_int()
{
var lstNumbers = new List<int>();
for(var i = 1; i <= count; i++)
{
lstNumbers.Add(i);
}
return lstNumbers;
}
private static int[] GetSomeNumbers_Array()
{
var lstNumbers = new int[count];
for (var i = 1; i <= count; i++)
{
lstNumbers[i-1] = i + 1;
}
return lstNumbers;
}
private static int[] GetSomeNumbers_Enumerable_Range()
{
return Enumerable.Range(1, count).ToArray();
}
static void performance_100_Million()
{
var sw = new Stopwatch();
sw.Start();
var numbers1 = GetSomeNumbers_List_int();
sw.Stop();
//numbers1 = null;
//GC.Collect();
Console.WriteLine(String.Format("\"List<int>\" took {0} milliseconds", sw.ElapsedMilliseconds));
sw.Reset();
sw.Start();
var numbers2 = GetSomeNumbers_Array();
sw.Stop();
//numbers2 = null;
//GC.Collect();
Console.WriteLine(String.Format("\"int[]\" took {0} milliseconds", sw.ElapsedMilliseconds));
sw.Reset();
sw.Start();
//getting System.OutOfMemoryException in GetSomeNumbers_Enumerable_Range method
var numbers3 = GetSomeNumbers_Enumerable_Range();
sw.Stop();
//numbers3 = null;
//GC.Collect();
Console.WriteLine(String.Format("\"int[]\" Enumerable.Range took {0} milliseconds", sw.ElapsedMilliseconds));
}
and I got OutOfMemoryException in GetSomeNumbers_Enumerable_Range method the only workaround is to deallocate the memory by:
numbers = null;
GC.Collect();
You should try to avoid using GC.Collect() since its very expensive. Here is an example:
public void ClearFrame(ulong timeStamp)
{
if (RecordSet.Count <= 0) return;
if (Limit == false)
{
var seconds = (timeStamp - RecordSet[0].TimeStamp)/1000;
if (seconds <= _preFramesTime) return;
Limit = true;
do
{
RecordSet.Remove(RecordSet[0]);
} while (((timeStamp - RecordSet[0].TimeStamp) / 1000) > _preFramesTime);
}
else
{
RecordSet.Remove(RecordSet[0]);
}
GC.Collect(); // AVOID
}
TEST RESULT: CPU USAGE 12%
When you change to this:
public void ClearFrame(ulong timeStamp)
{
if (RecordSet.Count <= 0) return;
if (Limit == false)
{
var seconds = (timeStamp - RecordSet[0].TimeStamp)/1000;
if (seconds <= _preFramesTime) return;
Limit = true;
do
{
RecordSet[0].Dispose(); // Bitmap destroyed!
RecordSet.Remove(RecordSet[0]);
} while (((timeStamp - RecordSet[0].TimeStamp) / 1000) > _preFramesTime);
}
else
{
RecordSet[0].Dispose(); // Bitmap destroyed!
RecordSet.Remove(RecordSet[0]);
}
//GC.Collect();
}
TEST RESULT: CPU USAGE 2-3%
In your example, I think that calling GC.Collect isn't the issue, but rather there is a design issue.
If you are going to wake up at intervals, (set times) then your program should be crafted for a single execution (perform the task once) and then terminate. Then, you set the program up as a scheduled task to run at the scheduled intervals.
This way, you don't have to concern yourself with calling GC.Collect, (which you should rarely if ever, have to do).
That being said, Rico Mariani has a great blog post on this subject, which can be found here:
http://blogs.msdn.com/ricom/archive/2004/11/29/271829.aspx
One useful place to call GC.Collect() is in a unit test when you want to verify that you are not creating a memory leak (e. g. if you are doing something with WeakReferences or ConditionalWeakTable, dynamically generated code, etc).
For example, I have a few tests like:
WeakReference w = CodeThatShouldNotMemoryLeak();
Assert.IsTrue(w.IsAlive);
GC.Collect();
GC.WaitForPendingFinalizers();
Assert.IsFalse(w.IsAlive);
It could be argued that using WeakReferences is a problem in and of itself, but it seems that if you are creating a system that relies on such behavior then calling GC.Collect() is a good way to verify such code.
There are some situations where it is better safe than sorry.
Here is one situation.
It is possible to author an unmanaged DLL in C# using IL rewrites (because there are situations where this is necessary).
Now suppose, for example, the DLL creates an array of bytes at the class level - because many of the exported functions need access to such. What happens when the DLL is unloaded? Is the garbage collector automatically called at that point? I don't know, but being an unmanaged DLL it is entirely possible the GC isn't called. And it would be a big problem if it wasn't called. When the DLL is unloaded so too would be the garbage collector - so who is going to be responsible for collecting any possible garbage and how would they do it? Better to employ C#'s garbage collector. Have a cleanup function (available to the DLL client) where the class level variables are set to null and the garbage collector called.
Better safe than sorry.
The short answer is: never!
using(var stream = new MemoryStream())
{
bitmap.Save(stream, ImageFormat.Png);
techObject.Last().Image = Image.FromStream(stream);
bitmap.Dispose();
// Without this code, I had an OutOfMemory exception.
GC.Collect();
GC.WaitForPendingFinalizers();
//
}
Another reason is when you have a SerialPort opened on a USB COM port, and then the USB device is unplugged. Because the SerialPort was opened, the resource holds a reference to the previously connected port in the system's registry. The system's registry will then contain stale data, so the list of available ports will be wrong. Therefore the port must be closed.
Calling SerialPort.Close() on the port calls Dispose() on the object, but it remains in memory until garbage collection actually runs, causing the registry to remain stale until the garbage collector decides to release the resource.
From https://stackoverflow.com/a/58810699/8685342:
try
{
if (port != null)
port.Close(); //this will throw an exception if the port was unplugged
}
catch (Exception ex) //of type 'System.IO.IOException'
{
System.GC.Collect();
System.GC.WaitForPendingFinalizers();
}
port = null;
If you are creating a lot of new System.Drawing.Bitmap objects, the Garbage Collector doesn't clear them. Eventually GDI+ will think you are running out of memory and will throw a "The parameter is not valid" exception. Calling GC.Collect() every so often (not too often!) seems to resolve this issue.
i am still pretty unsure about this.
I am working since 7 years on an Application Server. Our bigger installations take use of 24 GB Ram. Its hightly Multithreaded, and ALL calls for GC.Collect() ran into really terrible performance issues.
Many third party Components used GC.Collect() when they thought it was clever to do this right now.
So a simple bunch of Excel-Reports blocked the App Server for all threads several times a minute.
We had to refactor all the 3rd Party Components in order to remove the GC.Collect() calls, and all worked fine after doing this.
But i am running Servers on Win32 as well, and here i started to take heavy use of GC.Collect() after getting a OutOfMemoryException.
But i am also pretty unsure about this, because i often noticed, when i get a OOM on 32 Bit, and i retry to run the same Operation again, without calling GC.Collect(), it just worked fine.
One thing i wonder is the OOM Exception itself...
If i would have written the .Net Framework, and i can't alloc a memory block, i would use GC.Collect(), defrag memory (??), try again, and if i still cant find a free memory block, then i would throw the OOM-Exception.
Or at least make this behavior as configurable option, due the drawbacks of the performance issue with GC.Collect.
Now i have lots of code like this in my app to "solve" the problem:
public static TResult ExecuteOOMAware<T1, T2, TResult>(Func<T1,T2 ,TResult> func, T1 a1, T2 a2)
{
int oomCounter = 0;
int maxOOMRetries = 10;
do
{
try
{
return func(a1, a2);
}
catch (OutOfMemoryException)
{
oomCounter++;
if (maxOOMRetries > 10)
{
throw;
}
else
{
Log.Info("OutOfMemory-Exception caught, Trying to fix. Counter: " + oomCounter.ToString());
System.Threading.Thread.Sleep(TimeSpan.FromSeconds(oomCounter * 10));
GC.Collect();
}
}
} while (oomCounter < maxOOMRetries);
// never gets hitted.
return default(TResult);
}
(Note that the Thread.Sleep() behavior is a really App apecific behavior, because we are running a ORM Caching Service, and the service takes some time to release all the cached objects, if RAM exceeds some predefined values. so it waits a few seconds the first time, and has increased waiting time each occurence of OOM.)
one good reason for calling GC is on small ARM computers with little memory, like the Raspberry PI (running with mono).
If unallocated memory fragments use too much of the system RAM, then the Linux OS can get unstable.
I have an application where I have to call GC every second (!) to get rid of memory overflow problems.
Another good solution is to dispose objects when they are no longer needed. Unfortunately this is not so easy in many cases.
This isn't that relevant to the question, but for XSLT transforms in .NET (XSLCompiledTranform) then you might have no choice. Another candidate is the MSHTML control.
If you are using a version of .net less than 4.5, manual collection may be inevitable (especially if you are dealing with many 'large objects').
this link describes why:
https://blogs.msdn.microsoft.com/dotnet/2011/10/03/large-object-heap-improvements-in-net-4-5/
Since there are Small object heap(SOH) and Large object heap(LOH)
We can call GC.Collect() to clear de-reference object in SOP, and move lived object to next generation.
In .net4.5, we can also compact LOH by using largeobjectheapcompactionmode
In my C#/.NET 3.5 program I am using Threadpool threads ( delegate+BeginInvoke/EndInvoke) to parallelize and speed up some file loading. SystemInternals tool ProcessExplorer shows that number of threads in process is increasing over time, while I would expect to stay the same. Looks like some Threads/Threads handles stay hanging around for no reason.
Interestingly enough, I can not find pattern how threads grow and seems that happen sporadically, without repeatable pattern each time I start application. I spend some time analyzing and here are some observations:
1) code looks like this:
ArrayList IAsyncResult_s = new ArrayList();
AsyncProcessing thread1 = processRasterLayer;
... ArrayList filesToRender....
foreach (string FileName in filesToRender)
{
string fileName2 = FileName;
GeoImage partialImage1;
IAsyncResult asyncResult = thread1.BeginInvoke(
fileName2, .....,
out partialImage1, ..., null, null);
IAsyncResult_s.Add(asyncResult);
asyncResult = null;
}
.................
//block and render all
foreach (IAsyncResult asyncResult in IAsyncResult_s)
{
GeoImage partialImage1;
thread1.EndInvoke(
out partialImage1, , asyncResult);
//render image.. some calls to render partial image here
partialImage1.Dispose();
partialImage1 = null;
}
IAsyncResult_s.Clear();
IAsyncResult_s = null;
thread1 = null;
2) Number of Process Threads
My trace shows that during execution inside loop, ThreadPool.GetAvailableThreads(out workerThreads, out completionPortThreads); gives numbers like 493, 1000.
At the end of loops , , ThreadPool.GetAvailableThreads(out workerThreads, out completionPortThreads); gives numbers 500, 1000. So, number of available thread returns to same
Number of process threads reported by SystemInternals ProcessExplorer and API System.Diagnostics.Process.GetCurrentProcess().Threads.Count is the 16 before loops, and around 21 after loops.
If I call againg those loops, number of threads in process grows, but not by fixed nubmer each time, but grows 1-4 each time I repeat above code, so grows like 16->21->22->26->31...
3)Forced garbage collection didn’t htelp
I tried to froce garbage collection to get rid of those extra threads, but that didn’t removed them from process.
4)Profling tools
I was using RedGates Memory and Performace profilers, but hasen’t found obvious reason. I saw several extra threas and their object (ThreadContext etc) hanging, but saw no object holding those threads in memory. I am prety sure those extra threads were involved into loops work above, since I added thread name inside calls, and they still have that name I gave them.
5) Intelitrace
Intelitrace debuging showed also extra threads hanging. They still have names I gave them. But interestingly, it also showed that same thread that is hanging now, was used by above loop in the past, but also same thread was executing some timer related evens from timers form my code.
6) Locating issue
So, When I disable above loops that process filse Asynchroniously, and load files sequentialy, I do not have extra threads, and number of threads in my application is constant and and around 16.
7) Regarding SetMaxThreads :Here how it looks on my machine (XP, .NET 3.5):
Code like this:
ThreadPool.GetAvailableThreads(out AvailableWorkerThreads, out AvailableCompletionPortThreads);
ThreadPool.GetMaxThreads(out MaxWorkerThreads, out MaxCompletionPortThreads);
ThreadPool.GetMinThreads(out MinWorkerThreads, out MinCompletionPortThreads);
Gives result:
MinWorkerThreads:2 MaxWorkerThreads:500 MinCompletionPortThreads:2 MaxCompletionPortThreads:1000 AvailableWorkerThreads:500 AvailableCompletionPortThreads:1000
My app is using maybe 8 worker threads at the same time. I see no problem with SetMaxThreads.
8)
Functionally, I have no problems so far with this solution above. But somehow, if tools report that number of threads in my app is growing, it looks like “resource leak” of some kind, and I would like to address it. It looks like some thread handles are hanging around for no reason.
9) Here is one interesting article. It sasy that thread resources are cleaned once EndInvoke is called. I am doing so in my code. Article sasy: ..”. Because EndInvoke cleans up after the spawned thread, you must make sure that an EndInvoke is called for each BeginInvoke.” “If the thread pool thread has exited, EndInvoke does the following: It cleans up the exited thread's loose ends and disposes of its resources.” See: http://en.csharp-online.net/Asynchronous_Programming%E2%80%94BeginInvoke_EndInvoke
10) Another interesting article. Author says he had thread handle leaks because he was creating controls from non-gui thread. It is pretty elaborate article, see: http://msmvps.com/blogs/senthil/archive/2008/05/29/the-case-of-the-leaking-thread-handles.aspx
11) Another interesting article. It talks about ThreadPool.SetMinThreads property. It seems that it is not ThreadPool.SetMaxThreads but ThreadPool.SetMinThreads that enables useful control over ThradPool. This article is an eye-opener for me, and made me think about how ThreadPool works and performance problems it might cause. Article is: http_://www.dotnetperls.com/threadpool-setminthreads . Anoter similar one is : http_://www.codeproject.com/Articles/3813/NET-s-ThreadPool-Class-Behind-The-Scenes
12) Another interesting article. It is talking about throttling issue with ThreadPool. Article mentions ThreadPool limit of 2 new threads per second increase. See http_://social. msdn. microsoft. com/forums/en-US/clr/thread/3325cb32-371b-4f3e-965f-6ca88538dc3e/
13) So, in maybe 30 tests I saw only 2 times that number of threads allocated would shrink. But, it did happen. I saw once thread number going like 16->....->31->61-> ->30->16. So, it went back to 16. It doesn’t happen often, and it is not about time waited, it was like big activity in process, followed by a period of constant low level activity.
14) ThreadPool.SetMinThreads Method documentation. It talks about 2 new threads per second limit for threadpool. It is not clear if setting this property would remove that limit. http_://msdn.microsoft. com/en-ca/library/system. threading.threadpool.setminthreads(v=vs.90).aspx
So the answer is: there's no leak here. This is how the thread pool works. It keeps around threads that finished working so you don't have to pay the price of thread creation next time you need one. If you have many concurrent work items then the number of threads in the pool will increase but they'll max out at MaxWorkerThreads. (And it has nothing to do with the garbage collector.)
See this article for more info:
http://msdn.microsoft.com/en-us/library/0ka9477y.aspx
i would consider a consumer producer pattern. the idea behind a threadpool is to recycle threads, not create hundreds of new. in best case you have for each cpu one thread, and queue the work. this will be sure faster as you avoid useless context switches and waits for creating new threads, as far as i remember the net threadpool waits about one second until a new thread is created, to give other threads a chance to get recycled.
I've started to review some code in a project and found something like this:
GC.Collect();
GC.WaitForPendingFinalizers();
Those lines usually appear on methods that are conceived to destruct the object under the rationale of increase efficiency. I've made this remarks:
To call garbage collection explicitly on the destruction of every object decreases performance because doing so does not take into account if it is absolutely necessary for CLR performance.
Calling those instructions in that order causes every object to be destroyed only if other objects are being finalized. Therefore, an object that could be destroyed independently has to wait for another object's destruction without a real necessity.
It can generate a deadlock (see: this question)
Are 1, 2 and 3 true? Can you give some reference supporting your answers?
Although I'm almost sure about my remarks, I need to be clear in my arguments in order to explain to my team why is this a problem. That's the reason I'm asking for confirmation and reference.
The short answer is: take it out. That code will almost never improve performance, or long-term memory use.
All your points are true. (It can generate a deadlock; that does not mean it always will.) Calling GC.Collect() will collect the memory of all GC generations. This does two things.
It collects across all generations every time - instead of what the GC will do by default, which is to only collect a generation when it is full. Typical use will see Gen0 collecting (roughly) ten times as often than Gen1, which in turn collects (roughly) ten times as often as Gen2. This code will collect all generations every time. Gen0 collection is typically sub-100ms; Gen2 can be much longer.
It promotes non-collectable objects to the next generation. That is, every time you force a collection and you still have a reference to some object, that object will be promoted to the subsequent generation. Typically this will happen relatively rarely, but code such as the below will force this far more often:
void SomeMethod()
{
object o1 = new Object();
object o2 = new Object();
o1.ToString();
GC.Collect(); // this forces o2 into Gen1, because it's still referenced
o2.ToString();
}
Without a GC.Collect(), both of these items will be collected at the next opportunity. With the collection as writte, o2 will end up in Gen1 - which means an automated Gen0 collection won't release that memory.
It's also worth noting an even bigger horror: in DEBUG mode, the GC functions differently and won't reclaim any variable that is still in scope (even if it's not used later in the current method). So in DEBUG mode, the code above wouldn't even collect o1 when calling GC.Collect, and so both o1 and o2 will be promoted. This could lead to some very erratic and unexpected memory usage when debugging code. (Articles such as this highlight this behaviour.)
EDIT: Having just tested this behaviour, some real irony: if you have a method something like this:
void CleanUp(Thing someObject)
{
someObject.TidyUp();
someObject = null;
GC.Collect();
GC.WaitForPendingFinalizers();
}
... then it will explicitly NOT release the memory of someObject, even in RELEASE mode: it'll promote it into the next GC generation.
There is a point one can make that is very easy to understand: Having GC run automatically cleans up many objects per run (say, 10000). Calling it after every destruction cleans up about one object per run.
Because GC has high overhead (needs to stop and start threads, needs to scan all objects alive) batching calls is highly preferable.
Also, what good could come out of cleaning up after every object? How could this be more efficient than batching?
Your point number 3 is technically correct, but can only happen if someone locks during a finaliser.
Even without this sort of call, locking inside a finaliser is even worse than what you have here.
There are a handful of times when calling GC.Collect() really does help performance.
So far I've done so 2, maybe 3 times in my career. (Or maybe about 5 or 6 times if you include those where I did it, measured the results, and then took it out again - and this is something you should always measure after doing).
In cases where you're churning through hundreds or thousands of megs of memory in a short period of time, and then switching over to much less intensive use of memory for a long period of time, it can be a massive or even vital improvement to explicitly collect. Is that what's happening here?
Anywhere else, they're at best going to make it slower and use more memory.
See my other answer here:
To GC.Collect or not?
two things can happen when you call GC.Collect() yourself: you end up spending more time doing collections (because the normal background collections will still happen in addition to your manual GC.Collect()) and you'll hang on to the memory longer (because you forced some things into a higher order generation that didn't need to go there). In other words, using GC.Collect() yourself is almost always a bad idea.
About the only time you ever want to call GC.Collect() yourself is when you have specific information about your program that is hard for the Garbage Collector to know. The canonical example is a long-running program with distinct busy and light load cycles. You may want to force a collection near the end of a period of light load, ahead of a busy cycle, to make sure resources are as free as possible for the busy cycle. But even here, you might find you do better by re-thinking how your app is built (ie, would a scheduled task work better?).
We have run into similar problems to #Grzenio however we are working with much larger 2-dimensional arrays, in the order of 1000x1000 to 3000x3000, this is in a webservice.
Adding more memory isn't always the right answer, you have to understand your code and the use case. Without GC collecting we require 16-32gb of memory (depending on customer size). Without it we would require 32-64gb of memory and even then there are no guarantees the system won't suffer. The .NET garbage collector is not perfect.
Our webservice has an in-memory cache in the order of 5-50 million string (~80-140 characters per key/value pair depending on configuration), in addition with each client request we would construct 2 matrices one of double, one of boolean which were then passed to another service to do the work. For a 1000x1000 "matrix" (2-dimensional array) this is ~25mb, per request. The boolean would say which elements we need (based on our cache). Each cache entry represents one "cell" in the "matrix".
The cache performance dramatically degrades when the server has > 80% memory utilization due to paging.
What we found is that unless we explicitly GC the .net garbage collector would never 'cleanup' the transitory variables until we were in the 90-95% range by which point the cache performance had drastically degraded.
Since the down-stream process often took a long duration (3-900 seconds) the performance hit of a GC collection was neglible (3-10 seconds per collect). We initiated this collect after we had already returned the response to the client.
Ultimately we made the GC parameters configurable, also with .net 4.6 there are further options. Here is the .net 4.5 code we used.
if (sinceLastGC.Minutes > Service.g_GCMinutes)
{
Service.g_LastGCTime = DateTime.Now;
var sw = Stopwatch.StartNew();
long memBefore = System.GC.GetTotalMemory(false);
context.Response.Flush();
context.ApplicationInstance.CompleteRequest();
System.GC.Collect( Service.g_GCGeneration, Service.g_GCForced ? System.GCCollectionMode.Forced : System.GCCollectionMode.Optimized);
System.GC.WaitForPendingFinalizers();
long memAfter = System.GC.GetTotalMemory(true);
var elapsed = sw.ElapsedMilliseconds;
Log.Info(string.Format("GC starts with {0} bytes, ends with {1} bytes, GC time {2} (ms)", memBefore, memAfter, elapsed));
}
After rewriting for use with .net 4.6 we split the garbage colleciton into 2 steps - a simple collect and a compacting collect.
public static RunGC(GCParameters param = null)
{
lock (GCLock)
{
var theParams = param ?? GCParams;
var sw = Stopwatch.StartNew();
var timestamp = DateTime.Now;
long memBefore = GC.GetTotalMemory(false);
GC.Collect(theParams.Generation, theParams.Mode, theParams.Blocking, theParams.Compacting);
GC.WaitForPendingFinalizers();
//GC.Collect(); // may need to collect dead objects created by the finalizers
var elapsed = sw.ElapsedMilliseconds;
long memAfter = GC.GetTotalMemory(true);
Log.Info($"GC starts with {memBefore} bytes, ends with {memAfter} bytes, GC time {elapsed} (ms)");
}
}
// https://msdn.microsoft.com/en-us/library/system.runtime.gcsettings.largeobjectheapcompactionmode.aspx
public static RunCompactingGC()
{
lock (CompactingGCLock)
{
var sw = Stopwatch.StartNew();
var timestamp = DateTime.Now;
long memBefore = GC.GetTotalMemory(false);
GCSettings.LargeObjectHeapCompactionMode = GCLargeObjectHeapCompactionMode.CompactOnce;
GC.Collect();
var elapsed = sw.ElapsedMilliseconds;
long memAfter = GC.GetTotalMemory(true);
Log.Info($"Compacting GC starts with {memBefore} bytes, ends with {memAfter} bytes, GC time {elapsed} (ms)");
}
}
Hope this helps someone else as we spent a lot of time researching this.
[Edit] Following up on this, we have found some additional problems with the large matrices. we have started encountering heavy memory pressure and the application suddenly being unable to allocate the arrays, even if the process/server has plenty of memory (24gb free). Upon deeper investigation we discovered that the process had standby memory that was almost 100% of the "in use memory" (24gb in use, 24gb standby, 1gb free). When the "free" memory hit 0 the application would pause for 10+ seconds while standby was reallocated as free and then it could start responding to requests.
Based on our research this appears to be due to fragmentation of the large object heap.
To address this concern we are taking 2 approaches:
We are going to change to jagged array vs multi-dimensional arrays. This will reduce the amount of continuous memory required, and ideally keep more of these arrays out of the Large Object Heap.
We are going to implement the arrays using the ArrayPool class.
I've used this just once: to clean up server-side cache of Crystal Report documents. See my response in Crystal Reports Exception: The maximum report processing jobs limit configured by your system administrator has been reached
The WaitForPendingFinalizers was particularly helpful for me, as sometimes the objects were not being cleaned up properly. Considering the relatively slow performance of the report in a web page - any minor GC delay was negligible, and the improvement in memory management gave an overall happier server for me.
I've a class, say "MyComputation" which does a lot of computation in one long constructor. It takes typically about 20ms to run when executed on its own (with no disk i/o or network operations). 100 or so instances of this class are created by a parent class, say "ComputeParent", which queues them up in a ThreadPool as work items:
ThreadPool.QueueUserWorkItem(myComputationCall, my_computation_data);
"myComputationCall" looks like this:
public static void myComputationCall(Object my_computation_data)
{
try
{
MyDataObject data = (MyDataObject)my_computation_data;
var computation_run = new MyComputation(data.parameter1, data.parameter2);
data.result = computation_run.result;
}
finally
{
if (Interlocked.Decrement(ref num_work_items_remaining) == 0)
done_event.Set();
}
}
done_event is a static ManualResetEvent:
private static ManualResetEvent done_event;
...
done_event = new ManualResetEvent(false);
I run ComputeParent about 500 or so times, for various input parameters. So I have a lot of nested classes. The problem is that the time it takes to execute ComputeParent gradually increases. There will be a certain amount of variation between how long it takes to run each particular ComputeParent, but the amount of time increases quite steadily (geometrically, each successive iteration take longer by a longer amount).
The memory consumption of the program does not noticably increase over time though it is quite high (~300MB). Its running on a computer with 8 logical cores, and the processor use seems to be very bursty. I'm not sure what else might be relevant to the problem.
I'd prefer not to have to run ComputeParent through batch files, though the issue does not appear to arise when this is done.
If number of available threads in the ThreadPool becomes 0, and you continue to add new work items then newly added work items will "wait". This means that your ComputeParent will wait for its instances of "myComputationCall". Starting more and more ComputeParent will cause that average execution time of them will go up.
This question has been answered. Thanks to all of the posters.
For others with a similar issue, I would suggest the Task Parallel Library as suggested by Henk.