Most answers on stackoverflow implies in a way that sync vs async behaviour is quite similar to serial vs concurrent queue concept difference. Like the link in the first comment by #Roope
I have started to think that
Serial and concurrent are related to DispatchQueue, and sync/ async for how an operation will get executed on a thread.
Am I right?
Like if we've got DQ.main.sync then task/operation closure will get executed in a synchronous manner on this serial (main) queue.
And, if I do DQ.main.async then task will get asynchronously on some other background queue, and on reaching completion will return control on main thread.
And, since main is a serial queue, it won't let any other task/operation get into execution state/ start getting executed until the current closure task has finished its execution.
Then,
DQ.global().sync would execute a task synchronously on the thread on which its task/operation has been assigned i.e., it will block that thread from doing any other task/operation by blocking any context switching on that particular thread.
And, since, global is a concurrent queue it will keep on putting the tasks present in it to the execution state irrespective of previous task/operation's execution state.
DQ.global().async would allow context switching on the thread on which the operation closure has been put for execution
Is this the correct interpretations of the above dispatchQueues and sync vs async?
You are asking the right questions but I think you got a bit confused (mostly due to not very clear posts about this topic on internet).
Concurrent / Serial
Let's look at how you can create a new dispatch Queue:
let serialQueue = DispatchQueue(label: label)
If you don't specify any other additional parameter, this queue will behave as a serial queue:
This means that every block dispatched on this queue (sync or async it doesn't matter) will be executed alone, without the possibility for other blocks to be executed, on that same queue, simultaneously.
This doesn't mean that anything else is stopped, it just means that if something else is dispatched on that same queue, it will wait for the first block to finish before starting it's execution. Other threads and queues will still run on their own.
You can, however, create a concurrent queue, that will not constraint this blocks of code in this manner and, instead, if it happens that more blocks of code are dispatched on that same queue at the same time, it will execute them at the same time (on different threads)
let concurrentQueue = DispatchQueue(label: label,
qos: .background,
attributes: .concurrent,
autoreleaseFrequency: .inherit,
target: .global())
So, you just need to pass the attribute concurrent to the queue, and it won't be serial anymore.
(I won't be talking about the other parameters since they are not in focus of this particular question and, I think, you can read about them in the other SO post linked in the comment or, if it's not enough, you can ask another question)
If you want to understand more about concurrent queues (aka: skip if you don't care about concurrent queues)
You could ask: When do I even need a concurrent queue?
Well, just for example, let's think of a use-case where you want to synchronize READS on a shared resource: since the reads can be done simultaneously without issues, you could use a concurrent queue for that.
But what if you want to write on that shared resource?
well, in this case a write needs to act as a "barrier" and during the execution of that write, no other write and no reads can operate on that resource simultaneously.
To obtain this kind of behavior, the swift code would look something like this
concurrentQueue.async(flags: .barrier, execute: { /*your barriered block*/ })
So, in other words, you can make a concurrent queue work temporarily as a serial queue in case you need.
Once again, the concurrent / serial distinction is only valid for blocks dispatched to that same queue, it has nothing to do with other concurrent or serial work that can be done on another thread/queue.
SYNC / ASYNC
This is totally another issue, with virtually no connection to the previous one.
This two ways to dispatch some block of code are relative to the current thread/queue you are at the time of the dispatch call. This dispatch call blocks (in case of sync) or doesn't block (async) the execution of that thread/queue while executing the code you dispatch on the other queue.
So let's say I'm executing a method and in that method I dispatch async something on some other queue (I'm using main queue but it could be any queue):
func someMethod() {
var aString = "1"
DispatchQueue.main.async {
aString = "2"
}
print(aString)
}
What happens is that this block of code is dispatched on another queue and could be executed serially or concurrently on that queue, but that has no correlation to what is happening on the current queue (which is the one on which someMethod is called).
What happens on the current queue is that the code will continue executing and won't wait for that block to be completed before printing that variable.
This means that, very likely, you will see it print 1 and not 2. (More precisely you can't know what will happen first)
If instead you would dispatch it sync, than you would've ALWAYS printed 2 instead of 1, because the current queue would've waited for that block of code to be completed, before continuing in it's execution.
So this will print 2:
func someMethod() {
var aString = "1"
DispatchQueue.main.sync {
aString = "2"
}
print(aString)
}
But does it mean that the queue on which someMethod is called is actually stopped?
Well, it depends on the current queue:
If it's serial, than yes. All the blocks previously dispatched to that queue or that will be dispatched on that queue will have to wait for that block to be completed.
If it's concurrent, than no. All concurrent blocks will continue their execution, only this specific block of execution will be blocked, waiting for this dispatch call to finish it's work. Of course if we are in the barriered case, than it's like for serial queues.
What happens when the currentQueue and the queue on which we dispatch are the same?
Assuming we are on serial queues (which I think will be most of your use-cases)
In case we dispatch sync, than deadlock. Nothing will ever execute on that queue anymore. That's the worst it could happen.
In case we dispatch async, than the code will be executed at the end of all the code already dispatched on that queue (including but not limited to the code executing right now in someMethod)
So be extra careful when you use the sync method, and be sure you are not on that same queue you are dispatching into.
I hope this let you understand better.
I have started to think that Serial and concurrent are related to DispatchQueue, and sync/async for how an operation will get executed on a thread.
In short:
Whether the destination queue is serial or concurrent dictates how that destination queue will behave (namely, can that queue run this closure at the same time as other things that were dispatched to that same queue or not);
Whereas sync vs async dictates how the current thread from which you are dispatching will behave (namely, should the calling thread wait until the dispatched code to finish or not).
So, serial/concurrent affects the destination queue to which you are dispatching, whereas sync/async affects the current thread from which you are dispatching.
You go on to say:
Like if we've got DQ.main.sync then task/operation closure will get executed in a synchronous manner on this serial (main) queue.
I might rephrase this to say “if we've got DQ.main.sync then the current thread will wait for the main queue to perform this closure.”
FWIW, we don’t use DQ.main.sync very often, because 9 times out of 10, we’re just doing this to dispatch some UI update, and there’s generally no need to wait. It’s minor, but we almost always use DQ.main.async. We do use sync is when we’re trying to provide thread-safe interaction with some resource. In that scenario, sync can be very useful. But it often is not required in conjunction with main, but only introduces inefficiencies.
And, if I do DQ.main.async then task will get asynchronously on some other background queue, and on reaching completion will return control on main thread.
No.
When you do DQ.main.async, you’re specifying the closure will run asynchronously on the main queue (the queue to which you dispatched) and that that your current thread (presumably a background thread) doesn’t need to wait for it, but will immediately carry on.
For example, consider a sample network request, whose responses are processed on a background serial queue of the URLSession:
let task = URLSession.shared.dataTask(with: url) { data, _, error in
// parse the response
DispatchQueue.main.async {
// update the UI
}
// do something else
}
task.resume()
So, the parsing happens on this URLSession background thread, it dispatches a UI update to the main thread, and then carries on doing something else on this background thread. The whole purpose of sync vs async is whether the “do something else” has to wait for the “update the UI” to finish or not. In this case, there’s no point to block the current background thread while the main is processing the UI update, so we use async.
Then, DQ.global().sync would execute a task synchronously on the thread on which its task/operation has been assigned i.e., ...
Yes DQ.global().sync says “run this closure on a background queue, but block the current thread until that closure is done.”
Needless to say, in practice, we would never do DQ.global().sync. There’s no point in blocking the current thread waiting for something to run on a global queue. The whole point in dispatching closures to the global queues is so you don’t block the current thread. If you’re considering DQ.global().sync, you might as well just run it on the current thread because you’re blocking it anyway. (In fact, GCD knows that DQ.global().sync doesn’t achieve anything and, as an optimization, will generally run it on the current thread anyway.)
Now if you were going to use async or using some custom queue for some reason, then that might make sense. But there’s generally no point in ever doing DQ.global().sync.
... it will block that thread from doing any other task/operation by blocking any context switching on that particular thread.
No.
The sync doesn’t affect “that thread” (the worker thread of the global queue). The sync affects the current thread from which you dispatched this block of code. Will this current thread wait for the global queue to perform the dispatched code (sync) or not (async)?
And, since, global is a concurrent queue it will keep on putting the tasks present in it to the execution state irrespective of previous task/operation's execution state.
Yes. Again, I might rephrase this: “And, since global is a current queue, this closure will be scheduled to run immediately, regardless of what might already be running on this queue.”
The technical distinction is that when you dispatch something to a concurrent queue, while it generally starts immediately, sometimes it doesn’t. Perhaps all of the cores on your CPU are tied up running something else. Or perhaps you’ve dispatched many blocks and you’ve temporarily exhausted GCD’s very limited number of “worker threads”. Bottom line, while it generally will start immediately, there could always be resource constraints that prevent it from doing so.
But this is a detail: Conceptually, when you dispatch to a global queue, yes, it generally will start running immediately, even if you might have a few other closures that you have dispatched to that queue which haven’t finished yet.
DQ.global().async would allow context switching on the thread on which the operation closure has been put for execution.
I might avoid the phrase “context switching”, as that has a very specific meaning which is probably beyond the scope of this question. If you’re really interested, you can see WWDC 2017 video Modernizing Grand Central Dispatch Usage.
The way I’d describe DQ.global().async is that it simply “allows the current thread to proceed, unblocked, while the global queue performs the dispatched closure.” This is an extremely common technique, often called from the main queue to dispatch some computationally intensive code to some global queue, but not wait for it to finish, leaving the main thread free to process UI events, resulting in more responsive user interface.
NSOperationQueue class has an underlyingQueue property which is used to set the dispatch queue on which NSOperation instances will be executed.
let dispatchQueue = dispatch_queue_create("custom.queue", DISPATCH_QUEUE_SERIAL)
let opQueue = NSOperationQueue()
opQueue.underlyingQueue = dispatchQueue
However, official documentation states that:
The value of this property must not be the value returned by dispatch_get_main_queue
It seems that there is no more explanation on this subject from Apple. However, using main queue as underlyingQueue does not raises any errors nor does it yields any unwanted behavior. What is the reasoning behind this?
There could be a number of reasons; the potential for deadlocks springs to mind as one, but you would need to ask Apple for the definitive answer.
If your entire operation must excute on the main queue then you can get the operation queue associated with the main thread by using NSOperationQueue.mainQueue. If only part of your operation needs to execute on the main queue (such as updating UI elements) then you can just dispatch that operation onto the main queue either synchronously or asynchronously as required.
Can I write mainMOC.reset() or should I nest it like here:
mainMOC.performBlockAndWait({
mainMOC.reset()
})
I want to perform it from an arbitrary thread.
Any calls to a context must be on the queue associated with that context. If you are calling reset, it must be from the queue associated with the thread. Coming from an arbitrary thread, call it in the block.
You can test this and other questions like this by turning on the concurrency debug flag. It will let you know if you are violating the confinement constraints.
Utility.managedObjectContext().performBlockAndWait({
})
dispatch_sync(dispatch_get_main_queue(), {
})
Curious what is the difference between the two code above? context was created with .MainQueueConcurrencyType option.
If I perform blocks on the main queue, are queues executed in a FIFO order? Or can they overlap, operation mingle? I.e. (a1,a2,a3),(b1,b2,b3) can result (a1,b1,a2,a3,b2,b3)?
You are mixing two entirely different concepts here, but since it is the main thread/context/queue, your mix is masked and it "works".
Managed object context's performBlockAndWait: and performBlock: methods do not make any guarantees on which thread the block is executed, only that data accessed/mutated is safely accessed. Since your context is of main queue concurrency type, it is the exception in that it is safe to touch its objects outside of the performBlockAndWait: and performBlock: methods, on the main thread only. So when you queue your block to run on the main queue, it is guaranteed to run on the main thread, and thus your data is safe.
Block execution on the main thread is not atomic. Otherwise, what is the point of multithreading? To ensure data safety, you must performBlockAndWait: and performBlock: methods are called when accessing data. You are guaranteed that main queue scheduled blocks will run uninterrupted by other main queue scheduled blocks, and managed object context queues (background or main) are serial, so only one block will be allowed to concurrently access data.
Imagine you want to do many thing in the background of an iOS application but you code it properly so that you create threads (for example using GCD) do execute this background activity.
Now what if you need at some point to write update a variable but this update can occur or any of the threads you created.
You obviously want to protect that variable and you can use the keyword #synchronized to create the locks for you but here is the catch (extract from the Apple documentation)
The #synchronized() directive locks a section of code for use by a
single thread. Other threads are blocked until the thread exits the
protected code—that is, when execution continues past the last
statement in the #synchronized() block.
So that means if you synchronized an object and two threads are writing it at the same time, even the main thread will block until both threads are done writing their data.
An example of code that will showcase all this:
// Create the background queue
dispatch_queue_t queue = dispatch_queue_create("synchronized_example", NULL);
// Start working in new thread
dispatch_async(queue, ^
{
// Synchronized that shared resource
#synchronized(sharedResource_)
{
// Write things on that resource
// If more that one thread access this piece of code:
// all threads (even main thread) will block until task is completed.
[self writeComplexDataOnLocalFile];
}
});
// won’t actually go away until queue is empty
dispatch_release(queue);
So the question is fairly simple: How to overcome this ? How can we securely add a locks on all the threads EXCEPT the main thread which, we know, doesn't need to be blocked in that case ?
EDIT FOR CLARIFICATION
As you some of you commented, it does seem logical (and this was clearly what I thought at first when using synchronized) that only two the threads that are trying to acquire the lock should block until they are both done.
However, tested in a real situation, this doesn't seem to be the case and the main thread seems to also suffer from the lock.
I use this mechanism to log things in separate threads so that the UI is not blocked. But when I do intense logging, the UI (main thread) is clearly highly impacted (scrolling is not as smooth).
So two options here: Either the background tasks are too heavy that even the main thread gets impacted (which I doubt), or the synchronized also blocks the main thread while performing the lock operations (which I'm starting reconsidering).
I'll dig a little further using the Time Profiler.
I believe you are misunderstanding the following sentence that you quote from the Apple documentation:
Other threads are blocked until the thread exits the protected code...
This does not mean that all threads are blocked, it just means all threads that are trying to synchronise on the same object (the _sharedResource in your example) are blocked.
The following quote is taken from Apple's Thread Programming Guide, which makes it clear that only threads that synchronise on the same object are blocked.
The object passed to the #synchronized directive is a unique identifier used to distinguish the protected block. If you execute the preceding method in two different threads, passing a different object for the anObj parameter on each thread, each would take its lock and continue processing without being blocked by the other. If you pass the same object in both cases, however, one of the threads would acquire the lock first and the other would block until the first thread completed the critical section.
Update: If your background threads are impacting the performance of your interface then you might want to consider putting some sleeps into the background threads. This should allow the main thread some time to update the UI.
I realise you are using GCD but, for example, NSThread has a couple of methods that will suspend the thread, e.g. -sleepForTimeInterval:. In GCD you can probably just call sleep().
Alternatively, you might also want to look at changing the thread priority to a lower priority. Again, NSThread has the setThreadPriority: for this purpose. In GCD, I believe you would just use a low priority queue for the dispatched blocks.
I'm not sure if I understood you correctly, #synchronize doesn't block all threads but only the ones that want to execute the code inside of the block. So the solution probably is; Don't execute the code on the main thread.
If you simply want to avoid having the main thread acquire the lock, you can do this (and wreck havoc):
dispatch_async(queue, ^
{
if(![NSThread isMainThread])
{
// Synchronized that shared resource
#synchronized(sharedResource_)
{
// Write things on that resource
// If more that one thread access this piece of code:
// all threads (even main thread) will block until task is completed.
[self writeComplexDataOnLocalFile];
}
}
else
[self writeComplexDataOnLocalFile];
});