I've got a separate thread which needs to request some data that may change in the meantime within the JavaFX thread. I'd like to execute a blocking invocation in this separate thread that makes sure that the request becomes enqued into the JavaFX thread.
The Swing-GUI testing framework, AssertJ, provides an easy to use API for this purpose:
List list = GuiActionRunner.execute(new GuiQuery<...>...);
The invocation blocks the current thread, executes the passed code within event dispatching thread and returns the required data.
How can this be implemented in production code for JavaFX applications? What would be the recommended approach for this requirement?
Here's an alternative solution, using a FutureTask. This avoids the explicit latch and managing the synchronized data in an AtomicReference. The code here is probably simple enough that it would make including this functionality inPlatform redundant.
FutureTask<List<?>> task = new FutureTask<>( () -> {
List<?> data = ... ; // access data
return data ;
});
Platform.runLater(task);
List<?> data = task.get();
This technique is very useful if you want to pause a background thread to await user input.
Ok I think I got it now. You need to implement something like this yourself:
AtomicReference<List<?>> r = new AtomicReference<>();
CountDownLatch l = new CountDownLatch(1);
Platform.runLater( () -> {
// access data
r.set(...)
l.countDown();
})
l.await();
System.err.println(r.get());
Related
I have a system which runs multiple service (long lived) and worker (short lived) threads. They all share a state which contains objects. Any thread can request an object an any time, through a singleton-of-sorts class called ObjectManager. If the object is not available it needs to be loaded.
Here's some pseudo-code of how object loading looks now:
class ObjectManager {
getLoadinData(path) {
if (hasLoadingDataFor(path))
return whatWeHave()
else {
loadingData = createNewLoadingData();
loadingData.path = path;
pushLoadingTaskToLoadingThread(loadingData);
return loadingData;
}
}
// loads object and blocks until it's loaded
loadObjectSync(path) {
loadingData = getLoadinData(path);
waitFor(loadingData.conditionVar);
return loadingData.loadedObject;
}
// initiates a load and calls a callback when done
loadObjectAsync(path, callback) {
loadingData = getLoadinData(path);
loadingData.callbacks.add(callback);
}
// dedicated loading thread
loadingThread() {
while (running) {
loadingData = waitForLoadingData();
object = readObjectFromDisk(loadingData.path);
object.onLoaded(); // !!!!
loadingData.object = object;
// unblock cv waiters
loadingData.conditionVar.notifyAll();
// call callbacks
loadingData.callbacks.callAll(object);
}
}
}
The problem is the line object.onLoaded. I have no control over this function. Some objects might decide that they need other objects to be valid. So in their onLoaded method they might call loadObjectSync. Uh-oh! This (naturally) dead locks. It blocks the loading loop until the loading loop makes more iterations.
What I could do to solve this is leave the onLoaded call to the initiating threads. This will change loadObjectSync to something like:
loadObjectSync(path) {
loadingData = getLoadinData(path);
waitFor(loadingData.conditionVar);
if (loadingData.wasCreatedInThisThread()) {
object.onLoaded();
loadingData.onLoadedConditionVar.notifyAll();
loadingData.callbacks.callAll(object);
}
else {
// wait more
waitFor(loadingData.onLoadedConditionVar);
}
return loadingData.loadedObject;
}
... but then the problem is that if I have no calls for loadSync and only for loadAsync or simply the loadAsync call was the first to create the loading data, there will be no one to finalize the object. So to make this work, I have to introduce another thread finalizes objects whose loadingData was created by loadObjectAsync.
It seems that it would work. But I have a simpler idea! What if I change getLoadingData instead. What if it does this:
getLoadinData(path) {
if (hasLoadingDataFor(path))
return whatWeHave()
else {
loadingData = createNewLoadingData();
loadingData.path = path;
///
thread = spawnLoadingThread(loadingData);
thread.detach();
///
return loadingData;
}
}
Spawn a new thread for every object load. Thus there is no dead lock. Every loading thread can safely block until it's done. The rest of the code remains exactly as it is.
This means potentially tens (or why not thousands in certain edge cases) active threads, waiting on condition variables. I know that spawning threads has its overhead but I think it would be negligible compared to the cost of I/O from readObjectFromDisk
So my question is: Is this terrible? Can this somehow backfire?
The target platform is conventional desktop machines. But this software is supposed to run for a long time without stopping: weeks, maybe months.
Alternatively... even though I have an idea how to solve this if the thread-per-load turns out to be terrible, can this be solved in another way?
Very interesting! This is a problem I have bumped into a couple of times, trying to add a synchronous interface to a fundamentally asynchronous operation (i.e. file load, or in my case, network write) that is performed by a service thread.
My own preference would be to not provide the synchronous interface. Why? Because it keeps the code simpler in design & implementation and easier to reason about -- always important for multi-threading.
Benefits of sticking to single thread & async only is that you only have 1 service thread, so resource growth is not a concern, plus the user callbacks are always invoked on this same thread, which simplifies thread-safety concerns for users of ObjectManager (if you have multiple callback threads, every user callback must be thread safe, so it's an important choice to make). However sticking to only an async interface does mean the user of ObjectManager has more work to do.
But if you do want to keep the synchronous interface, then another approach that I have taken could work for you. You stick to a single service thread but inside the implementation of loadObjectSync you check the thread-ID to determine if the invoker is the service thread or any-other thread. If it is any-other thread you queue the request and safely block. But if it is the service thread, you can immediately load the object, say by calling a new function loadObjectImpl. You will need to grab the thread-ID of the service thread during initialization and store it within the ObjectManager instance, and use that for thread identification. And you will need a new function which is basically just the internal scope of the loadingThread function -- i.e. a new function called something like loadObjectImpl.
The following functions and fields are part of the same class in a Visual Studio DLL. Data is continuously being read and processed using the run function on a thread. However, getPoints is being accessed in a Qt app on a QTimer. I don't wan't to miss a single processed vector, because it seems it could be skipping leading to jumpy data. What's the safest way to get the points to the updated version?
If possible I'd like an answer that uses the C++ standard library as I've been exploring mutex-es, but it still seems to lead to jumpy data.
vector<float> points;
// std::mutex ioMutex;
// function running on a thread
void run(){
while(running){
//ioMutex.lock()
vector<byte> data = ReadData()
points = processData(data);
//ioMutex.unlock()
}
}
vector<float> getPoints(){
return points;
}
I believe there is a mistake in your code. The while loop will consume all the process activity and will not allow proper functionality of other functions. In Qt, in such continuous loops, usually it is a good habit to use the following because it actually gives other process time to access the event buffer properly. If this dll is written in Qt, please add the following within the while loop
QCoreApplication::processEvents();
The safest (and probably easiest) way to deliver your points-data to the main thread is by calling qApp->postEvent() with an object of a custom QEvent-subclass that contains your vector<float> as a member-variable.
That will cause the event(QEvent *) method of (whatever Qt object you specified as the first argument to postEvent()) to be called from inside the main/GUI thread, and so you can override that method to read the vector<float> out of the QEvent-subclassed object and update the GUI with that data.
Please consider a scala.js application which runs in the browser and consists of a main program and a web worker.
The main thread delegates long running operations to the web worker by passing messages that contain the names of methods and the parameters required to invoke them. The worker passes method return values back to the main thread in the form of response messages.
In simpler terms, this program abstracts web worker messaging so that code in the main thread can call methods in the worker thread in idiomatic and asynchronous Scala syntax.
Because web workers do not associate messages with their responses in any way, the abstraction relies on a registry, an intermediary object, that governs each cross context method call to associate the invocation with the result. This singleton could also bind callback functions but is there a way to accomplish this with futures instead of callbacks?
How can I build an abstraction over this registry that allows programmers to use it with the standard asynchronous programming structures in Scala: futures and promises?
How should I write this functionality so that scala programmers can interact with it in the canonical way? For example:
// long running method in the web worker
val f: Future[String] = Registry.ultimateQuestion(42) // async
f onSuccess { case q => println("The ultimate question is: " + q) }
I'm new to futures and promises, but it seems like they usually complete when some execution block terminates. In this case, receiving a response from the web worker signifies completion of the future. Is there a way to write a custom future that delegates its completion status to an external process? Is there another way to link the web worker response message to the status of the future?
Can/Should I extend the Future trait? Is this possible in Scala.js? Is there a concrete class that I should extend? Is there some other way to encapsulate these cross context web worker method calls in existing asynchronous Scala functionality?
Thank you for your consideration.
Hmm. Just spitballing here (I haven't used workers yet), but it seems like associating the request with the Future is fairly easy in the single-threaded JavaScript world you're working in.
Here's a hypothetical design. Say that each request/response to the worker is automatically wrapped in an Envelope; the Envelope contains a RequestId. So the send side looks something like (this is pseudo-code, but real-ish):
def sendRequest[R](msg:Message):Future[R] = {
val promise = Promise[R]
val id = nextRequestId()
val envelope = Envelope(id, msg)
register(id, promise)
sendToWorker(envelope)
promise.future
}
The worker processes msg, wraps the result in another Envelope, and the result gets handled back in the main thread with something like:
def handleResult(resultEnv:Envelope):Unit = {
val promise = findRegistered(resultEnv.id)
val result = resultEnv.msg
promise.success(result)
}
That needs some filling in, and some thought about what the types like R should be, but that sort of outline would probably work decently well. If this was the JVM you'd have to worry about all sorts of race conditions, but in the single-threaded JS world it probably can be as simple as using an autoincrementing integer for the request ID, and storing away the Promise...
In most of my interviews, I've been asked about web services and multithreading. I've done neither, so I decided to learn more about Web Services and Multithreading using Grand Central Dispatch.
For web services, the way that I understand it is that you need to fetch the data using a class such as NSURLConnection. basically setup a new NSURL, then a connection, then a request. You also need to make use of the API's methods such as didConnect, didReceiveData, and didFailLoadWithError. After you receive the data, which is generally in JSON or XML format and stored as an NSData object, you can store it and parse through it. There are multiple ways to parse through it, such as by using SBJSON or NSXMLParser. You can then do with it what you need.
For multithreading, Grand Central Dispatch is a c-style way of multithreading. Basically, you use it when you need to do heavy hauling away from the main thread to avoid the app freezing. You can dispatch synchronously or asynchronously. Asynchronously means that the method on the main thread will continue executing, synchronously means that it will not. You never need to use GCD alongside with NSURLConnection, because NSURLConnection already does its work in the background then calls upon delegates in the main thread. But, for saving and unzipping files, you should use GCD. When you call dispatch_async, you pass in a dispatch queue. You can use either a serial queue or a concurrent queue. A serial queue will execute tasks in the queue one at a time, in the order that they arrived. It is the default setting. With concurrently queues, tasks executed concurrently might be executed at the same time.
My first question is, do I have a proper understanding of these two concepts? I know that there is a lot to learn about GCD, but I just want to make sure that I have the basic ideas correct. Also, with GCD, why would someone ever want to dispatch synchronously, wouldn't that defeat the purpose of multithreading?
The only reason to dispatch synchronously is to prevent the current code from continuing until the critical section finishes.
For example, if you wanted to get some value from the shared resource and use it right away, you would need to dispatch synchronously. If the current code does not need to wait for the critical section to complete, or if it can simply submit additional follow-up tasks to the same serial queue, submitting asynchronously is generally preferred.
You can make synchronous request and dispatch it by using dispatch_async or dispatch_sync call. It will totally run in background.
-(void)requestSomething:(NSString *)url
{
NSString *queue_id = #"queue_identifier";
dispatch_queue_t queue = dispatch_queue_create([queue_id UTF8String], 0);
dispatch_queue_t main = dispatch_get_main_queue();
dispatch_async(queue, ^{
NSURLRequest *theRequest = [NSURLRequest requestWithURL:[NSURL URLWithString:url]];
NSError *serviceError = nil;
NSURLResponse *serviceResponse = nil;
NSData *dataResponse = [NSURLConnection sendSynchronousRequest:theRequest returningResponse:&serviceResponse error:&serviceError];
if(serviceError)
{
dispatch_sync(main, ^{
// Do UI work like removing indicator or show user an alert with description of error using serviceError object.
return;
});
}
else
{
// Use dataResponse object and parse it as this part of code will not executed on main thread.
dispatch_sync(main, ^{
// Do UI work like updating table-view or labels using parsed data or removing indicator
});
}
});
// If your project is not developed under ARC mechanism, add following line
dispatch_release(queue);
}
We recently adopted the TPL as the toolkit for running some heavy background tasks.
These tasks typically produce a single object that implements IDisposable. This is because it has some OS handles internally.
What I want to happen is that the object produced by the background thread will be properly disposed at all times, also when the handover coincides with application shutdown.
After some thinking, I wrote this:
private void RunOnUiThread(Object data, Action<Object> action)
{
var t = Task.Factory.StartNew(action, data, CancellationToken.None, TaskCreationOptions.None, _uiThreadScheduler);
t.ContinueWith(delegate(Task task)
{
if (!task.IsCompleted)
{
DisposableObject.DisposeObject(task.AsyncState);
}
});
}
The background Task calls RunOnUiThread to pass its result to the UI thread. The task t is scheduled on the UI thread, and takes ownership of the data passed in. I was expecting that if t could not be executed because the ui thread's message pump was shut down, the continuation would run, and I could see that that the task had failed, and dispose the object myself. DisposeObject() is a helper that checks if the object is actually IDisposable, and non-null, prior to disposing it.
Sadly, it does not work. If I close the application after the background task t is created, the continuation is not executed.
I solved this problem before. At that time I was using the Threadpool and the WPF Dispatcher to post messages on the UI thread. It wasn't very pretty, but in the end it worked. I was hoping that the TPL was better at this scenario. It would even be better if I could somehow teach the TPL that it should Dispose all leftover AsyncState objects if they implement IDisposable.
So, the code is mainly to illustrate the problem. I want to learn about any solution that allows me to safely handover Disposable objects to the UI thread from background Tasks, and preferably one with as little code as possible.
When a process closes, all of it's kernel handles are automatically closed. You shouldn't need to worry about this:
http://msdn.microsoft.com/en-us/library/windows/desktop/ms686722(v=vs.85).aspx
Have a look at the RX library. This may allow you to do what you want.
From MSDN:
IsCompleted will return true when the Task is in one of the three
final states: RanToCompletion, Faulted, or Canceled
In other words, your DisposableObject.DisposeObject will never be called, because the continuation will always be scheduled after one of the above conditions has taken place. I believe what you meant to do was :
t.ContinueWith(t => DisposableObject.DisposeObject(task.AsyncState),
TaskContinuationOptions.NotOnRanToCompletion)
(BTW you could have simply captured the data variable rather than using the AsyncState property)
However I wouldn't use a continuation for something that you want to ensure happens at all times. I believe a try-finally block will be more fitting here:
private void RunOnUiThread2(Object data, Action<Object> action)
{
var t = Task.Factory.StartNew(() =>
{
try
{
action(data);
}
finally
{
DisposableObject.DisposeObject(task.AsyncState);
//Or use a new *foreground* thread if the disposing is heavy
}
}, CancellationToken.None, TaskCreationOptions.None, _uiThreadScheduler);
}