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The System.Collections.Concurrent namespace provides various collection classes that are designed to be used in multithreaded environments. They look a little different from the normal collection classes because they are designed to be used without needing any locking, which means they can t offer features that rely on things staying consistent from one moment to the next. Numerical indexing is out, for example, because the number of items in the collection may change, as we saw when trying to use List<T> in a multithreaded fashion in Example 16-11. So these are not thread-safe versions of normal collection classes they are collections whose APIs are designed to support multithreaded use without the caller needing to use locks.
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BlockingCollection is not just a multithreaded collection; it also offers associated co-
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ordination. It provides a way for threads to sit and wait for items to become available in the collection. Its Take method will block if the collection is empty. Once data becomes available, Take will return one item. Any number of threads may be waiting inside Take at any time, and other threads are free to call Add. If you Add enough items that all the threads waiting to Take are satisfied, and then you keep calling Add, that s when items start to get added to the collection. And if the collection is nonempty, calls to Take will return immediately. This allows you to have one or more threads dedicated to processing work items generated by other threads. The BlockingCollection acts as a kind of buffer if you generate items faster than you process them, they will queue up in the BlockingCollec tion, and if the processing threads catch up, they will block efficiently until more items come along. You could use this in a WPF application that needs to do slow work in the background the UI thread could add work into a blocking collection, and then one or more worker threads could take items from the collection and process them. This is not hugely different from using the thread pool, but it gives you the opportunity to limit
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the number of worker threads if you had just a single thread that performs background work, you might be able to get away with much simpler synchronization code, because all your background work is always done by the same thread. We ve looked at how to create threads explicitly and at the tools available for ensuring that our programs function correctly in a multithreaded world. Next we re going to look at asynchronous programming models, where we don t explicitly create new threads. We will need the locking and synchronization techniques we just explored because we are still working in a concurrent world; it s just a slightly different programming style.
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Some things are intrinsically slow. Reading all of the audio data off a CD, downloading a large file from a server at the end of a low-bandwidth connection on the opposite side of the world, or playing a sound all of these processes have constraints that mean they ll take a long time to complete, maybe seconds, minutes, or even hours. How should these sorts of operations look to the programmer One simple answer is that they don t have to look different than faster operations. Our code consists of a sequence of statements one thing after another and some statements take longer than others. This has the useful property of being easy to understand. For example, if our code calls the WebClient class s DownloadString method, our program doesn t move on to the next step until the download is complete, and so we can know not just what our code does, but also the order in which it does it. This style of API is sometimes described as synchronous the time at which the API returns is determined by the time at which the operation finishes; execution progresses through the code in sync with the work being done. These are also sometimes known as blocking APIs, because they block the calling thread from further progress until work is complete. Blocking APIs are problematic for user interfaces because the blocked thread can t do anything else while slow work is in progress. Thread affinity means that code which responds to user input has to run on the UI thread, so if you re keeping that thread busy, the UI will become unresponsive. It s really annoying to use programs that stop responding to user input when they re working these applications seem to freeze anytime something takes too long, making them very frustrating to use. Failing to respond to user input within 100 ms is enough to disrupt the user s concentration. (And it gets worse if your program s user interface uses animation the occasional glitch of just 15 ms is enough to make a smooth animation turn into something disappointingly choppy.) Threads offer one solution to this: if you do all your potentially slow work on threads that aren t responsible for handling user input, your application can remain responsive. However, this can sometimes seem like an overcomplicated solution in a lot of cases,
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slow operations don t work synchronously under the covers. Take fundamental operations such as reading and writing data from and to devices such as network cards or disks, for example. The kernel-mode device drivers that manage disk and network I/O are instructed by the operating system to start doing some work, and the OS expects the driver to configure the hardware to perform the necessary work and then return control to the operating system almost immediately on the inside, Windows is built around the assumption that most slow work proceeds asynchronously, that there s no need for code to progress strictly in sync with the work. This asynchronous model is not limited to the internals of Windows there are asynchronous public APIs. These typically return very quickly, long before the work in question is complete, and you then use either a notification mechanism or polling to discover when the work is finished. The exact details vary from one API to another, but these basic principles are universal. Many synchronous APIs really are just some code that starts an asynchronous operation and then makes the thread sleep until the operation completes. An asynchronous API sounds like a pretty good fit for what we need to build responsive interactive applications.# So it seems somewhat ludicrous to create multiple threads in order to use synchronous APIs without losing responsiveness, when those synchronous APIs are just wrappers on top of intrinsically asynchronous underpinnings. Rather than creating new threads, we may as well just use asynchronous APIs directly where they are available, cutting out the middle man. .NET defines two common patterns for asynchronous operations. There s a low-level pattern which is powerful and corresponds efficiently to how Windows does things under the covers. And then there s a slightly higher-level pattern which is less flexible but considerably simpler to use in GUI code.
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