For example, the introduction includes a discussion of components and what they are. The first chapter-in which you compile the basic code and register it with Mozilla-prompts a discussion of the relationship between components and modules, of XPCOM interfaces, and of the registration process in general. Web courses and Web-based course supplements have popped up all over the world. No central force has yet emerged which dominates the field. Indeed, nearly every college, from the large to the small, has become a player.
Tremendous, broad-based Web-delivery activity has characterized the last few years of the 20th century. Elementary students publish Web-sites. Teachers use Web-pages to communicate with parents.
Web-commerce has flourished. The wave of Web-commerce has paled that of Web-teaching. The infrastructure that is emerging to support Web-commerce ultimately will permit piggybacking of Web-teaching. We can expect fast Web access to be available in students' homes. A key consequence of this evolution is that information technologists can continue to model business data using abstract structures that are amenable to machine processing; XForms binds a user-friendly Web browser interface to such abstract XML models, thereby empowering the end-user to edit and update these abstract structures.
This ability to view and edit XML documents from within a standard Web browser is likely to prove a key empowering technology. The material in this book has been the basis of MIT's entry-level computer science subject since We had been teaching this material for four years when the first edition was published, and twelve more years have elapsed until the appearance of this second edition.
We are pleased that our work has been widely adopted and incorporated into other texts. We have seen our students take the ideas and programs in this book and build them in as the core of new computer systems and languages. In literal realization of an ancient Talmudic pun, our students have become our builders. Dominic Giampaolo - file system design, online PDF book, provides details of file systems, low to high-level, topics related as the disk cache, file system, interface to the kernel, user-level APIs which use features of the file system.
There are many good books that deal with the subject at an undergraduate level, but there are few that are suitable for a one-semester graduate level course. This book is my attempt to fill that gap. The goal of this course, and hence of this book, is to expose first-year graduate students to a wide range of programming language paradigms and issues, so that they can understand the literature on programming languages.
You will have a thorough mastery of the ins and outs of PHP programming and development-related tasks, with particularly strong knowledge of forms, databases, and multimedia.
You'll be able to design, develop, and deploy complex web-based solutions across several platforms. Learn how …. Description Come learn how to make realtime apps with Brian Holt. In his signature teaching style Brian breaks down concepts to the most basic level and then builds easier-to-use, better abstractions upon the first …. Learn the Rust programming language from scratch! No previous experience needed. Description Databases can seem like big, insurmountable obstacles when learning to become a full-stack developer.
In this course, you'll learn the basics of using four of the most popular open-source types of databases: document-based …. Description Learn React Hooks by creating the key features of a realistic app. First level If all you've done is the …. Description Learn how to use Figma, a leading design software, to make a functional app mock-up from scratch The beauty of prototyping and software like Figma is that they allow you to quickly make ….
We will start the process in Adobe Lightroom for fast processing and then …. A comprehensive dive into the world of mobile security Course Overview The more that we become connected the more we need to be conscious of mobile security. Contacts, emails, passwords, location data, confidential …. This DevOps Bootcamp will take you from an absolute beginner in Linux to getting hired as a confident and effective Linux System Administrator.
Course Details We guarantee you that this is the most …. Description: Explore the power of the browser. You'll learn all the major APIs that were introduced in the HTML5 specification and beyond, to give you the full knowledge you need to build any application …. Start a career or earn a side income by becoming a Freelancer.
No experience needed. You'll learn the exact steps you need to take to start freelancing, build an online presence, get high-paying clients …. Description The fully self-paced version of our Online Developer Bootcamp, we start off by teaching you about the underpinnings of blockchain technology and show how it all comes together to allow us to build ….
Table Of Contents: 1 Welcome …. Description Pass those difficult algorithms and data structures interview questions asked by the largest silicon valley companies.
Description Structures to repeat tasks or access data collections are at the heart of compact and reusable code. C , like other programming languages, provides three basic mechanisms allowing you to execute statements multiple times …. About Learn from Node.
Six Proven Steps to Consistent Profits The best place to start when you're trying to learn something, especially trading, is the starting line. If task1 had completed before the second line of code ran, task2 would be scheduled to execute right away. Our example demonstrated the simplest kind of continuation, and is functionally similar to the following:. The continuation-based approach, however, is more flexible in that you could first wait on task1 , and then later wait on task2.
This is particularly useful if task1 returns data. Another subtler difference is that by default, antecedent and continuation tasks may execute on different threads. You can force them to execute on the same thread by specifying TaskContinuationOptions.
ExecuteSynchronously when calling ContinueWith : this can improve performance in very fine-grained continuations by lessening indirection.
In the following example, we calculate Math. Our example is somewhat contrived for simplicity; in real life, these lambda expressions would call computationally intensive functions. The following writes the details of a NullReferenceException to the console:. A safe pattern is to rethrow antecedent exceptions. As long as the continuation is Wait ed upon, the exception will be propagated and rethrown to the Wait er:.
Another way to deal with exceptions is to specify different continuations for exceptional versus nonexceptional outcomes. This is done with TaskContinuationOptions :.
A powerful feature of continuations is that they kick off only when all child tasks have completed. At that point, any exceptions thrown by the children are marshaled to the continuation. In the following example, we start three child tasks, each throwing a NullReferenceException.
We then catch all of them in one fell swoop via a continuation on the parent:. By default, a continuation is scheduled unconditionally — whether the antecedent completes, throws an exception, or is canceled. You can alter this behavior via a set of combinable flags included within the TaskContinuationOptions enum. The three core flags that control conditional continuation are:.
These flags are subtractive in the sense that the more you apply, the less likely the continuation is to execute. For convenience, there are also the following precombined values:.
This means that any continuations on the continuation itself will then run — unless you predicate them with NotOnCanceled. For example, consider this:. This is because if t1 succeeds, the fault task will be canceled , and with no continuation restrictions placed on t3 , t3 will then execute unconditionally. If we want t3 to execute only if fault actually runs, we must instead do this:.
Alternatively, we could specify OnlyOnRanToCompletion ; the difference is that t3 would not then execute if an exception was thrown within fault. Another useful feature of continuations is that you can schedule them to execute based on the completion of multiple antecedents. ContinueWhenAll schedules execution when all antecedents have completed; ContinueWhenAny schedules execution when one antecedent completes.
Both methods are defined in the TaskFactory class:. The tasks argument in the lambda expression gives you access to the array of completed tasks, which is useful when the antecedents return data. The following example adds together numbers returned from two antecedent tasks:. The type argument is unnecessary, though, as it will be inferred by the compiler. Calling ContinueWith more than once on the same task creates multiple continuations on a single antecedent.
When the antecedent finishes, all continuations will start together unless you specify TaskContinuationOptions. ExecuteSynchronously , in which case the continuations will execute sequentially. A task scheduler allocates tasks to threads.
All tasks are associated with a task scheduler, which is represented by the abstract TaskScheduler class. The Framework provides two concrete implementations: the default scheduler that works in tandem with the CLR thread pool , and the synchronization context scheduler.
The latter is designed primarily to help you with the threading model of WPF and Windows Forms, which requires that UI elements and controls are accessed only from the thread that created them. For example, suppose we wanted to fetch some data from a web service in the background, and then update a WPF label called lblResult with its result. We can divide this into two tasks:.
If, for a continuation task , we specify the synchronization context scheduler obtained when the window was constructed, we can safely update lblResult :. When you call Task. The purpose of a task factory is to create tasks — specifically, three kinds of tasks:. Interestingly, TaskFactory is the only way to achieve the latter two goals. In the case of StartNew , TaskFactory is purely a convenience and technically redundant in that you can simply instantiate Task objects and call Start on them.
TaskFactory is not an abstract factory: you can actually instantiate the class, and this is useful when you want to repeatedly create tasks using the same nonstandard values for TaskCreationOptions , TaskContinuationOptions , or TaskScheduler. For example, if we wanted to repeatedly create long-running parented tasks, we could create a custom factory as follows:. The class that enables this pattern of use is called TaskCompletionSource.
To use TaskCompletionSource you simply instantiate the class. It exposes a Task property that returns a task upon which you can wait and attach continuations—just like any other task.
The task, however, is entirely controlled by the TaskCompletionSource object via the following methods:. If you want a task with no result, create a TaskCompletionSource of object and pass in null when calling SetResult. We then demonstrate how TaskCompletionSource improves the solution by allowing queued work items to be waited upon and canceled.
If we asked PLINQ to parallelize this query and it ignored the handling of exceptions, a DivideByZeroException would probably be thrown on a separate thread , bypassing our catch block and causing the application to die. Hence, exceptions are automatically caught and rethrown to the caller. To ensure that all exceptions are reported, exceptions are therefore wrapped in an AggregateException container, which exposes an InnerExceptions property containing each of the caught exception s :.
Both PLINQ and the Parallel class end the query or loop execution upon encountering the first exception — by not processing any further elements or loop bodies. More exceptions might be thrown, however, before the current cycle is complete. The first exception in AggregateException is visible in the InnerException property.
The AggregateException class provides a couple of methods to simplify exception handling: Flatten and Handle.
AggregateException s will quite often contain other AggregateException s. An example of when this might happen is if a child task throws an exception. You can eliminate any level of nesting to simplify handling by calling Flatten. This method returns a new AggregateException with a simple flat list of inner exceptions:.
The Handle method on AggregateException provides a shortcut for doing this. It accepts an exception predicate which it runs over every inner exception:. For instance, the following ends up rethrowing another AggregateException that contains a single NullReferenceException :.
Concurrent namespace. All of these are fully thread-safe:. The concurrent collections can sometimes be useful in general multithreading when you need a thread-safe collection. However, there are some caveats:. To demonstrate, if we execute the following code on a single thread:. Reading from a ConcurrentDictionary , however, is fast because reads are lock-free.
The concurrent collections also differ from conventional collections in that they expose special methods to perform atomic test-and-act operations, such as TryPop. The classic examples are stacks and queues. The following classes implement this interface:.
The testing and acting are performed atomically, eliminating the need to lock as you would around a conventional collection:. TryTake returns false if the collection is empty. TryAdd always succeeds and returns true in the three implementations provided. The three concrete classes mostly implement the TryTake and TryAdd methods explicitly, exposing the same functionality through more specifically named public methods such as TryDequeue and TryPop.
In contrast, calling Add in parallel on a queue or stack incurs some contention although a lot less than locking around a nonconcurrent collection.
Inside a concurrent bag, each thread gets it own private linked list. Elements are added to the private list that belongs to the thread calling Add , eliminating contention. So, to be precise, calling Take gives you the element added most recently on that thread; if there are no elements on that thread, it gives you the element added most recently on another thread, chosen at random.
Concurrent bags are ideal when the parallel operation on your collection mostly comprises Add ing elements — or when the Add s and Take s are balanced on a thread. We saw an example of the former previously, when using Parallel. ForEach to implement a parallel spellchecker:. Sometimes it would be more useful in this scenario to wait until an element is available. A blocking collection also lets you limit the total size of the collection, blocking the producer if that size is exceeded.
A collection limited in this manner is called a bounded blocking collection. The producing and consuming methods let you specify cancellation tokens and timeouts. Add and TryAdd may block if the collection size is bounded; Take and TryTake block while the collection is empty.
Another way to consume elements is to call GetConsumingEnumerable. This returns a potentially infinite sequence that yields elements as they become available. You can force the sequence to end by calling CompleteAdding : this method also prevents further elements from being enqueued. BlockingCollection also provides static methods called AddToAny and TakeFromAny , which let you add or take an element while specifying several blocking collections. The action is then honored by the first collection able to service the request.
It would be nice if we could:. An ideal solution would be to have the EnqueueTask method return some object giving us the functionality just described.
The good news is that a class already exists to do exactly this — the Task class. All we need to do is to hijack control of the task via TaskCompletionSource :. In EnqueueTask , we enqueue a work item that encapsulates the target delegate and a task completion source — which lets us later control the task that we return to the consumer. In Consume , we first check whether a task has been canceled after dequeuing the work item.
If not, we run the delegate and then call SetResult on the task completion source to indicate its completion. We can now wait on task , perform continuations on it, have exceptions propagate to continuations on parent tasks, and so on. In parallel programming, a brief episode of spinning is often preferable to blocking, as it avoids the cost of context switching and kernel transitions. SpinLock and SpinWait are designed to help in such cases.
Their main use is in writing custom synchronization constructs. SpinLock and SpinWait are structs and not classes! You are commenting using your WordPress. You are commenting using your Google account. You are commenting using your Twitter account. You are commenting using your Facebook account. Notify me of new comments via email. Notify me of new posts via email. This site uses Akismet to reduce spam.
0コメント