Although modern CPUs actually support out-of-order execution, committal of results remains in order in Java

Creation QR Code in Java Although modern CPUs actually support out-of-order execution, committal of results remains in order
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Synchronous communication is a part of almost all distributed computing systems Web applications, being distributed, are inherently synchronous when the user is involved When you use your Web browser to download a Web page, the download is a synchronous process: An HTTP request is issued and an HTTP response follows shortly thereafter In most server-side application systems, servers contact each other synchronously (for example, using RMI, CORBA, or COM) as well as the database All of this makes sense given that queries must be answered for the application to continue However, while synchronous behavior may be necessary in certain scenarios, it's never desirable from a performance or scalability standpoint because it effectively serializes execution Synchronous communication means that a requestor is idle while its reply is being constructed A called function or an instruction must complete before execution proceeds In many situations, asynchronous methods may be applicable and can dramatically improve parallelism and thus performance For example, suppose you develop a Web application that broadcasts live pitch-by-pitch baseball coverage in which the user downloads some graphical client that shows the play by play Under a synchronous model, the deploying Web site would have to keep track of all clients and contact them individually waiting for their replies whenever a pitch was thrown But this seems inefficient Since client replies don't really mean anything, why waste server-side time waiting for them If it were possible to asynchronously communicate or broadcast this information to the clients, server-side performance would improve substantially For example, the server could write the updated data to some public data source that clients could access at will Since there would be no value in their replies (other than that they got the message), the server wouldn't need to wait for them to receive the data Asynchrony doesn't apply only to communication between remote pieces of functionality If single-threaded synchronous execution is recast as multithreaded, asynchronous execution within a given program can yield important efficiency benefits Consider a Web application that downloads a set of URLs, and inserts their contents into a database db A simple way to accomplish this task would involve the following pseudo-code: for each url u in the list of URLs to be downloaded page FETCH-PAGE(u)
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DATABASE-INSERT(db, page) This means that, after the first download, each successive download occurs only after the DATABASE-INSERT of the previous one It seems like a waste We know that fetching the page is an I/O-bound activity, while database insertion is generally CPU-bound It would seem optimal to request the next page be downloaded while the database insertion of the previous one is taking place Thus, both activities would be occurring in parallel Now, the only thing one needs to do is identify a way for data (ie, the downloaded page) to be passed between them For this type of parallel, asynchronous solution, we might create two threads one for downloading and one for database insertion In doing so, suppose that the threads are able to communicate over a common thread-safe queue q Given these assumptions, consider sample pseudo-code related to the first thread, which is in charge of downloading the content: for each url u in the list of URLs to be downloaded page FETCH-PAGE(u)
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ENQUEUE(q, page)
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ENQUEUE(q, End-Of-Stream) Next, consider sample pseudo-code related to the second thread, which is in charge of inserting the extracted information i into a database d as it becomes available: object DEQUEUE(q) End-Of-Stream
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while object
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DATABASE-INSERT(db, object) object DEQUEUE(q)
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Thus, by allowing multiple threads to communicate asynchronously via a global data structure, we increase overall processing parallelism In this example, idle CPU cycles were put to more efficient use at the expense of a slightly more complex implementation When applicable, asynchronous designs such as this perform well and are easier to scale because of the more efficient use of resources The main challenge is in implementation writing correct multithreaded code and ensuring serialization (when necessary) for certain important operations on shared data structures Later in 9, we'll also discuss how technologies like the Java Message Service (JMS) make distributed asynchronous solutions very easy
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