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If you have experience with application servers, you're probably wondering why I'm talking so much about replicating code Actually, the reason goes back to an earlier assumption I made that our application servers are single-threaded Now, let's assume that we can build multithreaded application servers First, think about why we want to do this As you probably know, threads are lightweight processes mechanisms for execution that share an address space By "mechanisms for execution," I mean that they are scheduled by the operating system and can use the CPU (when their turn comes up) to execute program code In their most simple form, threads consist of a program counter, registers, and a stack Generally speaking, threads maintain bookkeeping information about their state of execution, sharing other common program resources with other threads Thread-scheduling policies vary, but by far the most common is round-robin, in which one thread at a time has access to the CPU Later, we'll talk about upcoming processors that are specifically designed to run multiple threads efficiently in a truly parallel manner Since multiple program threads share an address space, it is possible to have them access a common block of code in that address space This means that multiple threads can execute the same instructions (regardless of what other threads are doing) Taking this one step further, threads can be managed by yet other threads and used as "workers" to service incoming requests The idea is that when multiple clients want to access the same piece of code, they can be assigned to an available thread and have that thread execute the code they want Figure 2-8 shows three concurrent requests to a program that has five threads All three requests want to execute the same block of code called myPopularProc() As the figure shows, each one of these threads can execute this code at the same time (since the CPU runs one thread at a time, this is not quite true, but it's very close depending on the function) In fact, each thread is currently executing a different line of code, as the figure shows Thus, threads do not have to wait in line to execute the same piece of code They can be interleaved so that the execution is very nearly parallel Figure 2-8 A multi-threaded application server.



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Figure 31-5 illustrates the query execution plan for the distributed UPDATE query, beginning at the right with a Remote Scan operation that returns all 19 rows from the Excel named range. The data is then processed within SQL Server. The details of the Remote Update logical operation reveal that the distributed UPDATE query actually updated only two rows. To complete the example, the following query reads from the same Excel spreadsheet and veri es that the update took place. Again, the OpenDataSource() function is only pointing the distributed query to an external server:





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All of this means that we don't need to replicate code; we just need to make our programs multithreaded and assign threads to individual client connections as they arrive This is exactly what most application servers do today They separate the logic from its access mechanism and, instead of replicating code, they assign threads to service requests Later on, we'll see that EJB containers do the same thing One note of caution here: I have quietly avoided the main problem associated with writing multithreaded code; namely, synchronization If some portion of code must be executed serially, we need to identify that part and make sure that access to it is synchronized Fortunately, Java makes this very easy, by allowing us to synchronize at the function level or create synchronized blocks as necessary As long as we know what we are doing, Java gives us the tools to make sure that it is done safely For an in-depth discussion of synchronization and writing highly concurrent code, see Concurrent Programming in Java: Design Principles and Patterns (Lea, 1999)

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