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Assuming each Service is represented by one instance, dependency injection alone is a fine solution for a single-threaded application; only one client may be accessing a resource at a given time. However, this quickly becomes a problem in situations where a centralized server is fit to serve many simultaneous requests. Deadlocks, livelocks, and race conditions are some of the possible nightmares arising out of an environment in which threads may compete for shared resources. These are hard to anticipate, harder to debug, and are prone to first exposing themselves in production! Proper solutions lie outside the scope of this book, and for good reason: EJB allows the application developer to sidestep the problem entirely thanks to a series of concurrency policies. That said, there are a series of effects upon performance to consider, so the specification allows for configuration in some cases. Otherwise, it s important to be aware how each component type views concurrency concerns; this is covered alongside the session bean in s 5, 6, and 7.
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Because of the strict concurrency rules enforced by the Container, an intentional bottleneck is often introduced where a service instance may not be available for processing until some other request has completed. If the service was restricted to a singular instance, all subsequent requests would have to queue up until their turn was reached (see Figure 3-1).
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Recommended reading is Java Concurrency in Practice, Goetz et al., http://www.javaconcurrencyinpractice .com/
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Conversely, if the service was permitted to use any number of underlying instances, there would be no guard to say how many requests could be processed in tandem, and access across the physical machine could crawl to a halt as its resources were spread too thin (Figure 3-2).
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EJB addresses this problem through a technique called instance pooling, in which each module is allocated some number of instances with which to serve incoming requests (Figure 3-3). Many vendors provide configuration options that allow the deployer to allocate pool sizes appropriate to the work being performed, providing the compromise needed to achieve optimal throughput.
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Instance pooling addresses performance, and it is explained alongside session beans in s 5, 6, and 7.
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As a routine chugs along, it may perform half of its duties before encountering some exceptional circumstance that prevents successful completion. At this point, the system may be left in an unreliable or incorrect state. Take the popular account transfer example : 1. User requests that $100 be transferred between her checking and savings accounts. 2. System deducts $100 from checking. 3. An unexpected error is thrown up the call chain. The money has disappeared from record, and the customer is out $100. Although this may be a desirable scenario if you re a particularly scheming bank manager, in most cases we d like our programs to reliably leave things in consistent state. EJB ensures this via its integration with the Java Transaction Service (JTS; http://java.sun.com/jav aee/technologies/jts/) and exposes an API that gives the bean provider (application developer) control over the properties specifying how a transaction-aware application behaves. Again, the nuts and bolts of how this is achieved is not a problem for the EJB developer; all that s required is some understanding of the ACID fundamentals: Atomicity Every instruction in a call completes or none do. If there s a failure halfway through, state is restored to the point before the request was made. Consistency The system will be consistent with its governing rules both before and after the request. Isolation Transactions in progress are not seen outside the scope of their request until successful completion. Shared resources may not be mutated by two transactions at once. Durability Once a transaction successfully returns, it must commit to its changes. The system must process the result once a client has received word of normal completion. There are a variety of options available to configure transactional behavior, and these are explored in 17.
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