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The previous example showed that attempting to divide by zero causes an exception. You can modify the program to handle that exception by placing the code inside a try block and supplying a simple catch clause. When the exception is raised, it is caught and handled in the catch block. static void Main() { int x = 10; try { int y = 0; x /= y; } catch { ... // Code to handle the exception // Raises an exception



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System exceptions include java.lang.RuntimeException and its subclasses. EJBException is a subclass of RuntimeException, so it is considered a system exception. System exceptions also include java.rmi.RemoteException and its subclasses. The Run timeException and RemoteException subclasses differ in that they can be turned into application exceptions using the @javax.ejb.ApplicationException annotation. This annotation is discussed later in this chapter. System exceptions always cause a transaction to roll back when they are thrown from an enterprise bean method. Any RuntimeException not annotated with @Applica tionException that is thrown within a business method (for instance, EJBException, NullPointerException, IndexOutOfBoundsException, and so on) is handled by the container automatically and results in a transaction rollback. In Java, RuntimeException types do not need to be declared in the throws clause of the method signature or handled using try/catch blocks; they are automatically thrown from the method. The container handles system exceptions automatically and it will always do the following: 1. Roll back the transaction. 2. Log the exception to alert the system administrator. 3. Discard the EJB instance. When a system exception is thrown from any callback method (@PostConstruct, @Post Activate, and so on), it is treated the same way as exceptions thrown from any business method. Although EJB requires system exceptions to be logged, it does not specify how they should be logged or the format of the logfile. The exact mechanism for recording exceptions and reporting them to the system administrator is left to the vendor.





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Your Azure storage account can have many queues; at any time, a queue can have many messages Messages are the lifeblood of a queue system and should represent the things that a producer is telling a consumer You can think of a queue as having a name, some properties, and a collection of ordered messages In Azure, messages are limited to 8 KB in size This low limit is designed for performance and scalability reasons If a message could be up to 1 GB in size, writing to and reading from the queue would take a long time This would also make it hard for the queue to respond quickly when there were many different consumers reading messages from the top of the queue Because of this limit, most Azure queue messages will follow a work ticket pattern.

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But there could be a logical problem with this rewrite Unless the combination of (dept_no, dept_group) or at least the dept_no is constrained to be unique across the dept table, a simple join could produce multiple copies of each relevant emp row If you are not very careful as you switch between joins and subqueries, you can get wrong answers This is where the semi-join comes in: it deals with cases where the suitable uniqueness constraint simply does not exist A semi-join is like a simple join, but once a row from the outer table has joined to one row from the inner table, no further processing is done for that outer row In its nested loop form, it s like having an inner loop that always stops after one success, thus saving resources.

The message will usually not contain the data needed by the consumer itself Instead, the message will contain a pointer of some sort to the real work that needs to be done For example, following along with figure 163, a queue that contains messages for video compression won t include the actual video that needs to be compressed The producer will store the video in a shared storage location q, perhaps a BLOB container or a table Once the video is stored, the producer will then place a message in the queue with the name of the BLOB that needs to be compressed w There ll likely be other jobs in the queue as well The consumer will then pick up the work ticket, fetch the proper video from BLOB storage, compress the video e, and then store the new video back in BLOB storage r.

NOTE At the time of writing, little information is available about these changes, so my apologies for the lack of detail.

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