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For an example of printer priority, see Figure 11-10. User1 sends documents to a printer with the lowest priority of 1, and User2 sends documents to a printer with the highest priority of 99. In this example, User2 s documents always print before User1 s documents.

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After setting a new fetching strategy, rerun the use case and check the generated SQL again. Note the SQL statements and go to the next use case. After optimizing all use cases, check every one again and see whether any global optimization had side effects for others. With some experience, you ll easily be able to avoid any negative effects and get it right the first time. This optimization technique is practical for more than the default fetching strategies; you may also use it to tune HQL and Criteria queries, which can define the fetch plan and the fetching strategy dynamically. You often can replace a global fetch setting with a new dynamic query or a change of an existing query we ll have much more to say about these options in the next chapter. In the next section, we introduce the Hibernate caching system. Caching data on the application tier is a complementary optimization that you can utilize in any sophisticated multiuser application.

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A major justification for our claim that applications using an object/relational persistence layer are expected to outperform applications built using direct JDBC is the potential for caching. Although we ll argue passionately that most applications should be designed so that it s possible to achieve acceptable performance without the use of a cache, there is no doubt that for some kinds of applications, especially read-mostly applications or applications that keep significant metadata in the database, caching can have an enormous impact on performance. Furthermore, scaling a highly concurrent application to thousands of online transactions usually requires some caching to reduce the load on the database server(s). We start our exploration of caching with some background information. This includes an explanation of the different caching and identity scopes and the impact of caching on transaction isolation. This information and these rules can be applied to caching in general and are valid for more than just Hibernate applications. This discussion gives you the background to understand why the

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In the following guide we'll create a local report ( RDLC file) which features barcoding capabilities by using Bytescout Barcode SDK. Follow these steps:.

Use the following steps to set the priority for a printer: 1. Click Start, and then click Printers And Faxes. 2. In the Printers And Faxes window, right-click the icon for the printer, and then click Properties. 3. In the Properties dialog box for the printer, on the Advanced tab, adjust the Priority setting for the printer. This value for a printer can be set from 1 through 99 the higher the number, the higher the priority of the printer. 4. Click OK.

The major enhancements in Windows XP Service Pack 2 include Security Center, Automatic Updates, Windows Firewall, and Internet Explorer. This section describes these enhancements in detail.

Hibernate caching system is the way it is. We then introduce the Hibernate caching system and show you how to enable, tune, and manage the first- and second-level Hibernate cache. We recommend that you carefully study the fundamentals laid out in this section before you start using the cache. Without the basics, you may quickly run into hard to debug concurrency problems and risk the integrity of your data. Caching is all about performance optimization, so naturally it isn t part of the Java Persistence or EJB 3.0 specification. Every vendor provides different solutions for optimization, in particular any second-level caching. All strategies and options we present in this section work for a native Hibernate application or an application that depends on Java Persistence interfaces and uses Hibernate as a persistence provider. A cache keeps a representation of current database state close to the application, either in memory or on disk of the application server machine. The cache is a local copy of the data. The cache sits between your application and the database. The cache may be used to avoid a database hit whenever

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