J2EE AntiPatterns by Bill Dudney, Stephen Asbury, Joseph K. Krozak, Kevin

By Bill Dudney, Stephen Asbury, Joseph K. Krozak, Kevin Wittkopf

The insights during this ebook are in accordance with confirmed ideas from specialists. they'll make sure the luck of your J2EE implementations. invoice Brown, AntiPattern Evangelist All too frequently introduced software program is stuffed with insects and poorly appearing approaches.

Unfortunately, uncovering precisely what has long gone fallacious and what should be performed to right it may be a tricky method. concentrating on J2EE, this leading edge booklet provides you with the instruments you'll have to realize and proper AntiPatternsbad behavior of code and layout. The authors discover the typical blunders which are made whereas constructing J2EE purposes and obviously aid you refactor your approach out of them.

They first seize the AntiPatterns in a template that easily describes their signs and results in addition to their average motives. Then they consultant you thru the method of reworking the implementation of code to make the layout higher. for every AntiPattern, the authors current you with real-world examples, code, and no less than one refactoring.

This method may help you write J2EE courses that paintings higher, speedier, and with much less attempt. you'll locate greater than fifty [i]J2EE AntiPatterns[/i[ that take on a lot of Javas greatest troubl

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One way to plan in upgrades is to have administrative signals that are part of your design. These signals might start when the administrator fills in a particular form on the Web site. The servlet that processes that form could send a JMS message to the associated Message Beans that a shutdown is going to occur. Likewise, a special Message Bean might be listening for the signal and notify the other types of Enterprise JavaBeans and other custom software. Each component can react to the administrative signal by cleaning up any in-memory data and closing out open requests.

Refactorings There are a couple ways to fix the problem of the Misunderstanding Data Requirements AntiPattern. Fundamentally, the solution is to understand the data requirements. To do this, you have to make realistic bandwidth calculations, which requires realistic data calculations. Second, you have to look at what information each part of a distributed application really needs. Then you have to pick the right data architecture from these requirements. The refactorings to apply are Plan for Scaling, and Choose the Right Data Architecture, both found in this chapter.

However, if more customers, transactions, or requests are added to the system, some machines that have been acting as hubs may be unable to keep up with the new requirements. ■■ Budget constraints. Sometimes the scalable solution may involve hardware or software that is more expensive. A poorly planned or highly constrained budget could result in the purchase of less than ideal technology support, which could lead to overworked hubs. Distribution and Scaling ■■ Adding new clients. Companies that buy software that inherently creates hubs—such as messaging, database, application, and Web servers—are likely to reuse them for multiple applications.

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