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Why Hibernate
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When to use ORM
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Although powerful, object/relational mapping is fundamentally limited by the underlying database schema, particularly in legacy databases. For instance, if tables refer to each other through columns other than primary keys, your chosen ORM solution may have trouble adapting to the legacy schema. Let s look at a good example of a bad design, shown in figure 1.4. Admittedly, this schema is a contrived example; but before you dismiss it, realize that schemas even more poorly designed than this exist in enterprise applications. Just what s wrong with this schema None of the tables have a surrogate primary key. By a surrogate key, we mean that the table s primary key has no business significance. All the columns in the tables are relevant to the business problem. You can certainly map these tables to objects with an ORM solution, but that may not be the best way to handle the domain model. You may spend more time working around how your ORM framework manages the data than is desirable. Alternative solutions, such as iBATIS, may be a better candidate for persisting legacy databases.1
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vin make model has_4wd has_aircond color varchar(30) varchar(50) varchar(20) boolean boolean varchar(15) name city state
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Figure 1.4 Poorly designed database schema
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iBATIS (www.ibatis.com) is an alternative to Hibernate.
Using direct JDBC
ORM is a good solution for legacy databases when the schema Is highly normalized Has primary keys Has foreign key relationships referring to primary keys, not columns Thankfully, the Hibernate developers have been responsive to developers working with legacy database schemas. Hibernate 3, discussed in chapter 11, adds many new features to support legacy database schemas.
Before diving into what Hibernate offers, let s take a brief look at why using JDBC is so painful for large applications. If you re still clinging to direct JDBC for application persistence, the next section is for you.
1.2 Using direct JDBC
The core drawback of JDBC is that it doesn t allow you to store objects directly to the database you must convert the objects to a relational format. For instance, if you want to persist a new instance of the Event class to the database, you must first convert the Event object to a SQL statement that can be executed on the underlying database. Similarly, when rows are returned from the database, you must convert each result row into an instance of Event. Let s look at some of the difficulties presented when converting objects and graphs of objects between the relational and object models. When working with objects, you re generally using a number of connected objects. This is called an object graph. An object graph represents an internally consistent view of application data. Internally consistent means that a change made to one object is reflected throughout the graph. The objects within a graph are typically connected using one-to-one or one-to-many associations. Using direct JDBC for persistence presents distinct problems for each of the persistence operations: creation, updating, retrieval, and deletion. Some of the problems we describe expand on the object/relational
Why Hibernate
mismatch, discussed earlier. We examine those problems in detail in a moment, using an example application that will reappear throughout this book.
1.2.1 Example application
To address the drawbacks of traditional application persistence with JDBC, we must first introduce an example that we ll use as the basis of comparison. The application that we use throughout the book is an event-management application used to manage a conference with speakers, attendees, and various locations, among other things. To demonstrate the problems with JDBC, we ll discuss persisting one of the central objects in the domain model, Event. We use the term domain model frequently. A domain model is the collection of related objects describing the problem domain for an application. Each object in the domain model represents some significant component in the application, such as an Event or Speaker. Diagrams of the Event object and the relational table used to store the Event are shown in figure 1.5. The parallel between the Event object and the relational table is clear. Each property in the Event class is reflected as a column in the events table. The id column in the events table is the primary key for the table. We ve intentionally kept the Event object simple for the opening discussion. With the object and relational table defined, we can move forward with examining the drawbacks of application persistence with direct JDBC.
Event id:Long name:String startDate:java.util.Date duration:int events bigint (pk) varchar (255 ) date int
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