1.1. What is persistence?

Almost all applications require persistent data. Persistence is one of the fundamental concepts in application development. If an information system didn't preserve data when it was powered off, the system would be of little practical use. When we talk about persistence in Java, we're normally talking about storing data in a relational database using SQL. We'll start by taking a brief look at the technology and how we use it with Java. Armed with that information, we'll then continue our discussion of persistence and how it's implemented in object-oriented applications.

1.1.1. Relational databases

You, like most other developers, have probably worked with a relational database. Most of us use a relational database every day. Relational technology is a known quantity, and this alone is sufficient reason for many organizations to choose it. But to say only this is to pay less respect than is due. Relational databases are entrenched because they're an incredibly flexible and robust approach to data management. Due to the complete and consistent theoretical foundation of the relational data model, relational databases can effectively guarantee and protect the integrity of the data, among other desirable characteristics. Some people would even say that the last big invention in computing has been the relational concept for data management as first introduced by E.F. Codd (Codd, 1970) more than three decades ago.

Relational database management systems aren't specific to Java, nor is a relational database specific to a particular application. This important principle is known as data independence. In other words, and we can't stress this important fact enough, data lives longer than any application does. Relational technology provides a way of sharing data among different applications, or among different technologies that form parts of the same application (the transactional engine and the reporting engine, for example). Relational technology is a common denominator of many disparate systems and technology platforms. Hence, the relational data model is often the common enterprise-wide representation of business entities.

Relational database management systems have SQL-based application programming interfaces; hence, we call today's relational database products SQL database management systems or, when we're talking about particular systems, SQL databases.

Before we go into more detail about the practical aspects of SQL databases, we have to mention an important issue: Although marketed as relational, a database system providing only an SQL data language interface isn't really relational and in many ways isn't even close to the original concept. Naturally, this has led to confusion. SQL practitioners blame the relational data model for shortcomings in the SQL language, and relational data management experts blame the SQL standard for being a weak implementation of the relational model and ideals. Application developers are stuck somewhere in the middle, with the burden to deliver something that works. We'll highlight some important and significant aspects of this issue throughout the book, but generally we'll focus on the practical aspects. If you're interested in more background material, we highly recommend Practical Issues in Database Management: A Reference for the Thinking Practitioner by Fabian Pascal (Pascal, 2000).

1.1.2. Understanding SQL

To use Hibernate effectively, a solid understanding of the relational model and SQL is a prerequisite. You need to understand the relational model and topics such as normalization to guarantee the integrity of your data, and you'll need to use your knowledge of SQL to tune the performance of your Hibernate application. Hibernate automates many repetitive coding tasks, but your knowledge of persistence technology must extend beyond Hibernate itself if you want to take advantage of the full power of modern SQL databases. Remember that the underlying goal is robust, efficient management of persistent data.

Let's review some of the SQL terms used in this book. You use SQL as a data definition language (DDL) to create a database schema with CREATE and ALTER statements. After creating tables (and indexes, sequences, and so on), you use SQL as a data manipulation language (DML) to manipulate and retrieve data. The manipulation operations include insertions, updates, and deletions. You retrieve data by executing queries with restrictions, projections, and join operations (including the Cartesian product). For efficient reporting, you use SQL to group, order, and aggregate data as necessary. You can even nest SQL statements inside each other; this technique uses subselects.

You've probably used SQL for many years and are familiar with the basic operations and statements written in this language. Still, we know from our own experience that SQL is sometimes hard to remember, and some terms vary in usage. To understand this book, we must use the same terms and concepts, so we advise you to read appendix A if any of the terms we've mentioned are new or unclear.

If you need more details, especially about any performance aspects and how SQL is executed, get a copy of the excellent book SQL Tuning by Dan Tow (Tow, 2003). Also read An Introduction to Database Systems by Chris Date (Date, 2003) for the theory, concepts, and ideals of (relational) database systems. The latter book is an excellent reference (it's big) for all questions you may possibly have about databases and data management.

Although the relational database is one part of ORM, the other part, of course, consists of the objects in your Java application that need to be persisted to and loaded from the database using SQL.

1.1.3. Using SQL in Java

When you work with an SQL database in a Java application, the Java code issues SQL statements to the database via the Java Database Connectivity (JDBC) API. Whether the SQL was written by hand and embedded in the Java code, or generated on the fly by Java code, you use the JDBC API to bind arguments to prepare query parameters, execute the query, scroll through the query result table, retrieve values from the result set, and so on. These are low-level data access tasks; as application developers, we're more interested in the business problem that requires this data access. What we'd really like to write is code that saves and retrieves objects—the instances of our classes—to and from the database, relieving us of this low-level drudgery.

Because the data access tasks are often so tedious, we have to ask: Are the relational data model and (especially) SQL the right choices for persistence in object-oriented applications? We answer this question immediately: Yes! There are many reasons why SQL databases dominate the computing industry—relational database management systems are the only proven data management technology, and they're almost always a requirement in any Java project.

However, for the last 15 years, developers have spoken of a paradigm mismatch. This mismatch explains why so much effort is expended on persistence-related concerns in every enterprise project. The paradigms referred to are object modeling and relational modeling, or perhaps object-oriented programming and SQL.

Let's begin our exploration of the mismatch problem by asking what persistence means in the context of object-oriented application development. First we'll widen the simplistic definition of persistence stated at the beginning of this section to a broader, more mature understanding of what is involved in maintaining and using persistent data.

1.1.4. Persistence in object-oriented applications

In an object-oriented application, persistence allows an object to outlive the process that created it. The state of the object can be stored to disk, and an object with the same state can be re-created at some point in the future.

This isn't limited to single objects—entire networks of interconnected objects can be made persistent and later re-created in a new process. Most objects aren't persistent; a transient object has a limited lifetime that is bounded by the life of the process that instantiated it. Almost all Java applications contain a mix of persistent and transient objects; hence, we need a subsystem that manages our persistent data.

Modern relational databases provide a structured representation of persistent data, enabling the manipulating, sorting, searching, and aggregating of data. Database management systems are responsible for managing concurrency and data integrity; they're responsible for sharing data between multiple users and multiple applications. They guarantee the integrity of the data through integrity rules that have been implemented with constraints. A database management system provides data-level security. When we discuss persistence in this book, we're thinking of all these things:

• Storage, organization, and retrieval of structured data

• Concurrency and data integrity

• Data sharing

And, in particular, we're thinking of these problems in the context of an object-oriented application that uses a domain model.

An application with a domain model doesn't work directly with the tabular representation of the business entities; the application has its own object-oriented model of the business entities. If the database of an online auction system has ITEM and BID tables, for example, the Java application defines Item and Bid classes.

Then, instead of directly working with the rows and columns of an SQL result set, the business logic interacts with this object-oriented domain model and its runtime realization as a network of interconnected objects. Each instance of a Bid has a reference to an auction Item, and each Item may have a collection of references to Bid instances. The business logic isn't executed in the database (as an SQL stored procedure); it's implemented in Java in the application tier. This allows business logic to make use of sophisticated object-oriented concepts such as inheritance and polymorphism. For example, we could use well-known design patterns such as Strategy, Mediator, and Composite (Gamma and others, 1995), all of which depend on polymorphic method calls.

Now a caveat: Not all Java applications are designed this way, nor should they be. Simple applications may be much better off without a domain model. Complex applications may have to reuse existing stored procedures. SQL and the JDBC API are perfectly serviceable for dealing with pure tabular data, and the JDBC RowSet makes CRUD operations even easier. Working with a tabular representation of persistent data is straightforward and well understood.

However, in the case of applications with nontrivial business logic, the domain model approach helps to improve code reuse and maintainability significantly. In practice, both strategies are common and needed. Many applications need to execute procedures that modify large sets of data, close to the data. At the same time, other application modules could benefit from an object-oriented domain model that executes regular online transaction processing logic in the application tier. An efficient way to bring persistent data closer to the application code is required.

If we consider SQL and relational databases again, we finally observe the mismatch between the two paradigms. SQL operations such as projection and join always result in a tabular representation of the resulting data. (This is known as transitive closure; the result of an operation on relations is always a relation.) This is quite different from the network of interconnected objects used to execute the business logic in a Java application. These are fundamentally different models, not just different ways of visualizing the same model.

With this realization, you can begin to see the problems—some well understood and some less well understood—that must be solved by an application that combines both data representations: an object-oriented domain model and a persistent relational model. Let's take a closer look at this so-called paradigm mismatch.