So, another JPA tutorial. What makes this one different? Well, for one thing, this one comes with a working, downloadable project that works with Eclipse, NetBeans, and IntelliJ IDEA 7. It’s packaged with Hibernate, Toplink, and OpenJPA. And it’s been tested with MySQL, PostgreSQL, MS SQL Server, and Sybase. In other words, it works with 36 different IDE/JPA Provider/Database combinations!
Another thing that makes this tutorial different is the subject matter: Pizza! Who doesn’t love pizza? Except lactose intolerant people. And people who can’t eat gluten. But other than them, who doesn’t love pizza? So we’re going to create a simple database model for a pizza shop’s point-of-sale system.
Unsurprisingly, the starting point for any ORM task is usually the database schema (there are people who start with the Objects and work “backward” to the schema, but I haven’t worked with any of them yet). In our example, we have a pristine, consistent, completely normalized schema. In other words, it’s probably nothing like you’ll ever be lucky enough to see in the real world! Here’s our simple little ERD: From this ERD, we can infer the following: 1.) An order is comprised of zero or more pizzas. 2.) A pizza is associated with one size. 3.) A pizza may be associated with a string of text containing “special instructions.” 4.) A pizza may have zero or more toppings. You probably also notice that each table has a column called version. This will be used for an optimistic locking strategy.
The first question is, “Where should we start?” There’s no right answer for this, but I find that it’s easiest to start working with the entities with the fewest dependencies. For example, you can’t have an order without a pizza, and you can’t have a pizza without a size, so maybe it makes sense to start with the size. But before that, we’ll want an ID interface.
An ID Interface
First things first. You’ll notice that, in our schema, every table has an integer ID. It’s often a good idea to have all of your objects implement the same interface for accessing the ID, because it makes it easier to create Generic DAOs (more about that in a future post). For now, let’s make a really simple interface like this:
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Many-to-One Unidirectional Relationships
Now that we’ve gotten that out of the way, let’s create the Size class. It’s a simple POJO littered with annotations, like this:
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Here are some notes on the annotations that were used in the above class:
@Entity tells the JPA provider that this is a managed object.
@Table specifies the table name. The JPA provider will attempt to default the table name to a sane value based on the class name, but I like to be explicit. I’m funny that way. Perhaps it’s OCD. Or a power-trip.
@Column indicates the name of the column, and can include other attributes about the column (you’ll see a few additional attributes later on). Again, JPA can try to default this to sane values for you, but I like to be explicit.
@Version indicates that a particular column is used for indicating when a row is updated. This column can then be used in an optimistic locking scheme.
Next, let’s do the Pizza object to show how we map a Pizza to a Size.
One thing I that always tripped me up when I started out with ORM
tools was the difference between “One-to-Many” and “Many-to-One.” I never knew, if I call a relationship many-to-one in my metadata, is this object the one that there are many of, or is it the other way around? The answer is that “this” object always comes first. ManyToOne means that “there are many of this object to one of those objects.” The “Many” side is often the side that has the foreign key.
In our case, there will be many Pizzas that are the same size. So when we make our Pizza object, we will want to use the @ManyToOne annotation. Here’s what the Pizza object looks like so far. I’ve omitted the getters and setters to save space:
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Note that, when we made our Size object, we did not include a reference to the Pizza. That was an intentional design decision. In this application, it’s unlikely that we will want to instantiate a Size object, and get a collection containing all of the Pizzas of that size, so we don’t bother with mapping it. This is called unidirectional association.
The @ManyToOne annotation specifies a cascade attribute. There are several different settings for this attribute, which you can read more about here. I tend to cascade the persistent state to all related objects because it reduces the amount of redundant API calls. By default, JPA does not cascade pers istence to related objects. I’ll cover the cascade attribute in future posts, but for now, we’ll go with my personal preference, because I’m writing the article!
The @JoinColumn annotation indicates the column name that defines the linkage between the Pizza and the Size. You’ll also note that we’ve included some additional attributes on our @Column and @JoinColumn annotations. The unique and nullable attributes are particularly useful if you use tools to generate schema DDL from your mappings.
One-to-Many bidirectional relationships
Both the SpecialInstruction and the Order objects are examples of One-to-Many bidirectional relationships. In the case of SpecialInstruction, it is likely that we will care about which Pizza an instruction is associated with, and likewise for the Order. A bidirectional one-to-many relationship implies that one object has a collection of other o bjects. For example, an Order has a collection of Pizzas. First, lets add an order attribute to our Pizza object:
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Next, let’s create an Order object to contain our collection of Pizzas, like this:
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There are a couple of things you worth noting about this mapping:
1.) The @OneToMany annotation uses the mappedBy attribute to indicate which member of the related object defines the linkage between the two tables. In this case, we are saying that the Pizza object contains a member named order, which defines the linkage between the two objects.
2.) I’ve created a utility method called addPizza. This simplifies setting both sides of the bidirectional relationship by setting the Order object on the Pizza and adding the Pizza to the Order’s collection. Users of this class will only need to make one method call to do both.
Many-to-Many relationships via a Join Table
The last thing we’ll cover is how to map Join Tables. In our ERD, you can see that Toppings are modeled in the database with a TOPPING table that contains all of the valid toppings, a PIZZA table that contains all of the valid Pizzas, and a PIZZA_TOPPING table in the middle that maps all of the valid Pizzas to all of the valid Toppings. You could create an object called PizzaTopping that corresponds to the PIZZA_TOPPING table. Then you could have a One-to-Many relationship from the Pizza to the PizzaTopping, and a One-to-One from each PizzaTopping to a Topping. That would be very cumbersome to work with! Fortunately, there’s a better way.
Logically, a Pizza has a collection of Toppings. In our Java code, we really shouldn’t care about the fact that there is a PIZZA_TOPPING join table in the middle. First, let’s create a simple Topping class:
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This is how the association would be mapped in the Pizza class:
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The @JoinTable annotation defines three key attributes:
name: Identifies the name of the join table.
joinColumns: This attribute identifies the column name in the join table that points to this object.
inverseJoinColumns: This attribute defines the column name in the join table that points to the other objects.
From your Java code, the semantics for dealing with toppings on a pizza are just like any other set, much like you’d work with a One-to-many object.
Since the introduction of annotations, object/relational mapping is one of the easiest aspects of working with JPA over other frameworks. You can see this whole project in action on your IDE of choice by downloading it here (or from here if that doesn’t work for some reason). It should be a pretty reasonable starting point if you want a reference project to start playing with JPA. I hope to revisit the Pizza Shop project to cover other JPA topics in future posts.