1. Introduction
This is an introductory article to get you up and running with the powerful Querydsl API for data persistence.
The goal here is to give you the practical tools to add Querydsl to your project, understand the structure and purpose of the generated classes, and get a basic understanding of how to write type-safe database queries for the most common scenarios.
2. The Purpose of Querydsl
Object-relational mapping frameworks are at the core of Enterprise Java. These compensate for the mismatch between the object-oriented approach and the relational database model. They also allow developers to write cleaner and more concise persistence code and domain logic.
However, one of the most difficult design choices for an ORM framework is the API for building correct and type-safe queries.
One of the most widely used Java ORM frameworks, Hibernate (and also closely related JPA standard), proposes a string-based query language HQL (JPQL) very similar to SQL. The obvious drawbacks of this approach are the lack of type safety and the absence of static query checking. Also, in more complex cases (for instance, when the query needs to be constructed at runtime depending on some conditions), building an HQL query typically involves the concatenation of strings which is usually very unsafe and error-prone.
Starting with JPA 2.0 standard brought an improvement in the form of Criteria Query API — a new and type-safe method of building queries that took advantage of metamodel classes generated during annotation preprocessing. Unfortunately, being groundbreaking in its essence, Criteria Query API ended up very verbose and practically unreadable. Here’s an example from the Jakarta EE tutorial for generating a query as simple as SELECT p FROM Pet p:
EntityManager em = ...;
CriteriaBuilder cb = em.getCriteriaBuilder();
CriteriaQuery<Pet> cq = cb.createQuery(Pet.class);
Root<Pet> pet = cq.from(Pet.class);
cq.select(pet);
TypedQuery<Pet> q = em.createQuery(cq);
List<Pet> allPets = q.getResultList();
No wonder that a more adequate Querydsl library soon emerged, based on the same idea of generated metadata classes, yet implemented with a fluent and readable API.
3. Querydsl Class Generation
Let’s start with generating and exploring the magical metaclasses that account for the fluent API of Querydsl.
3.1. Adding Querydsl to Maven Build
Including Querydsl in your project is as simple as adding several dependencies to your build file and configuring a plugin for processing JPA annotations. Let’s start with the dependencies. The version of Querydsl libraries should be extracted to a separate property inside the
<properties>
<querydsl.version>5.0.0</querydsl.version>
</properties>
Next, add the following dependencies to the
<dependencies>
<dependency>
<groupId>com.querydsl</groupId>
<artifactId>querydsl-apt</artifactId>
<version>${querydsl.version}</version>
<classifier>jakarta</classifier>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>com.querydsl</groupId>
<artifactId>querydsl-jpa</artifactId>
<classifier>jakarta</classifier>
<version>${querydsl.version}</version>
</dependency>
</dependencies>
The querydsl-apt dependency is an annotation processing tool (APT) — implementation of corresponding Java API that allows the processing of annotations in source files before they move on to the compilation stage. This tool generates the so-called Q-types — classes that directly relate to the entity classes of your application, but are prefixed with the letter Q. For instance, if you have a User class marked with the @Entity annotation in your application, then the generated Q-type will reside in a QUser.java source file.
The provided scope of the querydsl-apt dependency means that this jar should be made available only at build time, but not included in the application artifact.
The querydsl-jpa library is the Querydsl itself, designed to be used together with a JPA application.
To configure the annotation processing plugin that takes advantage of querydsl-apt, add the following plugin configuration to your pom – inside the
<plugin>
<groupId>com.mysema.maven</groupId>
<artifactId>apt-maven-plugin</artifactId>
<version>1.1.3</version>
<executions>
<execution>
<goals>
<goal>process</goal>
</goals>
<configuration>
<outputDirectory>target/generated-sources/java</outputDirectory>
<processor>com.querydsl.apt.jpa.JPAAnnotationProcessor</processor>
</configuration>
</execution>
</executions>
</plugin>
This plugin makes sure that the Q-types are generated during the process goal of the Maven build. The outputDirectory configuration property points to the directory where the Q-type source files will be generated. The value of this property will be useful later on when you’ll go exploring the Q-files.
You should also add this directory to the source folders of the project, if your IDE does not do this automatically — consult the documentation for your favourite IDE on how to do that.
For this article, we will use a simple JPA model of a blog service, consisting of Users and their BlogPosts with a one-to-many relationship between them:
@Entity
public class User {
@Id
@GeneratedValue
private Long id;
private String login;
private Boolean disabled;
@OneToMany(cascade = CascadeType.PERSIST, mappedBy = "user")
private Set<BlogPost> blogPosts = new HashSet<>(0);
// getters and setters
}
@Entity
public class BlogPost {
@Id
@GeneratedValue
private Long id;
private String title;
private String body;
@ManyToOne
private User user;
// getters and setters
}
To generate Q-types for your model, simply run:
mvn compile
3.2. Exploring Generated Classes
Now go to the directory specified in the outputDirectory property of apt-maven-plugin (target/generated-sources/java in our example). You will see a package and class structure that directly mirrors your domain model, except all the classes start with the letter Q (QUser and QBlogPost in our case).
Open the file QUser.java. This is your entry point to building all queries that have User as a root entity. The first thing you’ll notice is the @Generated annotation which means that this file was automatically generated and should not be edited manually. Should you change any of your domain model classes, you will have to run mvn compile again to regenerate all of the corresponding Q-types.
Aside from several QUser constructors present in this file, you should also take notice of a public static final instance of the QUser class:
public static final QUser user = new QUser("user");
This is the instance that you can use in most of your Querydsl queries to this entity, except when you need to write some more complex queries, like joining several different instances of a table in a single query.
The last thing that should be noted is that for every field of the entity class, there is a corresponding *Path field in the Q-type, like NumberPath id, StringPath login and SetPath blogPosts in the QUser class (notice that the name of the field corresponding to Set is pluralized). These fields are used as parts of fluent query API that we will encounter later on.
4. Querying With Querydsl
4.1. Simple Querying and Filtering
To build a query, first, we’ll need an instance of a JPAQueryFactory, which is a preferred way of starting the building process. The only thing that JPAQueryFactory needs is an EntityManager, which should already be available in your JPA application via EntityManagerFactory.createEntityManager() call or @PersistenceContext injection.
EntityManagerFactory emf =
Persistence.createEntityManagerFactory("com.baeldung.querydsl.intro");
EntityManager em = entityManagerFactory.createEntityManager();
JPAQueryFactory queryFactory = new JPAQueryFactory(JPQLTemplates.DEFAULT, em);
Now let’s create our first query:
QUser user = QUser.user;
User c = queryFactory.selectFrom(user)
.where(user.login.eq("David"))
.fetchOne();
Notice we’ve defined a local variable QUser user and initialized it with QUser.user static instance. This is done purely for brevity, alternatively, you may import the static QUser.user field.
The selectFrom method of the JPAQueryFactory starts building a query. We pass it to the QUser instance and continue building the conditional clause of the query with the .where() method. The user.login is a reference to a StringPath field of the QUser class that we’ve seen before. The StringPath object also has the .eq() method that allows to fluently continue building the query by specifying the field equality condition.
Finally, to fetch the value from the database into the persistence context, we end the building chain with the call to the fetchOne() method. This method returns null if the object can’t be found, but throws a NonUniqueResultException if there are multiple entities satisfying the .where() condition.
4.2. Ordering and Grouping
Now let’s fetch all users in a list, sorted by their login in ascension order.
List<User> c = queryFactory.selectFrom(user)
.orderBy(user.login.asc())
.fetch();
This syntax is possible because the *Path classes have the .asc() and .desc() methods. You can also specify several arguments for the .orderBy() method to sort by multiple fields.
Now let’s try something more difficult. Suppose we need to group all posts by title and count duplicating titles. This is done with the .groupBy() clause. We’ll also want to order the titles by resulting occurrence count.
NumberPath<Long> count = Expressions.numberPath(Long.class, "c");
List<Tuple> userTitleCounts = queryFactory.select(
blogPost.title, blogPost.id.count().as(count))
.from(blogPost)
.groupBy(blogPost.title)
.orderBy(count.desc())
.fetch();
We selected the blog post title and count of duplicates, grouping by title and then ordering by aggregated count. Notice we first created an alias for the count() field in the .select() clause, because we needed to reference it in the .orderBy() clause.
4.3. Complex Queries With Joins and Subqueries
Let’s find all users that wrote a post titled “Hello World!” For such query, we could use an inner join. Notice we’ve created an alias blogPost for the joined table to reference it in the .on() clause:
QBlogPost blogPost = QBlogPost.blogPost;
List<User> users = queryFactory.selectFrom(user)
.innerJoin(user.blogPosts, blogPost)
.on(blogPost.title.eq("Hello World!"))
.fetch();
Now let’s try to achieve the same with a subquery:
List<User> users = queryFactory.selectFrom(user)
.where(user.id.in(
JPAExpressions.select(blogPost.user.id)
.from(blogPost)
.where(blogPost.title.eq("Hello World!"))))
.fetch();
As we can see, subqueries are very similar to queries, and they are also quite readable, but they start with JPAExpressions factory methods. To connect subqueries with the main query, as always, we reference the aliases defined and used earlier.
4.4. Modifying Data
JPAQueryFactory allows not only constructing queries but also modifying and deleting records. Let’s change the user’s login and disable the account:
queryFactory.update(user)
.where(user.login.eq("Ash"))
.set(user.login, "Ash2")
.set(user.disabled, true)
.execute();
We can have any number of .set() clauses we want for different fields. The .where() clause is not necessary, so we can update all the records at once.
To delete the records matching a certain condition, we can use a similar syntax:
queryFactory.delete(user)
.where(user.login.eq("David"))
.execute();
The .where() clause is also not necessary, but be careful, because omitting the .where() clause results in deleting all of the entities of a certain type.
You may wonder, why JPAQueryFactory doesn’t have the .insert() method. This is a limitation of the JPA Query interface. The underlying jakarta.persistence.Query.executeUpdate() method is capable of executing update and delete but not insert statements. To insert data, you should simply persist the entities with EntityManager.
If you still want to take advantage of a similar Querydsl syntax for inserting data, you should use SQLQueryFactory class that resides in the querydsl-sql library.
5. Conclusion
In this article, we’ve discovered a powerful and type-safe API for persistent object manipulation that is provided by Querydsl.
We’ve learned to add Querydsl to the project and explored the generated Q-types. We’ve also covered some typical use cases and enjoyed their conciseness and readability.
All the source code for the examples can be found in the GitHub repository.
Finally, there are of course many more features that Querydsl provides, including working with raw SQL, non-persistent collections, NoSQL databases and full-text search – and we’ll explore some of these in future articles.