1. Overview
In this tutorial we’ll explore some of the core features of Spring Data MongoDB – indexing, common annotations and converters. We”ll use Spring Boot to fetch the transitive dependency.
2. Indexes
2.1. @Indexed
This annotation marks the field as indexed in MongoDB:
@QueryEntity
@Document
public class User {
@Indexed
private String name;
...
}
Now that the name field is indexed – let’s have a look at the indexes in MongoDB shell:
db.user.getIndexes();
Here’s what we get:
[
{
"v" : 1,
"key" : {
"_id" : 1
},
"name" : "_id_",
"ns" : "test.user"
}
]
We may be surprised there’s no sign of the name field anywhere!
This is because, as of Spring Data MongoDB 3.0, automatic index creation is turned off by default.
We can, however, change that behavior by explicitly overriding autoIndexCreation() method in our MongoConfig:
public class MongoConfig extends AbstractMongoClientConfiguration {
// rest of the config goes here
@Override
protected boolean autoIndexCreation() {
return true;
}
}
Let’s again check out the indexes in MongoDB shell:
[
{
"v" : 1,
"key" : {
"_id" : 1
},
"name" : "_id_",
"ns" : "test.user"
},
{
"v" : 1,
"key" : {
"name" : 1
},
"name" : "name",
"ns" : "test.user"
}
]
As we can see, this time, we have two indexes – one of them is _id – which was created by default due to the @Id annotation and the second one is our name field.
Setting this property in Spring boot spring.data.mongodb.auto-index-creation property to true will enable index creation on application startup.
2.2. Create an Index Programmatically
We can also create an index programmatically:
mongoOps.indexOps(User.class).
ensureIndex(new Index().on("name", Direction.ASC));
We’ve now created an index for the field name and the result will be the same as in the previous section.
2.3. Compound Indexes
MongoDB supports compound indexes, where a single index structure holds references to multiple fields.
Let’s see a quick example using compound indexes:
@QueryEntity
@Document
@CompoundIndexes({
@CompoundIndex(name = "email_age", def = "{'email.id' : 1, 'age': 1}")
})
public class User {
//
}
We created a compound index with the email and age fields. Let’s now check out the actual indexes:
{
"v" : 1,
"key" : {
"email.id" : 1,
"age" : 1
},
"name" : "email_age",
"ns" : "test.user"
}
Note that a DBRef field cannot be marked with @Index – that field can only be part of a compound index.
3. Common Annotations
3.1. @Transient
As we’d expect, this simple annotation excludes the field from being persisted in the database:
public class User {
@Transient
private Integer yearOfBirth;
// standard getter and setter
}
Let’s insert user with the setting field yearOfBirth:
User user = new User();
user.setName("Alex");
user.setYearOfBirth(1985);
mongoTemplate.insert(user);
Now if we look the state of database, we see that the filed yearOfBirth was not saved:
{
"_id" : ObjectId("55d8b30f758fd3c9f374499b"),
"name" : "Alex",
"age" : null
}
So if we query and check:
mongoTemplate.findOne(Query.query(Criteria.where("name").is("Alex")), User.class).getYearOfBirth()
The result will be null.
3.2. @Field
@Field indicates the key to be used for the field in the JSON document:
@Field("email")
private EmailAddress emailAddress;
Now emailAddress will be saved in the database using the key email:
User user = new User();
user.setName("Brendan");
EmailAddress emailAddress = new EmailAddress();
emailAddress.setValue("[email protected]");
user.setEmailAddress(emailAddress);
mongoTemplate.insert(user);
And the state of the database:
{
"_id" : ObjectId("55d076d80bad441ed114419d"),
"name" : "Brendan",
"age" : null,
"email" : {
"value" : "[email protected]"
}
}
3.3. @PersistenceConstructor and @Value
@PersistenceConstructor marks a constructor, even one that’s package protected, to be the primary constructor used by the persistence logic. The constructor arguments are mapped by name to the key values in the retrieved DBObject.
Let’s look at this constructor for our User class:
@PersistenceConstructor
public User(String name, @Value("#root.age ?: 0") Integer age, EmailAddress emailAddress) {
this.name = name;
this.age = age;
this.emailAddress = emailAddress;
}
Notice the use of the standard Spring @Value annotation here. It’s with the help of this annotation that we can use the Spring Expressions to transform a key’s value retrieved from the database before it is used to construct a domain object. That is a very powerful and highly useful feature here.
In our example if age isn’t set, it’ll be set to 0 by default.
Let’s now see how it works:
User user = new User();
user.setName("Alex");
mongoTemplate.insert(user);
Our database will look:
{
"_id" : ObjectId("55d074ca0bad45f744a71318"),
"name" : "Alex",
"age" : null
}
So the age field is null, but when we query the document and retrieve age:
mongoTemplate.findOne(Query.query(Criteria.where("name").is("Alex")), User.class).getAge();
The result will be 0.
4. Converters
Let’s now take a look at another very useful feature in Spring Data MongoDB – converters, and specifically at the MongoConverter.
This is used to handle the mapping of all Java types to DBObjects when storing and querying these objects.
We have two options – we can either work with MappingMongoConverter – or SimpleMongoConverter in earlier versions (this was deprecated in Spring Data MongoDB M3 and its functionality has been moved into MappingMongoConverter)*.
*
Or we can write our own custom converter. To do that, we would need to implement the Converter interface and register the implementation in MongoConfig.
Let’s look at a quick example. As we’ve seen in some of the JSON output here, all objects saved in a database have the field _class which is saved automatically. If however we’d like to skip that particular field during persistence, we can do that using a MappingMongoConverter.
First – here’s the custom converter implementation:
@Component
public class UserWriterConverter implements Converter<User, DBObject> {
@Override
public DBObject convert(User user) {
DBObject dbObject = new BasicDBObject();
dbObject.put("name", user.getName());
dbObject.put("age", user.getAge());
if (user.getEmailAddress() != null) {
DBObject emailDbObject = new BasicDBObject();
emailDbObject.put("value", user.getEmailAddress().getValue());
dbObject.put("email", emailDbObject);
}
dbObject.removeField("_class");
return dbObject;
}
}
Notice how we can easily hit the goal of not persisting _class by specifically removing the field directly here.
Now we need to register the custom converter:
private List<Converter<?,?>> converters = new ArrayList<Converter<?,?>>();
@Override
public MongoCustomConversions customConversions() {
converters.add(new UserWriterConverter());
return new MongoCustomConversions(converters);
}
We can of course achieve the same result with XML configuration as well, if we need to:
<bean id="mongoTemplate"
class="org.springframework.data.mongodb.core.MongoTemplate">
<constructor-arg name="mongo" ref="mongo"/>
<constructor-arg ref="mongoConverter" />
<constructor-arg name="databaseName" value="test"/>
</bean>
<mongo:mapping-converter id="mongoConverter" base-package="org.baeldung.converter">
<mongo:custom-converters base-package="com.baeldung.converter" />
</mongo:mapping-converter>
Now, when we save a new user:
User user = new User();
user.setName("Chris");
mongoOps.insert(user);
The resulting document in the database no longer contains the class information:
{
"_id" : ObjectId("55cf09790bad4394db84b853"),
"name" : "Chris",
"age" : null
}
5. Conclusion
In this tutorial we’ve covered some core concepts of working with Spring Data MongoDB – indexing, common annotations and converters.
The implementation of all these examples and code snippets can be found over on GitHub.