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Spring Data Object Mapping Fundamentals
This section covers the fundamentals of Spring Data object mapping, object creation, field and property access, mutability and immutability.
Core responsibility of the Spring Data object mapping is to create instances of domain objects and map the store-native data structures onto those. This means we need two fundamental steps:
-
Instance creation by using one of the constructors exposed.
-
Instance population to materialize all exposed properties.
Object creation
Spring Data automatically tries to detect a persistent entity’s constructor to be used to materialize objects of that type. The resolution algorithm works as follows:
-
If there is a no-argument constructor, it will be used. Other constructors will be ignored.
-
If there is a single constructor taking arguments, it will be used.
-
If there are multiple constructors taking arguments, the one to be used by Spring Data will have to be annotated with
@PersistenceCreator
.
The value resolution assumes constructor argument names to match the property names of the entity, i.e. the resolution will be performed as if the property was to be populated, including all customizations in mapping (different datastore column or field name etc.).
This also requires either parameter names information available in the class file or an @ConstructorProperties
annotation being present on the constructor.
Property population
Once an instance of the entity has been created, Spring Data populates all remaining persistent properties of that class. Unless already populated by the entity’s constructor (i.e. consumed through its constructor argument list), the identifier property will be populated first to allow the resolution of cyclic object references. After that, all non-transient properties that have not already been populated by the constructor are set on the entity instance. For that we use the following algorithm:
-
If the property is immutable but exposes a wither method (see below), we use the wither to create a new entity instance with the new property value.
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If property access (i.e. access through getters and setters) is defined, we are invoking the setter method.
-
By default, we set the field value directly.
Let’s have a look at the following entity:
class Person {
private final @Id Long id; (1)
private final String firstname, lastname; (2)
private final LocalDate birthday;
private final int age; (3)
private String comment; (4)
private @AccessType(Type.PROPERTY) String remarks; (5)
static Person of(String firstname, String lastname, LocalDate birthday) { (6)
return new Person(null, firstname, lastname, birthday,
Period.between(birthday, LocalDate.now()).getYears());
}
Person(Long id, String firstname, String lastname, LocalDate birthday, int age) { (6)
this.id = id;
this.firstname = firstname;
this.lastname = lastname;
this.birthday = birthday;
this.age = age;
}
Person withId(Long id) { (1)
return new Person(id, this.firstname, this.lastname, this.birthday);
}
void setRemarks(String remarks) { (5)
this.remarks = remarks;
}
}
1 | The identifier property is final but set to null in the constructor.
The class exposes a withId(…) method that’s used to set the identifier, e.g. when an instance is inserted into the datastore and an identifier has been generated.
The original Vertex instance stays unchanged as a new one is created.
The same pattern is usually applied for other properties that are store managed but might have to be changed for persistence operations. |
2 | The firstname and lastname properties are ordinary immutable properties potentially exposed through getters. |
3 | The age property is an immutable but derived one from the birthday property.
With the design shown, the database value will trump the defaulting as Spring Data uses the only declared constructor.
Even if the intent is that the calculation should be preferred, it’s important that this constructor also takes age as parameter (to potentially ignore it) as otherwise the property population step will attempt to set the age field and fail due to it being immutable and no wither being present. |
4 | The comment property is mutable is populated by setting its field directly. |
5 | The remarks properties are mutable and populated by setting the comment field directly or by invoking the setter method for |
6 | The class exposes a factory method and a constructor for object creation.
The core idea here is to use factory methods instead of additional constructors to avoid the need for constructor disambiguation through @PersistenceCreator .
Instead, defaulting of properties is handled within the factory method. |
General recommendations
-
Try to stick to immutable objects — Immutable objects are straightforward to create as materializing an object is then a matter of calling its constructor only. Also, this prevents your domain objects from being littered with setter methods that allow client code to manipulate the objects state. If you need those, prefer to make them package protected so that they can only be invoked by a limited amount of co-located types. Constructor-only materialization is up to 30% faster than properties population.
-
Provide an all-args constructor — Even if you cannot or don’t want to model your entities as immutable values, there’s still value in providing a constructor that takes all properties of the entity as arguments, including the mutable ones, as this allows the object mapping to skip the property population for optimal performance.
-
Use factory methods instead of overloaded constructors to avoid
@PersistenceCreator
— With an all-argument constructor needed for optimal performance, we usually want to expose more application use case specific constructors that omit things like auto-generated identifiers etc. It’s an established pattern to rather use static factory methods to expose these variants of the all-args constructor. -
Make sure you adhere to the constraints that allow the generated instantiator and property accessor classes to be used
-
For identifiers to be generated, still use a final field in combination with a wither method
-
Use Lombok to avoid boilerplate code — As persistence operations usually require a constructor taking all arguments, their declaration becomes a tedious repetition of boilerplate parameter to field assignments that can best be avoided by using Lombok’s
@AllArgsConstructor
.
A note on immutable mapping
Although we recommend to use immutable mapping and constructs wherever possible, there are some limitations when it comes to mapping.
Given a bidirectional relationship where A
has a constructor reference to B
and B
has a reference to A
, or a more complex scenario.
This hen/egg situation is not solvable for Spring Data Neo4j.
During the instantiation of A
it eagerly needs to have a fully instantiated B
, which on the other hand requires an instance (to be precise, the same instance) of A
.
SDN allows such models in general, but will throw a MappingException
at runtime if the data that gets returned from the database contains such constellation as described above.
In such cases or scenarios, where you cannot foresee what the data that gets returned looks like, you are better suited with a mutable field for the relationships.
Kotlin support
Spring Data adapts specifics of Kotlin to allow object creation and mutation.
Kotlin object creation
Kotlin classes are supported to be instantiated , all classes are immutable by default and require explicit property declarations to define mutable properties.
Consider the following data
class Vertex
:
data class Person(val id: String, val name: String)
The class above compiles to a typical class with an explicit constructor.
We can customize this class by adding another constructor and annotate it with @PersistenceCreator
to indicate a constructor preference:
data class Person(var id: String, val name: String) {
@PersistenceCreator
constructor(id: String) : this(id, "unknown")
}
Kotlin supports parameter optionality by allowing default values to be used if a parameter is not provided.
When Spring Data detects a constructor with parameter defaulting, then it leaves these parameters absent if the data store does not provide a value (or simply returns null
) so Kotlin can apply parameter defaulting.
Consider the following class that applies parameter defaulting for name
data class Person(var id: String, val name: String = "unknown")
Every time the name
parameter is either not part of the result or its value is null
, then the name
defaults to unknown
.
Property population of Kotlin data classes
In Kotlin, all classes are immutable by default and require explicit property declarations to define mutable properties.
Consider the following data
class Vertex
:
data class Person(val id: String, val name: String)
This class is effectively immutable.
It allows creating new instances as Kotlin generates a copy(…)
method that creates new object instances copying all property values from the existing object and applying property values provided as arguments to the method.