# Preface
The Spring Data Commons project applies core Spring concepts to the development of solutions using many relational and non-relational data stores.
## 1. Project Metadata
* Version control: [https://github.com/spring-projects/spring-data-commons](https://github.com/spring-projects/spring-data-commons)
* Bugtracker: [https://github.com/spring-projects/spring-data-commons/issues](https://github.com/spring-projects/spring-data-commons/issues)
* Release repository: [https://repo.spring.io/libs-release](https://repo.spring.io/libs-release)
* Milestone repository: [https://repo.spring.io/libs-milestone](https://repo.spring.io/libs-milestone)
* Snapshot repository: [https://repo.spring.io/libs-snapshot](https://repo.spring.io/libs-snapshot)
## Reference Documentation
## 2. Dependencies
Due to the different inception dates of individual Spring Data modules, most of them carry different major and minor version numbers. The easiest way to find compatible ones is to rely on the Spring Data Release Train BOM that we ship with the compatible versions defined. In a Maven project, you would declare this dependency in the `` section of your POM as follows:
Example 1. Using the Spring Data release train BOM
```
org.springframework.dataspring-data-bom2021.1.2importpom
```
The current release train version is `2021.1.2`. The train version uses [calver](https://calver.org/) with the pattern `YYYY.MINOR.MICRO`.
The version name follows `${calver}` for GA releases and service releases and the following pattern for all other versions: `${calver}-${modifier}`, where `modifier` can be one of the following:
* `SNAPSHOT`: Current snapshots
* `M1`, `M2`, and so on: Milestones
* `RC1`, `RC2`, and so on: Release candidates
You can find a working example of using the BOMs in our [Spring Data examples repository](https://github.com/spring-projects/spring-data-examples/tree/master/bom). With that in place, you can declare the Spring Data modules you would like to use without a version in the `` block, as follows:
Example 2. Declaring a dependency to a Spring Data module
```
org.springframework.dataspring-data-jpa
```
### 2.1. Dependency Management with Spring Boot
Spring Boot selects a recent version of Spring Data modules for you. If you still want to upgrade to a newer version, set
the `spring-data-releasetrain.version` property to the [train version and iteration](#dependencies.train-version) you would like to use.
### 2.2. Spring Framework
The current version of Spring Data modules require Spring Framework 5.3.16 or better. The modules might also work with an older bugfix version of that minor version. However, using the most recent version within that generation is highly recommended.
## 3. Object Mapping Fundamentals
This section covers the fundamentals of Spring Data object mapping, object creation, field and property access, mutability and immutability.
Note, that this section only applies to Spring Data modules that do not use the object mapping of the underlying data store (like JPA).
Also be sure to consult the store-specific sections for store-specific object mapping, like indexes, customizing column or field names or the like.
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:
1. Instance creation by using one of the constructors exposed.
2. Instance population to materialize all exposed properties.
### 3.1. 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:
1. If there is a single constructor, it is used.
2. If there are multiple constructors and exactly one is annotated with `@PersistenceConstructor`, it is used.
3. If there’s a no-argument constructor, it is used.
Other constructors will be ignored.
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.
The value resolution can be customized by using Spring Framework’s `@Value` value annotation using a store-specific SpEL expression.
Please consult the section on store specific mappings for further details.
Object creation internals
To avoid the overhead of reflection, Spring Data object creation uses a factory class generated at runtime by default, which will call the domain classes constructor directly.
I.e. for this example type:
```
class Person {
Person(String firstname, String lastname) { … }
}
```
we will create a factory class semantically equivalent to this one at runtime:
```
class PersonObjectInstantiator implements ObjectInstantiator {
Object newInstance(Object... args) {
return new Person((String) args[0], (String) args[1]);
}
}
```
This gives us a roundabout 10% performance boost over reflection.
For the domain class to be eligible for such optimization, it needs to adhere to a set of constraints:
* it must not be a private class
* it must not be a non-static inner class
* it must not be a CGLib proxy class
* the constructor to be used by Spring Data must not be private
If any of these criteria match, Spring Data will fall back to entity instantiation via reflection.
### 3.2. 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:
1. If the property is immutable but exposes a `with…` method (see below), we use the `with…` method to create a new entity instance with the new property value.
2. If property access (i.e. access through getters and setters) is defined, we’re invoking the setter method.
3. If the property is mutable we set the field directly.
4. If the property is immutable we’re using the constructor to be used by persistence operations (see [Object creation](#mapping.object-creation)) to create a copy of the instance.
5. By default, we set the field value directly.
Property population internals
Similarly to our [optimizations in object construction](#mapping.object-creation.details) we also use Spring Data runtime generated accessor classes to interact with the entity instance.
```
class Person {
private final Long id;
private String firstname;
private @AccessType(Type.PROPERTY) String lastname;
Person() {
this.id = null;
}
Person(Long id, String firstname, String lastname) {
// Field assignments
}
Person withId(Long id) {
return new Person(id, this.firstname, this.lastame);
}
void setLastname(String lastname) {
this.lastname = lastname;
}
}
```
Example 3. A generated Property Accessor
```
class PersonPropertyAccessor implements PersistentPropertyAccessor {
private static final MethodHandle firstname; (2)
private Person person; (1)
public void setProperty(PersistentProperty property, Object value) {
String name = property.getName();
if ("firstname".equals(name)) {
firstname.invoke(person, (String) value); (2)
} else if ("id".equals(name)) {
this.person = person.withId((Long) value); (3)
} else if ("lastname".equals(name)) {
this.person.setLastname((String) value); (4)
}
}
}
```
|**1**| PropertyAccessor’s hold a mutable instance of the underlying object. This is, to enable mutations of otherwise immutable properties. |
|-----|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|**2**| By default, Spring Data uses field-access to read and write property values. As per visibility rules of `private` fields, `MethodHandles` are used to interact with fields. |
|**3**|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. Calling `withId(…)` creates a new `Person` object. All subsequent mutations will take place in the new instance leaving the previous untouched.|
|**4**| Using property-access allows direct method invocations without using `MethodHandles`. |
This gives us a roundabout 25% performance boost over reflection.
For the domain class to be eligible for such optimization, it needs to adhere to a set of constraints:
* Types must not reside in the default or under the `java` package.
* Types and their constructors must be `public`
* Types that are inner classes must be `static`.
* The used Java Runtime must allow for declaring classes in the originating `ClassLoader`. Java 9 and newer impose certain limitations.
By default, Spring Data attempts to use generated property accessors and falls back to reflection-based ones if a limitation is detected.
Let’s have a look at the following entity:
Example 4. A sample 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, this.age);
}
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 `Person` 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. The wither method is optional as the persistence constructor (see 6) is effectively a copy constructor and setting the property will be translated into creating a fresh instance with the new identifier value applied.|
|-----|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|**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 `with…` method 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 `@PersistenceConstructor`. Instead, defaulting of properties is handled within the factory method. |
### 3.3. 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 avoids your domain objects to be 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 `@PersistenceConstructor`* — 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 an all-arguments persistence constructor (preferred) or a `with…` 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`.
#### 3.3.1. Overriding Properties
Java’s allows a flexible design of domain classes where a subclass could define a property that is already declared with the same name in its superclass.
Consider the following example:
```
public class SuperType {
private CharSequence field;
public SuperType(CharSequence field) {
this.field = field;
}
public CharSequence getField() {
return this.field;
}
public void setField(CharSequence field) {
this.field = field;
}
}
public class SubType extends SuperType {
private String field;
public SubType(String field) {
super(field);
this.field = field;
}
@Override
public String getField() {
return this.field;
}
public void setField(String field) {
this.field = field;
// optional
super.setField(field);
}
}
```
Both classes define a `field` using assignable types. `SubType` however shadows `SuperType.field`.
Depending on the class design, using the constructor could be the only default approach to set `SuperType.field`.
Alternatively, calling `super.setField(…)` in the setter could set the `field` in `SuperType`.
All these mechanisms create conflicts to some degree because the properties share the same name yet might represent two distinct values.
Spring Data skips super-type properties if types are not assignable.
That is, the type of the overridden property must be assignable to its super-type property type to be registered as override, otherwise the super-type property is considered transient.
We generally recommend using distinct property names.
Spring Data modules generally support overridden properties holding different values.
From a programming model perspective there are a few things to consider:
1. Which property should be persisted (default to all declared properties)?
You can exclude properties by annotating these with `@Transient`.
2. How to represent properties in your data store?
Using the same field/column name for different values typically leads to corrupt data so you should annotate least one of the properties using an explicit field/column name.
3. Using `@AccessType(PROPERTY)` cannot be used as the super-property cannot be generally set without making any further assumptions of the setter implementation.
### 3.4. Kotlin support
Spring Data adapts specifics of Kotlin to allow object creation and mutation.
#### 3.4.1. 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 `Person`:
```
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 `@PersistenceConstructor` to indicate a constructor preference:
```
data class Person(var id: String, val name: String) {
@PersistenceConstructor
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`.
#### 3.4.2. 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 `Person`:
```
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.
#### 3.4.3. Kotlin Overriding Properties
Kotlin allows declaring [property overrides](https://kotlinlang.org/docs/inheritance.html#overriding-properties) to alter properties in subclasses.
```
open class SuperType(open var field: Int)
class SubType(override var field: Int = 1) :
SuperType(field) {
}
```
Such an arrangement renders two properties with the name `field`.
Kotlin generates property accessors (getters and setters) for each property in each class.
Effectively, the code looks like as follows:
```
public class SuperType {
private int field;
public SuperType(int field) {
this.field = field;
}
public int getField() {
return this.field;
}
public void setField(int field) {
this.field = field;
}
}
public final class SubType extends SuperType {
private int field;
public SubType(int field) {
super(field);
this.field = field;
}
public int getField() {
return this.field;
}
public void setField(int field) {
this.field = field;
}
}
```
Getters and setters on `SubType` set only `SubType.field` and not `SuperType.field`.
In such an arrangement, using the constructor is the only default approach to set `SuperType.field`.
Adding a method to `SubType` to set `SuperType.field` via `this.SuperType.field = …` is possible but falls outside of supported conventions.
Property overrides create conflicts to some degree because the properties share the same name yet might represent two distinct values.
We generally recommend using distinct property names.
Spring Data modules generally support overridden properties holding different values.
From a programming model perspective there are a few things to consider:
1. Which property should be persisted (default to all declared properties)?
You can exclude properties by annotating these with `@Transient`.
2. How to represent properties in your data store?
Using the same field/column name for different values typically leads to corrupt data so you should annotate least one of the properties using an explicit field/column name.
3. Using `@AccessType(PROPERTY)` cannot be used as the super-property cannot be set.
## 4. Working with Spring Data Repositories
The goal of the Spring Data repository abstraction is to significantly reduce the amount of boilerplate code required to implement data access layers for various persistence stores.
| |*Spring Data repository documentation and your module*
This chapter explains the core concepts and interfaces of Spring Data repositories. The information in this chapter is pulled from the Spring Data Commons module. It uses the configuration and code samples for the Java Persistence API (JPA) module. You should adapt the XML namespace declaration and the types to be extended to the equivalents of the particular module that you use. “[Namespace reference](#repositories.namespace-reference)” covers XML configuration, which is supported across all Spring Data modules that support the repository API. “[Repository query keywords](#repository-query-keywords)” covers the query method keywords supported by the repository abstraction in general. For detailed information on the specific features of your module, see the chapter on that module of this document.|
|---|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
### 4.1. Core concepts
The central interface in the Spring Data repository abstraction is `Repository`.
It takes the domain class to manage as well as the ID type of the domain class as type arguments.
This interface acts primarily as a marker interface to capture the types to work with and to help you to discover interfaces that extend this one.
The [`CrudRepository`](https://docs.spring.io/spring-data/commons/docs/current/api/org/springframework/data/repository/CrudRepository.html) interface provides sophisticated CRUD functionality for the entity class that is being managed.
Example 5. `CrudRepository` Interface
```
public interface CrudRepository extends Repository {
S save(S entity); (1)
Optional findById(ID primaryKey); (2)
Iterable findAll(); (3)
long count(); (4)
void delete(T entity); (5)
boolean existsById(ID primaryKey); (6)
// … more functionality omitted.
}
```
|**1**| Saves the given entity. |
|-----|-----------------------------------------------------|
|**2**| Returns the entity identified by the given ID. |
|**3**| Returns all entities. |
|**4**| Returns the number of entities. |
|**5**| Deletes the given entity. |
|**6**|Indicates whether an entity with the given ID exists.|
| |We also provide persistence technology-specific abstractions, such as `JpaRepository` or `MongoRepository`. Those interfaces extend `CrudRepository` and expose the capabilities of the underlying persistence technology in addition to the rather generic persistence technology-agnostic interfaces such as `CrudRepository`.|
|---|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
On top of the `CrudRepository`, there is a [`PagingAndSortingRepository`](https://docs.spring.io/spring-data/commons/docs/current/api/org/springframework/data/repository/PagingAndSortingRepository.html) abstraction that adds additional methods to ease paginated access to entities:
Example 6. `PagingAndSortingRepository` interface
```
public interface PagingAndSortingRepository extends CrudRepository {
Iterable findAll(Sort sort);
Page findAll(Pageable pageable);
}
```
To access the second page of `User` by a page size of 20, you could do something like the following:
```
PagingAndSortingRepository repository = // … get access to a bean
Page users = repository.findAll(PageRequest.of(1, 20));
```
In addition to query methods, query derivation for both count and delete queries is available.
The following list shows the interface definition for a derived count query:
Example 7. Derived Count Query
```
interface UserRepository extends CrudRepository {
long countByLastname(String lastname);
}
```
The following listing shows the interface definition for a derived delete query:
Example 8. Derived Delete Query
```
interface UserRepository extends CrudRepository {
long deleteByLastname(String lastname);
List removeByLastname(String lastname);
}
```
### 4.2. Query Methods
Standard CRUD functionality repositories usually have queries on the underlying datastore.
With Spring Data, declaring those queries becomes a four-step process:
1. Declare an interface extending Repository or one of its subinterfaces and type it to the domain class and ID type that it should handle, as shown in the following example:
```
interface PersonRepository extends Repository { … }
```
2. Declare query methods on the interface.
```
interface PersonRepository extends Repository {
List findByLastname(String lastname);
}
```
3. Set up Spring to create proxy instances for those interfaces, either with [JavaConfig](#repositories.create-instances.java-config) or with [XML configuration](#repositories.create-instances).
1. To use Java configuration, create a class similar to the following:
```
import org.springframework.data.jpa.repository.config.EnableJpaRepositories;
@EnableJpaRepositories
class Config { … }
```
2. To use XML configuration, define a bean similar to the following:
```
```
The JPA namespace is used in this example.
If you use the repository abstraction for any other store, you need to change this to the appropriate namespace declaration of your store module.
In other words, you should exchange `jpa` in favor of, for example, `mongodb`.
Also, note that the JavaConfig variant does not configure a package explicitly, because the package of the annotated class is used by default.
To customize the package to scan, use one of the `basePackage…` attributes of the data-store-specific repository’s `@Enable${store}Repositories`-annotation.
4. Inject the repository instance and use it, as shown in the following example:
```
class SomeClient {
private final PersonRepository repository;
SomeClient(PersonRepository repository) {
this.repository = repository;
}
void doSomething() {
List persons = repository.findByLastname("Matthews");
}
}
```
The sections that follow explain each step in detail:
* [Defining Repository Interfaces](#repositories.definition)
* [Defining Query Methods](#repositories.query-methods.details)
* [Creating Repository Instances](#repositories.create-instances)
* [Custom Implementations for Spring Data Repositories](#repositories.custom-implementations)
### 4.3. Defining Repository Interfaces
To define a repository interface, you first need to define a domain class-specific repository interface.
The interface must extend `Repository` and be typed to the domain class and an ID type.
If you want to expose CRUD methods for that domain type, extend `CrudRepository` instead of `Repository`.
#### 4.3.1. Fine-tuning Repository Definition
Typically, your repository interface extends `Repository`, `CrudRepository`, or `PagingAndSortingRepository`.
Alternatively, if you do not want to extend Spring Data interfaces, you can also annotate your repository interface with `@RepositoryDefinition`.
Extending `CrudRepository` exposes a complete set of methods to manipulate your entities.
If you prefer to be selective about the methods being exposed, copy the methods you want to expose from `CrudRepository` into your domain repository.
| |Doing so lets you define your own abstractions on top of the provided Spring Data Repositories functionality.|
|---|-------------------------------------------------------------------------------------------------------------|
The following example shows how to selectively expose CRUD methods (`findById` and `save`, in this case):
Example 9. Selectively exposing CRUD methods
```
@NoRepositoryBean
interface MyBaseRepository extends Repository {
Optional findById(ID id);
S save(S entity);
}
interface UserRepository extends MyBaseRepository {
User findByEmailAddress(EmailAddress emailAddress);
}
```
In the prior example, you defined a common base interface for all your domain repositories and exposed `findById(…)` as well as `save(…)`.These methods are routed into the base repository implementation of the store of your choice provided by Spring Data (for example, if you use JPA, the implementation is `SimpleJpaRepository`), because they match the method signatures in `CrudRepository`.
So the `UserRepository` can now save users, find individual users by ID, and trigger a query to find `Users` by email address.
| |The intermediate repository interface is annotated with `@NoRepositoryBean`. Make sure you add that annotation to all repository interfaces for which Spring Data should not create instances at runtime.|
|---|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
#### 4.3.2. Using Repositories with Multiple Spring Data Modules
Using a unique Spring Data module in your application makes things simple, because all repository interfaces in the defined scope are bound to the Spring Data module.
Sometimes, applications require using more than one Spring Data module.
In such cases, a repository definition must distinguish between persistence technologies.
When it detects multiple repository factories on the class path, Spring Data enters strict repository configuration mode.
Strict configuration uses details on the repository or the domain class to decide about Spring Data module binding for a repository definition:
1. If the repository definition [extends the module-specific repository](#repositories.multiple-modules.types), it is a valid candidate for the particular Spring Data module.
2. If the domain class is [annotated with the module-specific type annotation](#repositories.multiple-modules.annotations), it is a valid candidate for the particular Spring Data module.
Spring Data modules accept either third-party annotations (such as JPA’s `@Entity`) or provide their own annotations (such as `@Document` for Spring Data MongoDB and Spring Data Elasticsearch).
The following example shows a repository that uses module-specific interfaces (JPA in this case):
Example 10. Repository definitions using module-specific interfaces
```
interface MyRepository extends JpaRepository { }
@NoRepositoryBean
interface MyBaseRepository extends JpaRepository { … }
interface UserRepository extends MyBaseRepository { … }
```
`MyRepository` and `UserRepository` extend `JpaRepository` in their type hierarchy.
They are valid candidates for the Spring Data JPA module.
The following example shows a repository that uses generic interfaces:
Example 11. Repository definitions using generic interfaces
```
interface AmbiguousRepository extends Repository { … }
@NoRepositoryBean
interface MyBaseRepository extends CrudRepository { … }
interface AmbiguousUserRepository extends MyBaseRepository { … }
```
`AmbiguousRepository` and `AmbiguousUserRepository` extend only `Repository` and `CrudRepository` in their type hierarchy.
While this is fine when using a unique Spring Data module, multiple modules cannot distinguish to which particular Spring Data these repositories should be bound.
The following example shows a repository that uses domain classes with annotations:
Example 12. Repository definitions using domain classes with annotations
```
interface PersonRepository extends Repository { … }
@Entity
class Person { … }
interface UserRepository extends Repository { … }
@Document
class User { … }
```
`PersonRepository` references `Person`, which is annotated with the JPA `@Entity` annotation, so this repository clearly belongs to Spring Data JPA. `UserRepository` references `User`, which is annotated with Spring Data MongoDB’s `@Document` annotation.
The following bad example shows a repository that uses domain classes with mixed annotations:
Example 13. Repository definitions using domain classes with mixed annotations
```
interface JpaPersonRepository extends Repository { … }
interface MongoDBPersonRepository extends Repository { … }
@Entity
@Document
class Person { … }
```
This example shows a domain class using both JPA and Spring Data MongoDB annotations.
It defines two repositories, `JpaPersonRepository` and `MongoDBPersonRepository`.
One is intended for JPA and the other for MongoDB usage.
Spring Data is no longer able to tell the repositories apart, which leads to undefined behavior.
[Repository type details](#repositories.multiple-modules.types) and [distinguishing domain class annotations](#repositories.multiple-modules.annotations) are used for strict repository configuration to identify repository candidates for a particular Spring Data module.
Using multiple persistence technology-specific annotations on the same domain type is possible and enables reuse of domain types across multiple persistence technologies.
However, Spring Data can then no longer determine a unique module with which to bind the repository.
The last way to distinguish repositories is by scoping repository base packages.
Base packages define the starting points for scanning for repository interface definitions, which implies having repository definitions located in the appropriate packages.
By default, annotation-driven configuration uses the package of the configuration class.
The [base package in XML-based configuration](#repositories.create-instances.spring) is mandatory.
The following example shows annotation-driven configuration of base packages:
Example 14. Annotation-driven configuration of base packages
```
@EnableJpaRepositories(basePackages = "com.acme.repositories.jpa")
@EnableMongoRepositories(basePackages = "com.acme.repositories.mongo")
class Configuration { … }
```
### 4.4. Defining Query Methods
The repository proxy has two ways to derive a store-specific query from the method name:
* By deriving the query from the method name directly.
* By using a manually defined query.
Available options depend on the actual store.
However, there must be a strategy that decides what actual query is created.
The next section describes the available options.
#### 4.4.1. Query Lookup Strategies
The following strategies are available for the repository infrastructure to resolve the query.
With XML configuration, you can configure the strategy at the namespace through the `query-lookup-strategy` attribute.
For Java configuration, you can use the `queryLookupStrategy` attribute of the `Enable${store}Repositories` annotation.
Some strategies may not be supported for particular datastores.
* `CREATE` attempts to construct a store-specific query from the query method name.
The general approach is to remove a given set of well known prefixes from the method name and parse the rest of the method.
You can read more about query construction in “[Query Creation](#repositories.query-methods.query-creation)”.
* `USE_DECLARED_QUERY` tries to find a declared query and throws an exception if it cannot find one.
The query can be defined by an annotation somewhere or declared by other means.
See the documentation of the specific store to find available options for that store.
If the repository infrastructure does not find a declared query for the method at bootstrap time, it fails.
* `CREATE_IF_NOT_FOUND` (the default) combines `CREATE` and `USE_DECLARED_QUERY`.
It looks up a declared query first, and, if no declared query is found, it creates a custom method name-based query.
This is the default lookup strategy and, thus, is used if you do not configure anything explicitly.
It allows quick query definition by method names but also custom-tuning of these queries by introducing declared queries as needed.
#### 4.4.2. Query Creation
The query builder mechanism built into the Spring Data repository infrastructure is useful for building constraining queries over entities of the repository.
The following example shows how to create a number of queries:
Example 15. Query creation from method names
```
interface PersonRepository extends Repository {
List findByEmailAddressAndLastname(EmailAddress emailAddress, String lastname);
// Enables the distinct flag for the query
List findDistinctPeopleByLastnameOrFirstname(String lastname, String firstname);
List findPeopleDistinctByLastnameOrFirstname(String lastname, String firstname);
// Enabling ignoring case for an individual property
List findByLastnameIgnoreCase(String lastname);
// Enabling ignoring case for all suitable properties
List findByLastnameAndFirstnameAllIgnoreCase(String lastname, String firstname);
// Enabling static ORDER BY for a query
List findByLastnameOrderByFirstnameAsc(String lastname);
List findByLastnameOrderByFirstnameDesc(String lastname);
}
```
Parsing query method names is divided into subject and predicate.
The first part (`find…By`, `exists…By`) defines the subject of the query, the second part forms the predicate.
The introducing clause (subject) can contain further expressions.
Any text between `find` (or other introducing keywords) and `By` is considered to be descriptive unless using one of the result-limiting keywords such as a `Distinct` to set a distinct flag on the query to be created or [`Top`/`First` to limit query results](#repositories.limit-query-result).
The appendix contains the [full list of query method subject keywords](#appendix.query.method.subject) and [query method predicate keywords including sorting and letter-casing modifiers](#appendix.query.method.predicate).
However, the first `By` acts as a delimiter to indicate the start of the actual criteria predicate.
At a very basic level, you can define conditions on entity properties and concatenate them with `And` and `Or`.
The actual result of parsing the method depends on the persistence store for which you create the query.
However, there are some general things to notice:
* The expressions are usually property traversals combined with operators that can be concatenated.
You can combine property expressions with `AND` and `OR`.
You also get support for operators such as `Between`, `LessThan`, `GreaterThan`, and `Like` for the property expressions.
The supported operators can vary by datastore, so consult the appropriate part of your reference documentation.
* The method parser supports setting an `IgnoreCase` flag for individual properties (for example, `findByLastnameIgnoreCase(…)`) or for all properties of a type that supports ignoring case (usually `String` instances — for example, `findByLastnameAndFirstnameAllIgnoreCase(…)`).
Whether ignoring cases is supported may vary by store, so consult the relevant sections in the reference documentation for the store-specific query method.
* You can apply static ordering by appending an `OrderBy` clause to the query method that references a property and by providing a sorting direction (`Asc` or `Desc`).
To create a query method that supports dynamic sorting, see “[Special parameter handling](#repositories.special-parameters)”.
#### 4.4.3. Property Expressions
Property expressions can refer only to a direct property of the managed entity, as shown in the preceding example.
At query creation time, you already make sure that the parsed property is a property of the managed domain class.
However, you can also define constraints by traversing nested properties.
Consider the following method signature:
```
List findByAddressZipCode(ZipCode zipCode);
```
Assume a `Person` has an `Address` with a `ZipCode`.
In that case, the method creates the `x.address.zipCode` property traversal.
The resolution algorithm starts by interpreting the entire part (`AddressZipCode`) as the property and checks the domain class for a property with that name (uncapitalized).
If the algorithm succeeds, it uses that property.
If not, the algorithm splits up the source at the camel-case parts from the right side into a head and a tail and tries to find the corresponding property — in our example, `AddressZip` and `Code`.
If the algorithm finds a property with that head, it takes the tail and continues building the tree down from there, splitting the tail up in the way just described.
If the first split does not match, the algorithm moves the split point to the left (`Address`, `ZipCode`) and continues.
Although this should work for most cases, it is possible for the algorithm to select the wrong property.
Suppose the `Person` class has an `addressZip` property as well.
The algorithm would match in the first split round already, choose the wrong property, and fail (as the type of `addressZip` probably has no `code` property).
To resolve this ambiguity you can use `_` inside your method name to manually define traversal points.
So our method name would be as follows:
```
List findByAddress_ZipCode(ZipCode zipCode);
```
Because we treat the underscore character as a reserved character, we strongly advise following standard Java naming conventions (that is, not using underscores in property names but using camel case instead).
#### 4.4.4. Special parameter handling
To handle parameters in your query, define method parameters as already seen in the preceding examples.
Besides that, the infrastructure recognizes certain specific types like `Pageable` and `Sort`, to apply pagination and sorting to your queries dynamically.
The following example demonstrates these features:
Example 16. Using `Pageable`, `Slice`, and `Sort` in query methods
```
Page findByLastname(String lastname, Pageable pageable);
Slice findByLastname(String lastname, Pageable pageable);
List findByLastname(String lastname, Sort sort);
List findByLastname(String lastname, Pageable pageable);
```
| |APIs taking `Sort` and `Pageable` expect non-`null` values to be handed into methods. If you do not want to apply any sorting or pagination, use `Sort.unsorted()` and `Pageable.unpaged()`.|
|---|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
The first method lets you pass an `org.springframework.data.domain.Pageable` instance to the query method to dynamically add paging to your statically defined query.
A `Page` knows about the total number of elements and pages available.
It does so by the infrastructure triggering a count query to calculate the overall number.
As this might be expensive (depending on the store used), you can instead return a `Slice`.
A `Slice` knows only about whether a next `Slice` is available, which might be sufficient when walking through a larger result set.
Sorting options are handled through the `Pageable` instance, too.
If you need only sorting, add an `org.springframework.data.domain.Sort` parameter to your method.
As you can see, returning a `List` is also possible.
In this case, the additional metadata required to build the actual `Page` instance is not created (which, in turn, means that the additional count query that would have been necessary is not issued).
Rather, it restricts the query to look up only the given range of entities.
| |To find out how many pages you get for an entire query, you have to trigger an additional count query. By default, this query is derived from the query you actually trigger.|
|---|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
##### Paging and Sorting
You can define simple sorting expressions by using property names.
You can concatenate expressions to collect multiple criteria into one expression.
Example 17. Defining sort expressions
```
Sort sort = Sort.by("firstname").ascending()
.and(Sort.by("lastname").descending());
```
For a more type-safe way to define sort expressions, start with the type for which to define the sort expression and use method references to define the properties on which to sort.
Example 18. Defining sort expressions by using the type-safe API
```
TypedSort person = Sort.sort(Person.class);
Sort sort = person.by(Person::getFirstname).ascending()
.and(person.by(Person::getLastname).descending());
```
| |`TypedSort.by(…)` makes use of runtime proxies by (typically) using CGlib, which may interfere with native image compilation when using tools such as Graal VM Native.|
|---|----------------------------------------------------------------------------------------------------------------------------------------------------------------------|
If your store implementation supports Querydsl, you can also use the generated metamodel types to define sort expressions:
Example 19. Defining sort expressions by using the Querydsl API
```
QSort sort = QSort.by(QPerson.firstname.asc())
.and(QSort.by(QPerson.lastname.desc()));
```
#### 4.4.5. Limiting Query Results
You can limit the results of query methods by using the `first` or `top` keywords, which you can use interchangeably.
You can append an optional numeric value to `top` or `first` to specify the maximum result size to be returned.
If the number is left out, a result size of 1 is assumed.
The following example shows how to limit the query size:
Example 20. Limiting the result size of a query with `Top` and `First`
```
User findFirstByOrderByLastnameAsc();
User findTopByOrderByAgeDesc();
Page queryFirst10ByLastname(String lastname, Pageable pageable);
Slice findTop3ByLastname(String lastname, Pageable pageable);
List findFirst10ByLastname(String lastname, Sort sort);
List findTop10ByLastname(String lastname, Pageable pageable);
```
The limiting expressions also support the `Distinct` keyword for datastores that support distinct queries.
Also, for the queries that limit the result set to one instance, wrapping the result into with the `Optional` keyword is supported.
If pagination or slicing is applied to a limiting query pagination (and the calculation of the number of available pages), it is applied within the limited result.
| |Limiting the results in combination with dynamic sorting by using a `Sort` parameter lets you express query methods for the 'K' smallest as well as for the 'K' biggest elements.|
|---|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
#### 4.4.6. Repository Methods Returning Collections or Iterables
Query methods that return multiple results can use standard Java `Iterable`, `List`, and `Set`.
Beyond that, we support returning Spring Data’s `Streamable`, a custom extension of `Iterable`, as well as collection types provided by [Vavr](https://www.vavr.io/).
Refer to the appendix explaining all possible [query method return types](#appendix.query.return.types).
##### Using Streamable as Query Method Return Type
You can use `Streamable` as alternative to `Iterable` or any collection type.
It provides convenience methods to access a non-parallel `Stream` (missing from `Iterable`) and the ability to directly `….filter(…)` and `….map(…)` over the elements and concatenate the `Streamable` to others:
Example 21. Using Streamable to combine query method results
```
interface PersonRepository extends Repository {
Streamable findByFirstnameContaining(String firstname);
Streamable findByLastnameContaining(String lastname);
}
Streamable result = repository.findByFirstnameContaining("av")
.and(repository.findByLastnameContaining("ea"));
```
##### Returning Custom Streamable Wrapper Types
Providing dedicated wrapper types for collections is a commonly used pattern to provide an API for a query result that returns multiple elements.
Usually, these types are used by invoking a repository method returning a collection-like type and creating an instance of the wrapper type manually.
You can avoid that additional step as Spring Data lets you use these wrapper types as query method return types if they meet the following criteria:
1. The type implements `Streamable`.
2. The type exposes either a constructor or a static factory method named `of(…)` or `valueOf(…)` that takes `Streamable` as an argument.
The following listing shows an example:
```
class Product { (1)
MonetaryAmount getPrice() { … }
}
@RequiredArgsConstructor(staticName = "of")
class Products implements Streamable { (2)
private final Streamable streamable;
public MonetaryAmount getTotal() { (3)
return streamable.stream()
.map(Priced::getPrice)
.reduce(Money.of(0), MonetaryAmount::add);
}
@Override
public Iterator iterator() { (4)
return streamable.iterator();
}
}
interface ProductRepository implements Repository {
Products findAllByDescriptionContaining(String text); (5)
}
```
|**1**| A `Product` entity that exposes API to access the product’s price. |
|-----|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|**2**|A wrapper type for a `Streamable` that can be constructed by using `Products.of(…)` (factory method created with the Lombok annotation). A standard constructor taking the `Streamable` will do as well.|
|**3**| The wrapper type exposes an additional API, calculating new values on the `Streamable`. |
|**4**| Implement the `Streamable` interface and delegate to the actual result. |
|**5**| That wrapper type `Products` can be used directly as a query method return type. You do not need to return `Streamable` and manually wrap it after the query in the repository client. |
##### Support for Vavr Collections
[Vavr](https://www.vavr.io/) is a library that embraces functional programming concepts in Java.
It ships with a custom set of collection types that you can use as query method return types, as the following table shows:
| Vavr collection type | Used Vavr implementation type |Valid Java source types|
|------------------------|----------------------------------|-----------------------|
|`io.vavr.collection.Seq`| `io.vavr.collection.List` | `java.util.Iterable` |
|`io.vavr.collection.Set`|`io.vavr.collection.LinkedHashSet`| `java.util.Iterable` |
|`io.vavr.collection.Map`|`io.vavr.collection.LinkedHashMap`| `java.util.Map` |
You can use the types in the first column (or subtypes thereof) as query method return types and get the types in the second column used as implementation type, depending on the Java type of the actual query result (third column).
Alternatively, you can declare `Traversable` (the Vavr `Iterable` equivalent), and we then derive the implementation class from the actual return value.
That is, a `java.util.List` is turned into a Vavr `List` or `Seq`, a `java.util.Set` becomes a Vavr `LinkedHashSet` `Set`, and so on.
#### 4.4.7. Null Handling of Repository Methods
As of Spring Data 2.0, repository CRUD methods that return an individual aggregate instance use Java 8’s `Optional` to indicate the potential absence of a value.
Besides that, Spring Data supports returning the following wrapper types on query methods:
* `com.google.common.base.Optional`
* `scala.Option`
* `io.vavr.control.Option`
Alternatively, query methods can choose not to use a wrapper type at all.
The absence of a query result is then indicated by returning `null`.
Repository methods returning collections, collection alternatives, wrappers, and streams are guaranteed never to return `null` but rather the corresponding empty representation.
See “[Repository query return types](#repository-query-return-types)” for details.
##### Nullability Annotations
You can express nullability constraints for repository methods by using [Spring Framework’s nullability annotations](https://docs.spring.io/spring-framework/docs/5.3.16/reference/html/core.html#null-safety).
They provide a tooling-friendly approach and opt-in `null` checks during runtime, as follows:
* [`@NonNullApi`](https://docs.spring.io/spring/docs/5.3.16/javadoc-api/org/springframework/lang/NonNullApi.html): Used on the package level to declare that the default behavior for parameters and return values is, respectively, neither to accept nor to produce `null` values.
* [`@NonNull`](https://docs.spring.io/spring/docs/5.3.16/javadoc-api/org/springframework/lang/NonNull.html): Used on a parameter or return value that must not be `null` (not needed on a parameter and return value where `@NonNullApi` applies).
* [`@Nullable`](https://docs.spring.io/spring/docs/5.3.16/javadoc-api/org/springframework/lang/Nullable.html): Used on a parameter or return value that can be `null`.
Spring annotations are meta-annotated with [JSR 305](https://jcp.org/en/jsr/detail?id=305) annotations (a dormant but widely used JSR).
JSR 305 meta-annotations let tooling vendors (such as [IDEA](https://www.jetbrains.com/help/idea/nullable-and-notnull-annotations.html), [Eclipse](https://help.eclipse.org/oxygen/index.jsp?topic=/org.eclipse.jdt.doc.user/tasks/task-using_external_null_annotations.htm), and [Kotlin](https://kotlinlang.org/docs/reference/java-interop.html#null-safety-and-platform-types)) provide null-safety support in a generic way, without having to hard-code support for Spring annotations.
To enable runtime checking of nullability constraints for query methods, you need to activate non-nullability on the package level by using Spring’s `@NonNullApi` in `package-info.java`, as shown in the following example:
Example 22. Declaring Non-nullability in `package-info.java`
```
@org.springframework.lang.NonNullApi
package com.acme;
```
Once non-null defaulting is in place, repository query method invocations get validated at runtime for nullability constraints.
If a query result violates the defined constraint, an exception is thrown.
This happens when the method would return `null` but is declared as non-nullable (the default with the annotation defined on the package in which the repository resides).
If you want to opt-in to nullable results again, selectively use `@Nullable` on individual methods.
Using the result wrapper types mentioned at the start of this section continues to work as expected: an empty result is translated into the value that represents absence.
The following example shows a number of the techniques just described:
Example 23. Using different nullability constraints
```
package com.acme; (1)
import org.springframework.lang.Nullable;
interface UserRepository extends Repository {
User getByEmailAddress(EmailAddress emailAddress); (2)
@Nullable
User findByEmailAddress(@Nullable EmailAddress emailAdress); (3)
Optional findOptionalByEmailAddress(EmailAddress emailAddress); (4)
}
```
|**1**| The repository resides in a package (or sub-package) for which we have defined non-null behavior. |
|-----|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|**2**|Throws an `EmptyResultDataAccessException` when the query does not produce a result. Throws an `IllegalArgumentException` when the `emailAddress` handed to the method is `null`.|
|**3**| Returns `null` when the query does not produce a result. Also accepts `null` as the value for `emailAddress`. |
|**4**| Returns `Optional.empty()` when the query does not produce a result. Throws an `IllegalArgumentException` when the `emailAddress` handed to the method is `null`. |
##### Nullability in Kotlin-based Repositories
Kotlin has the definition of [nullability constraints](https://kotlinlang.org/docs/reference/null-safety.html) baked into the language.
Kotlin code compiles to bytecode, which does not express nullability constraints through method signatures but rather through compiled-in metadata.
Make sure to include the `kotlin-reflect` JAR in your project to enable introspection of Kotlin’s nullability constraints.
Spring Data repositories use the language mechanism to define those constraints to apply the same runtime checks, as follows:
Example 24. Using nullability constraints on Kotlin repositories
```
interface UserRepository : Repository {
fun findByUsername(username: String): User (1)
fun findByFirstname(firstname: String?): User? (2)
}
```
|**1**|The method defines both the parameter and the result as non-nullable (the Kotlin default). The Kotlin compiler rejects method invocations that pass `null` to the method. If the query yields an empty result, an `EmptyResultDataAccessException` is thrown.|
|-----|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|**2**| This method accepts `null` for the `firstname` parameter and returns `null` if the query does not produce a result. |
#### 4.4.8. Streaming Query Results
You can process the results of query methods incrementally by using a Java 8 `Stream` as the return type.
Instead of wrapping the query results in a `Stream`, data store-specific methods are used to perform the streaming, as shown in the following example:
Example 25. Stream the result of a query with Java 8 `Stream`
```
@Query("select u from User u")
Stream findAllByCustomQueryAndStream();
Stream readAllByFirstnameNotNull();
@Query("select u from User u")
Stream streamAllPaged(Pageable pageable);
```
| |A `Stream` potentially wraps underlying data store-specific resources and must, therefore, be closed after usage. You can either manually close the `Stream` by using the `close()` method or by using a Java 7 `try-with-resources` block, as shown in the following example:|
|---|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
Example 26. Working with a `Stream` result in a `try-with-resources` block
```
try (Stream stream = repository.findAllByCustomQueryAndStream()) {
stream.forEach(…);
}
```
| |Not all Spring Data modules currently support `Stream` as a return type.|
|---|---------------------------------------------------------------------------|
#### 4.4.9. Asynchronous Query Results
You can run repository queries asynchronously by using [Spring’s asynchronous method running capability](https://docs.spring.io/spring-framework/docs/5.3.16/reference/html/integration.html#scheduling).
This means the method returns immediately upon invocation while the actual query occurs in a task that has been submitted to a Spring `TaskExecutor`.
Asynchronous queries differ from reactive queries and should not be mixed.
See the store-specific documentation for more details on reactive support.
The following example shows a number of asynchronous queries:
```
@Async
Future findByFirstname(String firstname); (1)
@Async
CompletableFuture findOneByFirstname(String firstname); (2)
@Async
ListenableFuture findOneByLastname(String lastname); (3)
```
|**1**| Use `java.util.concurrent.Future` as the return type. |
|-----|--------------------------------------------------------------------------------|
|**2**| Use a Java 8 `java.util.concurrent.CompletableFuture` as the return type. |
|**3**|Use a `org.springframework.util.concurrent.ListenableFuture` as the return type.|
### 4.5. Creating Repository Instances
This section covers how to create instances and bean definitions for the defined repository interfaces. One way to do so is by using the Spring namespace that is shipped with each Spring Data module that supports the repository mechanism, although we generally recommend using Java configuration.
#### 4.5.1. XML Configuration
Each Spring Data module includes a `repositories` element that lets you define a base package that Spring scans for you, as shown in the following example:
Example 27. Enabling Spring Data repositories via XML
```
```
In the preceding example, Spring is instructed to scan `com.acme.repositories` and all its sub-packages for interfaces extending `Repository` or one of its sub-interfaces.
For each interface found, the infrastructure registers the persistence technology-specific `FactoryBean` to create the appropriate proxies that handle invocations of the query methods.
Each bean is registered under a bean name that is derived from the interface name, so an interface of `UserRepository` would be registered under `userRepository`.
Bean names for nested repository interfaces are prefixed with their enclosing type name.
The `base-package` attribute allows wildcards so that you can define a pattern of scanned packages.
##### Using Filters
By default, the infrastructure picks up every interface that extends the persistence technology-specific `Repository` sub-interface located under the configured base package and creates a bean instance for it.
However, you might want more fine-grained control over which interfaces have bean instances created for them.
To do so, use `` and `` elements inside the `` element.
The semantics are exactly equivalent to the elements in Spring’s context namespace.
For details, see the [Spring reference documentation](https://docs.spring.io/spring-framework/docs/5.3.16/reference/html/core.html#beans-scanning-filters) for these elements.
For example, to exclude certain interfaces from instantiation as repository beans, you could use the following configuration:
Example 28. Using exclude-filter element
```
```
The preceding example excludes all interfaces ending in `SomeRepository` from being instantiated.
#### 4.5.2. Java Configuration
You can also trigger the repository infrastructure by using a store-specific `@Enable${store}Repositories` annotation on a Java configuration class. For an introduction to Java-based configuration of the Spring container, see [JavaConfig in the Spring reference documentation](https://docs.spring.io/spring-framework/docs/5.3.16/reference/html/core.html#beans-java).
A sample configuration to enable Spring Data repositories resembles the following:
Example 29. Sample annotation-based repository configuration
```
@Configuration
@EnableJpaRepositories("com.acme.repositories")
class ApplicationConfiguration {
@Bean
EntityManagerFactory entityManagerFactory() {
// …
}
}
```
| |The preceding example uses the JPA-specific annotation, which you would change according to the store module you actually use. The same applies to the definition of the `EntityManagerFactory` bean. See the sections covering the store-specific configuration.|
|---|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
#### 4.5.3. Standalone Usage
You can also use the repository infrastructure outside of a Spring container — for example, in CDI environments. You still need some Spring libraries in your classpath, but, generally, you can set up repositories programmatically as well. The Spring Data modules that provide repository support ship with a persistence technology-specific `RepositoryFactory` that you can use, as follows:
Example 30. Standalone usage of the repository factory
```
RepositoryFactorySupport factory = … // Instantiate factory here
UserRepository repository = factory.getRepository(UserRepository.class);
```
### 4.6. Custom Implementations for Spring Data Repositories
Spring Data provides various options to create query methods with little coding.
But when those options don’t fit your needs you can also provide your own custom implementation for repository methods.
This section describes how to do that.
#### 4.6.1. Customizing Individual Repositories
To enrich a repository with custom functionality, you must first define a fragment interface and an implementation for the custom functionality, as follows:
Example 31. Interface for custom repository functionality
```
interface CustomizedUserRepository {
void someCustomMethod(User user);
}
```
Example 32. Implementation of custom repository functionality
```
class CustomizedUserRepositoryImpl implements CustomizedUserRepository {
public void someCustomMethod(User user) {
// Your custom implementation
}
}
```
| |The most important part of the class name that corresponds to the fragment interface is the `Impl` postfix.|
|---|-----------------------------------------------------------------------------------------------------------|
The implementation itself does not depend on Spring Data and can be a regular Spring bean.Consequently, you can use standard dependency injection behavior to inject references to other beans (such as a `JdbcTemplate`), take part in aspects, and so on.
Then you can let your repository interface extend the fragment interface, as follows:
Example 33. Changes to your repository interface
```
interface UserRepository extends CrudRepository, CustomizedUserRepository {
// Declare query methods here
}
```
Extending the fragment interface with your repository interface combines the CRUD and custom functionality and makes it available to clients.
Spring Data repositories are implemented by using fragments that form a repository composition. Fragments are the base repository, functional aspects (such as [QueryDsl](#core.extensions.querydsl)), and custom interfaces along with their implementations. Each time you add an interface to your repository interface, you enhance the composition by adding a fragment. The base repository and repository aspect implementations are provided by each Spring Data module.
The following example shows custom interfaces and their implementations:
Example 34. Fragments with their implementations
```
interface HumanRepository {
void someHumanMethod(User user);
}
class HumanRepositoryImpl implements HumanRepository {
public void someHumanMethod(User user) {
// Your custom implementation
}
}
interface ContactRepository {
void someContactMethod(User user);
User anotherContactMethod(User user);
}
class ContactRepositoryImpl implements ContactRepository {
public void someContactMethod(User user) {
// Your custom implementation
}
public User anotherContactMethod(User user) {
// Your custom implementation
}
}
```
The following example shows the interface for a custom repository that extends `CrudRepository`:
Example 35. Changes to your repository interface
```
interface UserRepository extends CrudRepository, HumanRepository, ContactRepository {
// Declare query methods here
}
```
Repositories may be composed of multiple custom implementations that are imported in the order of their declaration. Custom implementations have a higher priority than the base implementation and repository aspects. This ordering lets you override base repository and aspect methods and resolves ambiguity if two fragments contribute the same method signature. Repository fragments are not limited to use in a single repository interface. Multiple repositories may use a fragment interface, letting you reuse customizations across different repositories.
The following example shows a repository fragment and its implementation:
Example 36. Fragments overriding `save(…)`
```
interface CustomizedSave {
S save(S entity);
}
class CustomizedSaveImpl implements CustomizedSave {
public S save(S entity) {
// Your custom implementation
}
}
```
The following example shows a repository that uses the preceding repository fragment:
Example 37. Customized repository interfaces
```
interface UserRepository extends CrudRepository, CustomizedSave {
}
interface PersonRepository extends CrudRepository, CustomizedSave {
}
```
##### Configuration
If you use namespace configuration, the repository infrastructure tries to autodetect custom implementation fragments by scanning for classes below the package in which it found a repository.
These classes need to follow the naming convention of appending the namespace element’s `repository-impl-postfix` attribute to the fragment interface name.
This postfix defaults to `Impl`.
The following example shows a repository that uses the default postfix and a repository that sets a custom value for the postfix:
Example 38. Configuration example
```
```
The first configuration in the preceding example tries to look up a class called `com.acme.repository.CustomizedUserRepositoryImpl` to act as a custom repository implementation.
The second example tries to look up `com.acme.repository.CustomizedUserRepositoryMyPostfix`.
###### Resolution of Ambiguity
If multiple implementations with matching class names are found in different packages, Spring Data uses the bean names to identify which one to use.
Given the following two custom implementations for the `CustomizedUserRepository` shown earlier, the first implementation is used.
Its bean name is `customizedUserRepositoryImpl`, which matches that of the fragment interface (`CustomizedUserRepository`) plus the postfix `Impl`.
Example 39. Resolution of ambiguous implementations
```
package com.acme.impl.one;
class CustomizedUserRepositoryImpl implements CustomizedUserRepository {
// Your custom implementation
}
```
```
package com.acme.impl.two;
@Component("specialCustomImpl")
class CustomizedUserRepositoryImpl implements CustomizedUserRepository {
// Your custom implementation
}
```
If you annotate the `UserRepository` interface with `@Component("specialCustom")`, the bean name plus `Impl` then matches the one defined for the repository implementation in `com.acme.impl.two`, and it is used instead of the first one.
###### Manual Wiring
If your custom implementation uses annotation-based configuration and autowiring only, the preceding approach shown works well, because it is treated as any other Spring bean.
If your implementation fragment bean needs special wiring, you can declare the bean and name it according to the conventions described in the [preceding section](#repositories.single-repository-behaviour.ambiguity).
The infrastructure then refers to the manually defined bean definition by name instead of creating one itself.
The following example shows how to manually wire a custom implementation:
Example 40. Manual wiring of custom implementations
```
```
#### 4.6.2. Customize the Base Repository
The approach described in the [preceding section](#repositories.manual-wiring) requires customization of each repository interfaces when you want to customize the base repository behavior so that all repositories are affected.
To instead change behavior for all repositories, you can create an implementation that extends the persistence technology-specific repository base class.
This class then acts as a custom base class for the repository proxies, as shown in the following example:
Example 41. Custom repository base class
```
class MyRepositoryImpl
extends SimpleJpaRepository {
private final EntityManager entityManager;
MyRepositoryImpl(JpaEntityInformation entityInformation,
EntityManager entityManager) {
super(entityInformation, entityManager);
// Keep the EntityManager around to used from the newly introduced methods.
this.entityManager = entityManager;
}
@Transactional
public S save(S entity) {
// implementation goes here
}
}
```
| |The class needs to have a constructor of the super class which the store-specific repository factory implementation uses. If the repository base class has multiple constructors, override the one taking an `EntityInformation` plus a store specific infrastructure object (such as an `EntityManager` or a template class).|
|---|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
The final step is to make the Spring Data infrastructure aware of the customized repository base class.
In Java configuration, you can do so by using the `repositoryBaseClass` attribute of the `@Enable${store}Repositories` annotation, as shown in the following example:
Example 42. Configuring a custom repository base class using JavaConfig
```
@Configuration
@EnableJpaRepositories(repositoryBaseClass = MyRepositoryImpl.class)
class ApplicationConfiguration { … }
```
A corresponding attribute is available in the XML namespace, as shown in the following example:
Example 43. Configuring a custom repository base class using XML
```
```
### 4.7. Publishing Events from Aggregate Roots
Entities managed by repositories are aggregate roots.
In a Domain-Driven Design application, these aggregate roots usually publish domain events.
Spring Data provides an annotation called `@DomainEvents` that you can use on a method of your aggregate root to make that publication as easy as possible, as shown in the following example:
Example 44. Exposing domain events from an aggregate root
```
class AnAggregateRoot {
@DomainEvents (1)
Collection