Spring Data JDBC - Reference Documentation

The Spring Data JDBC project applies core Spring concepts to the development of solutions that use JDBC databases aligned with Domain-driven design principles . We provide a “template” as a high-level abstraction for storing and querying aggregates.

This document is the reference guide for Spring Data JDBC Support. It explains the concepts and semantics and syntax..

This section provides some basic introduction. The rest of the document refers only to Spring Data JDBC features and assumes the user is familiar with SQL and Spring concepts.

While you need not know the Spring APIs, understanding the concepts behind them is important. At a minimum, the idea behind Inversion of Control (IoC) should be familiar, and you should be familiar with whatever IoC container you choose to use.

The core functionality of the JDBC Aggregate support can be used directly, with no need to invoke the IoC services of the Spring Container. This is much like JdbcTemplate , which can be used "'standalone'" without any other services of the Spring container. To leverage all the features of Spring Data JDBC, such as the repository support, you need to configure some parts of the library to use Spring.

To learn more about Spring, you can refer to the comprehensive documentation that explains the Spring Framework in detail. There are a lot of articles, blog entries, and books on the subject. See the Spring framework home page for more information.

The Spring Data JDBC binaries require JDK level 8.0 and above and Spring Framework 6.0.11 and above.

In terms of databases, Spring Data JDBC requires a dialect to abstract common SQL functionality over vendor-specific flavours. Spring Data JDBC includes direct support for the following databases:

Learning a new framework is not always straightforward. In this section, we try to provide what we think is an easy-to-follow guide for starting with the Spring Data JDBC module. However, if you encounter issues or you need advice, feel free to use one of the following links:

Community Forum

Spring Data on Stack Overflow is a tag for all Spring Data (not just Document) users to share information and help each other. Note that registration is needed only for posting.

For information on the Spring Data JDBC source code repository, nightly builds, and snapshot artifacts, see the Spring Data JDBC homepage . You can help make Spring Data best serve the needs of the Spring community by interacting with developers through the Community on Stack Overflow . If you encounter a bug or want to suggest an improvement, please create a ticket on the Spring Data issue tracker . To stay up to date with the latest news and announcements in the Spring eco system, subscribe to the Spring Community Portal . You can also follow the Spring blog or the project team on Twitter ( SpringData ).

Instructions for how to upgrade from earlier versions of Spring Data are provided on the project wiki . Follow the links in the release notes section to find the version that you want to upgrade to.

Upgrading instructions are always the first item in the release notes. If you are more than one release behind, please make sure that you also review the release notes of the versions that you jumped.

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 <dependencyManagement /> section of your POM as follows:

Example 1. Using the Spring Data release train BOM

<dependencyManagement>
  <dependencies>
    <dependency>
      <groupId>org.springframework.data</groupId>
      <artifactId>spring-data-bom</artifactId>
      <version>2023.0.2</version>
      <scope>import</scope>
      <type>pom</type>
    </dependency>
  </dependencies>
</dependencyManagement>

The current release train version is 2023.0.2 . The train version uses calver 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:

You can find a working example of using the BOMs in our Spring Data examples repository . With that in place, you can declare the Spring Data modules you would like to use without a version in the <dependencies /> block, as follows:

Example 2. Declaring a dependency to a Spring Data module

<dependencies>
  <dependency>
    <groupId>org.springframework.data</groupId>
    <artifactId>spring-data-jpa</artifactId>
  </dependency>
<dependencies>

7.1. Dependency Management with Spring Boot

Spring Boot selects a recent version of the Spring Data modules for you. If you still want to upgrade to a newer version, set the spring-data-bom.version property to the train version and iteration you would like to use.

See Spring Boot’s documentation (search for "Spring Data Bom") for more details.

7.2. Spring Framework

The current version of Spring Data modules require Spring Framework 6.0.11 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.

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 Jakarta Persistence API (JPA) module. “ 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.

8.1. Core concepts

The central interface in the Spring Data repository abstraction is Repository . It takes the domain class to manage as well as the identifier 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 and ListCrudRepository interfaces provide sophisticated CRUD functionality for the entity class that is being managed.

Example 3.


    CrudRepository

Interface

public interface CrudRepository<T, ID> extends Repository<T, ID> {
  <S extends T> S save(S entity);      (1)
  Optional<T> findById(ID primaryKey); (2)
  Iterable<T> findAll();               (3)
  long count();                        (4)
  void delete(T entity);               (5)
  boolean existsById(ID primaryKey);   (6)
  // … more functionality omitted.
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.
Additional to the CrudRepository, there is a PagingAndSortingRepository abstraction that adds additional methods to ease paginated access to entities:
Example 4. PagingAndSortingRepository interface
public interface PagingAndSortingRepository<T, ID>  {
  Iterable<T> findAll(Sort sort);
  Page<T> findAll(Pageable pageable);
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 5. Derived Count Query
interface UserRepository extends CrudRepository<User, Long> {
  long countByLastname(String lastname);
interface UserRepository extends CrudRepository<User, Long> {
  long deleteByLastname(String lastname);
  List<User> removeByLastname(String lastname);
8.2. Query Methods

Standard CRUD functionality repositories usually have queries on the underlying datastore.
With Spring Data, declaring those queries becomes a four-step process:
interface PersonRepository extends Repository<Person, Long> {
  List<Person> findByLastname(String lastname);
import org.springframework.data.….repository.config.EnableJpaRepositories;
@EnableJpaRepositories
class Config { … }
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 @EnableJpaRepositories-annotation.
Inject the repository instance and use it, as shown in the following example:
8.3. 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, you may extend CrudRepository, or one of its variants instead of Repository.
8.3.1. Fine-tuning Repository Definition

There are a few variants how you can get started with your repository interface.
The typical approach is to extend CrudRepository, which gives you methods for CRUD functionality.
CRUD stands for Create, Read, Update, Delete.
With version 3.0 we also introduced ListCrudRepository which is very similar to the CrudRepository but for those methods that return multiple entities it returns a List instead of an Iterable which you might find easier to use.
If you are using a reactive store you might choose ReactiveCrudRepository, or RxJava3CrudRepository depending on which reactive framework you are using.
If you are using Kotlin you might pick CoroutineCrudRepository which utilizes Kotlin’s coroutines.
Additional you can extend PagingAndSortingRepository, ReactiveSortingRepository, RxJava3SortingRepository, or CoroutineSortingRepository if you need methods that allow to specify a Sort abstraction or in the first case a Pageable abstraction.
Note that the various sorting repositories no longer extended their respective CRUD repository as they did in Spring Data Versions pre 3.0.
Therefore, you need to extend both interfaces if you want functionality of both.
If you do not want to extend Spring Data interfaces, you can also annotate your repository interface with @RepositoryDefinition.
Extending one of the CRUD repository interfaces 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 the CRUD repository into your domain repository.
When doing so, you may change the return type of methods.
Spring Data will honor the return type if possible.
For example, for methods returning multiple entities you may choose Iterable<T>, List<T>, Collection<T> or a VAVR list.
If many repositories in your application should have the same set of methods you can define your own base interface to inherit from.
Such an interface must be annotated with @NoRepositoryBean.
This prevents Spring Data to try to create an instance of it directly and failing because it can’t determine the entity for that repository, since it still contains a generic type variable.
The following example shows how to selectively expose CRUD methods (findById and save, in this case):
Example 7. Selectively exposing CRUD methods
@NoRepositoryBean
interface MyBaseRepository<T, ID> extends Repository<T, ID> {
  Optional<T> findById(ID id);
  <S extends T> S save(S entity);
interface UserRepository extends MyBaseRepository<User, Long> {
  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.
8.3.2. 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:
If the repository definition extends the module-specific repository, it is a valid candidate for the particular Spring Data module.
If the domain class is annotated with the module-specific type annotation, 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 8. Repository definitions using module-specific interfaces
interface MyRepository extends JpaRepository<User, Long> { }
@NoRepositoryBean
interface MyBaseRepository<T, ID> extends JpaRepository<T, ID> { … }
interface UserRepository extends MyBaseRepository<User, Long> { … }
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 bad example shows a repository that uses domain classes with mixed annotations:
Example 11. Repository definitions using domain classes with mixed annotations
interface JpaPersonRepository extends Repository<Person, Long> { … }
interface MongoDBPersonRepository extends Repository<Person, Long> { … }
@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 and distinguishing domain class 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 is mandatory.
The following example shows annotation-driven configuration of base packages:
Example 12. Annotation-driven configuration of base packages
@EnableJpaRepositories(basePackages = "com.acme.repositories.jpa")
@EnableMongoRepositories(basePackages = "com.acme.repositories.mongo")
class Configuration { … }
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.
8.4.1. Query Lookup Strategies

The following strategies are available for the repository infrastructure to resolve the query.
For Java configuration, you can use the queryLookupStrategy attribute of the EnableJpaRepositories 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”.
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.
8.4.2. 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 13. Query creation from method names
interface PersonRepository extends Repository<Person, Long> {
  List<Person> findByEmailAddressAndLastname(EmailAddress emailAddress, String lastname);
  // Enables the distinct flag for the query
  List<Person> findDistinctPeopleByLastnameOrFirstname(String lastname, String firstname);
  List<Person> findPeopleDistinctByLastnameOrFirstname(String lastname, String firstname);
  // Enabling ignoring case for an individual property
  List<Person> findByLastnameIgnoreCase(String lastname);
  // Enabling ignoring case for all suitable properties
  List<Person> findByLastnameAndFirstnameAllIgnoreCase(String lastname, String firstname);
  // Enabling static ORDER BY for a query
  List<Person> findByLastnameOrderByFirstnameAsc(String lastname);
  List<Person> 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.
The appendix contains the full list of query method subject keywords and query method predicate keywords including sorting and letter-casing modifiers.
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 “Paging, Iterating Large Results, Sorting”.
8.4.3. 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:
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:
8.4.4. Paging, Iterating Large Results, Sorting

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 14. Using Pageable, Slice, and Sort in query methods
Page<User> findByLastname(String lastname, Pageable pageable);
Slice<User> findByLastname(String lastname, Pageable pageable);
List<User> findByLastname(String lastname, Sort sort);
List<User> findByLastname(String lastname, Pageable pageable);
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.
Which Method is Appropriate?

The value provided by the Spring Data abstractions is perhaps best shown by the possible query method return types outlined in the following table below.
The table shows which types you can return from a query method
Table 1. Consuming Large Query Results
All results.
Single query.
Query results can exhaust all memory. Fetching all data can be time-intensive.
Streamable<T>
All results.
Single query.
Query results can exhaust all memory. Fetching all data can be time-intensive.
Stream<T>
Chunked (one-by-one or in batches) depending on Stream consumption.
Single query using typically cursors.
Streams must be closed after usage to avoid resource leaks.
Flux<T>
Chunked (one-by-one or in batches) depending on Flux consumption.
Single query using typically cursors.
Store module must provide reactive infrastructure.
Slice<T>
Pageable.getPageSize() + 1 at Pageable.getOffset()
One to many queries fetching data starting at Pageable.getOffset() applying limiting.
A Slice can only navigate to the next Slice.
Offset-based queries becomes inefficient when the offset is too large because the database still has to materialize the full result.
Window provides details whether there is more data to fetch.
Offset-based queries becomes inefficient when the offset is too large because the database still has to materialize the full result.
Page<T>
Pageable.getPageSize()  at Pageable.getOffset()
One to many queries starting at Pageable.getOffset() applying limiting. Additionally, COUNT(…) query to determine the total number of elements can be required.
Often times, COUNT(…) queries are required that are costly.
You can define simple sorting expressions by using property names.
You can concatenate expressions to collect multiple criteria into one expression.
Example 15. 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 16. Defining sort expressions by using the type-safe API
TypedSort<Person> person = Sort.sort(Person.class);
Sort sort = person.by(Person::getFirstname).ascending()
  .and(person.by(Person::getLastname).descending());
If your store implementation supports Querydsl, you can also use the generated metamodel types to define sort expressions:
Example 17. Defining sort expressions by using the Querydsl API
QSort sort = QSort.by(QPerson.firstname.asc())
  .and(QSort.by(QPerson.lastname.desc()));
8.4.5. 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 18. Limiting the result size of a query with Top and First
User findFirstByOrderByLastnameAsc();
User findTopByOrderByAgeDesc();
Page<User> queryFirst10ByLastname(String lastname, Pageable pageable);
Slice<User> findTop3ByLastname(String lastname, Pageable pageable);
List<User> findFirst10ByLastname(String lastname, Sort sort);
List<User> 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.
8.4.6. 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.
Refer to the appendix explaining all possible query method 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 19. Using Streamable to combine query method results
interface PersonRepository extends Repository<Person, Long> {
  Streamable<Person> findByFirstnameContaining(String firstname);
  Streamable<Person> findByLastnameContaining(String lastname);
Streamable<Person> 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:
@RequiredArgsConstructor(staticName = "of")
class Products implements Streamable<Product> {         (2)
  private final Streamable<Product> streamable;
  public MonetaryAmount getTotal() {                    (3)
    return streamable.stream()
      .map(Priced::getPrice)
      .reduce(Money.of(0), MonetaryAmount::add);
  @Override
  public Iterator<Product> iterator() {                 (4)
    return streamable.iterator();
interface ProductRepository implements Repository<Product, Long> {
  Products findAllByDescriptionContaining(String text); (5)
A wrapper type for a Streamable<Product> that can be constructed by using Products.of(…) (factory method created with the Lombok annotation).
A standard constructor taking the Streamable<Product> will do as well.
The wrapper type exposes an additional API, calculating new values on the Streamable<Product>.
Implement the Streamable interface and delegate to the actual result.
That wrapper type Products can be used directly as a query method return type.
You do not need to return Streamable<Product> and manually wrap it after the query in the repository client.
Support for Vavr Collections

Vavr 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:
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.
8.4.7. Streaming Query Results

You can process the results of query methods incrementally by using a Java 8 Stream<T> 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 20. Stream the result of a query with Java 8 Stream<T>
@Query("select u from User u")
Stream<User> findAllByCustomQueryAndStream();
Stream<User> readAllByFirstnameNotNull();
@Query("select u from User u")
Stream<User> 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:
try (Stream<User> stream = repository.findAllByCustomQueryAndStream()) {
  stream.forEach(…);
8.4.8. 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:




    

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” for details.
Nullability Annotations

You can express nullability constraints for repository methods by using Spring Framework’s nullability annotations.
They provide a tooling-friendly approach and opt-in null checks during runtime, as follows:
@NonNullApi: 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: Used on a parameter or return value that must not be null (not needed on a parameter and return value where @NonNullApi applies).
@Nullable: Used on a parameter or return value that can be null.
Spring annotations are meta-annotated with JSR 305 annotations (a dormant but widely used JSR).
JSR 305 meta-annotations let tooling vendors (such as IDEA, Eclipse, and Kotlin) 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, Long> {
  User getByEmailAddress(EmailAddress emailAddress);                    (2)
  @Nullable
  User findByEmailAddress(@Nullable EmailAddress emailAdress);          (3)
  Optional<User> findOptionalByEmailAddress(EmailAddress emailAddress); (4)
The repository resides in a package (or sub-package) for which we have defined non-null behavior.
Throws an EmptyResultDataAccessException when the query does not produce a result.
Throws an IllegalArgumentException when the emailAddress handed to the method is null.
Returns null when the query does not produce a result.
Also accepts null as the value for emailAddress.
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 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<User, String> {
  fun findByUsername(username: String): User     (1)
  fun findByFirstname(firstname: String?): User? (2)
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.
This method accepts null for the firstname parameter and returns null if the query does not produce a result.
8.4.9. Asynchronous Query Results

You can run repository queries asynchronously by using Spring’s asynchronous method running capability.
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:
8.5. Creating Repository Instances

This section covers how to create instances and bean definitions for the defined repository interfaces.
8.5.1. Java Configuration

Use the store-specific @EnableJpaRepositories annotation on a Java configuration class to define a configuration for repository activation.
For an introduction to Java-based configuration of the Spring container, see JavaConfig in the Spring reference documentation.
A sample configuration to enable Spring Data repositories resembles the following:
Example 25. Sample annotation-based repository configuration
@Configuration
@EnableJpaRepositories("com.acme.repositories")
class ApplicationConfiguration {
  @Bean
  EntityManagerFactory entityManagerFactory() {
8.5.2. 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 filter elements inside the repository declaration.
The semantics are exactly equivalent to the elements in Spring’s component filters.
For details, see the Spring reference documentation for these elements.
For example, to exclude certain interfaces from instantiation as repository beans, you could use the following configuration:
Example 26. Using filters
@Configuration
@EnableJpaRepositories(basePackages = "com.acme.repositories",
    includeFilters = { @Filter(type = FilterType.REGEX, pattern = ".*SomeRepository") },
    excludeFilters = { @Filter(type = FilterType.REGEX, pattern = ".*SomeOtherRepository") })
class ApplicationConfiguration {
  @Bean
  EntityManagerFactory entityManagerFactory() {
8.5.3. 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 27. Standalone usage of the repository factory
RepositoryFactorySupport factory = … // Instantiate factory here
UserRepository repository = factory.getRepository(UserRepository.class);
8.6. 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.
8.6.1. 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 28. Interface for custom repository functionality
interface CustomizedUserRepository {
  void someCustomMethod(User user);
class CustomizedUserRepositoryImpl implements CustomizedUserRepository {
  public void someCustomMethod(User user) {
    // Your custom implementation
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 30. Changes to your repository interface
interface UserRepository extends CrudRepository<User, Long>, 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), 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 31. 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 32. Changes to your repository interface
interface UserRepository extends CrudRepository<User, Long>, 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 33. Fragments overriding save(…)
interface CustomizedSave<T> {
  <S extends T> S save(S entity);
class CustomizedSaveImpl<T> implements CustomizedSave<T> {
  public <S extends T> S save(S entity) {
    // Your custom implementation
interface PersonRepository extends CrudRepository<Person, Long>, CustomizedSave<Person> {
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 a postfix defaulting 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 35. Configuration example
@EnableJpaRepositories(repositoryImplementationPostfix = "MyPostfix")
class Configuration { … }
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 36. Resolution of ambiguous implementations
package com.acme.impl.one;
class CustomizedUserRepositoryImpl implements CustomizedUserRepository {
  // Your custom implementation
@Component("specialCustomImpl")
class CustomizedUserRepositoryImpl implements CustomizedUserRepository {
  // Your custom implementation
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.
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 37. Manual wiring of custom implementations
class MyClass {
  MyClass(@Qualifier("userRepositoryImpl") UserRepository userRepository) {
8.6.2. Customize the Base Repository

The approach described in the preceding section 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 38. Custom repository base class
class MyRepositoryImpl<T, ID>
  extends SimpleJpaRepository<T, ID> {
  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 extends T> 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 configuration, you can do so by using the repositoryBaseClass, as shown in the following example:
Example 39. Configuring a custom repository base class
@Configuration
@EnableJpaRepositories(repositoryBaseClass = MyRepositoryImpl.class)
class ApplicationConfiguration { … }
8.7. 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 40. Exposing domain events from an aggregate root
class AnAggregateRoot {
    @DomainEvents (1)
    Collection<Object> domainEvents() {
        // … return events you want to get published here
    @AfterDomainEventPublication (2)
    void callbackMethod() {
       // … potentially clean up domain events list
The method that uses @DomainEvents can return either a single event instance or a collection of events.
It must not take any arguments.
After all events have been published, we have a method annotated with @AfterDomainEventPublication.
You can use it to potentially clean the list of events to be published (among other uses).
8.8. Spring Data Extensions

This section documents a set of Spring Data extensions that enable Spring Data usage in a variety of contexts.
Currently, most of the integration is targeted towards Spring MVC.
8.8.1. Querydsl Extension

Querydsl is a framework that enables the construction of statically typed SQL-like queries through its fluent API.
Several Spring Data modules offer integration with Querydsl through QuerydslPredicateExecutor, as the following example shows:
Example 41. QuerydslPredicateExecutor interface
public interface QuerydslPredicateExecutor<T> {
  Optional<T> findById(Predicate predicate);  (1)
  Iterable<T> findAll(Predicate predicate);   (2)
  long count(Predicate predicate);            (3)
  boolean exists(Predicate predicate);        (4)
  // … more functionality omitted.
To use the Querydsl support, extend QuerydslPredicateExecutor on your repository interface, as the following example shows:
Example 42. Querydsl integration on repositories
interface UserRepository extends CrudRepository<User, Long>, QuerydslPredicateExecutor<User> {
Predicate predicate = user.firstname.equalsIgnoreCase("dave")
	.and(user.lastname.startsWithIgnoreCase("mathews"));
userRepository.findAll(predicate);
8.8.2. Web support

Spring Data modules that support the repository programming model ship with a variety of web support.
The web related components require Spring MVC JARs to be on the classpath.
Some of them even provide integration with Spring HATEOAS.
In general, the integration support is enabled by using the @EnableSpringDataWebSupport annotation in your JavaConfig configuration class, as the following example shows:
Example 43. Enabling Spring Data web support
@Configuration
@EnableWebMvc
@EnableSpringDataWebSupport
class WebConfiguration {}
<bean class="org.springframework.data.web.config.SpringDataWebConfiguration" />
<!-- If you use Spring HATEOAS, register this one *instead* of the former -->
<bean class="org.springframework.data.web.config.HateoasAwareSpringDataWebConfiguration" />
The @EnableSpringDataWebSupport annotation registers a few components.
We discuss those later in this section.
It also detects Spring HATEOAS on the classpath and registers integration components (if present) for it as well.
Basic Web Support

Enabling Spring Data web support in XML
The configuration shown in the previous section registers a few basic components:
A Using the DomainClassConverter Class to let Spring MVC resolve instances of repository-managed domain classes from request parameters or path variables.
HandlerMethodArgumentResolver implementations to let Spring MVC resolve Pageable and Sort instances from request parameters.
Jackson Modules to de-/serialize types like Point and Distance, or store specific ones, depending on the Spring Data Module used.
Using the DomainClassConverter Class

The DomainClassConverter class lets you use domain types in your Spring MVC controller method signatures directly so that you need not manually lookup the instances through the repository, as the following example shows:
Example 44. A Spring MVC controller using domain types in method signatures
@Controller
@RequestMapping("/users")
class UserController {
  @RequestMapping("/{id}")
  String showUserForm(@PathVariable("id") User user, Model model) {
    model.addAttribute("user", user);
    return "userForm";
HandlerMethodArgumentResolvers for Pageable and Sort

The configuration snippet shown in the previous section also registers a PageableHandlerMethodArgumentResolver as well as an instance of SortHandlerMethodArgumentResolver.
The registration enables Pageable and Sort as valid controller method arguments, as the following example shows:
Example 45. Using Pageable as a controller method argument
@Controller
@RequestMapping("/users")
class UserController {
  private final UserRepository repository;
  UserController(UserRepository repository) {
    this.repository = repository;
  @RequestMapping
  String showUsers(Model model, Pageable pageable) {
    model.addAttribute("users", repository.findAll(pageable));
    return "users";
The preceding method signature causes Spring MVC try to derive a Pageable instance from the request parameters by using the following default configuration:
Table 2. Request parameters evaluated for Pageable instances
Properties that should be sorted by in the format property,property(,ASC|DESC)(,IgnoreCase). The default sort direction is case-sensitive ascending. Use multiple sort parameters if you want to switch direction or case sensitivity — for example, ?sort=firstname&sort=lastname,asc&sort=city,ignorecase.
To customize this behavior, register a bean that implements the PageableHandlerMethodArgumentResolverCustomizer interface or the SortHandlerMethodArgumentResolverCustomizer interface, respectively.
Its customize() method gets called, letting you change settings, as the following example shows:
@Bean SortHandlerMethodArgumentResolverCustomizer sortCustomizer() {
    return s -> s.setPropertyDelimiter("<-->");
If setting the properties of an existing MethodArgumentResolver is not sufficient for your purpose, extend either SpringDataWebConfiguration or the HATEOAS-enabled equivalent, override the pageableResolver() or sortResolver() methods, and import your customized configuration file instead of using the @Enable annotation.
If you need multiple Pageable or Sort instances to be resolved from the request (for multiple tables, for example), you can use Spring’s @Qualifier annotation to distinguish one from another.
The request parameters then have to be prefixed with ${qualifier}_.
The following example shows the resulting method signature:
Hypermedia Support for Page and Slice

Spring HATEOAS ships with a representation model class (PagedModel/SlicedModel) that allows enriching the content of a Page or Slice instance with the necessary Page/Slice metadata as well as links to let the clients easily navigate the pages.
The conversion of a Page to a PagedModel is done by an implementation of the Spring HATEOAS RepresentationModelAssembler interface, called the PagedResourcesAssembler.
Similarly Slice instances can be converted to a SlicedModel using a SlicedResourcesAssembler.
The following example shows how to use a PagedResourcesAssembler as a controller method argument, as the SlicedResourcesAssembler works exactly the same:
Example 46. Using a PagedResourcesAssembler as controller method argument
@Controller
class PersonController {
  private final PersonRepository repository;
  // Constructor omitted
  @GetMapping("/people")
  HttpEntity<PagedModel<Person>> people(Pageable pageable,
    PagedResourcesAssembler assembler) {
    Page<Person> people = repository.findAll(pageable);
    return ResponseEntity.ok(assembler.toModel(people));
Enabling the configuration, as shown in the preceding example, lets the PagedResourcesAssembler be used as a controller method argument.
Calling toModel(…) on it has the following effects:
The PagedModel object gets a PageMetadata instance attached, and it is populated with information from the Page and the underlying Pageable.
The PagedModel may get prev and next links attached, depending on the page’s state.
The links point to the URI to which the method maps.
The pagination parameters added to the method match the setup of the PageableHandlerMethodArgumentResolver to make sure the links can be resolved later.
{ "links" : [
    { "rel" : "next", "href" : "http://localhost:8080/persons?page=1&size=20" }
  "content" : [
     … // 20 Person instances rendered here
  "pageMetadata" : {
    "size" : 20,
    "totalElements" : 30,
    "totalPages" : 2,
    "number" : 0
The JSON envelope format shown here doesn’t follow any formally specified structure and it’s not guaranteed stable and we might change it at any time.
It’s highly recommended to enable the rendering as a hypermedia-enabled, official media type, supported by Spring HATEOAS, like HAL.
Those can be activated by using its @EnableHypermediaSupport annotation.
Find more information in the Spring HATEOAS reference documentation.
The assembler produced the correct URI and also picked up the default configuration to resolve the parameters into a Pageable for an upcoming request.
This means that, if you change that configuration, the links automatically adhere to the change.
By default, the assembler points to the controller method it was invoked in, but you can customize that by passing a custom Link to be used as base to build the pagination links, which overloads the PagedResourcesAssembler.toModel(…) method.




    

Spring Data Jackson Modules

The core module, and some of the store specific ones, ship with a set of Jackson Modules for types, like org.springframework.data.geo.Distance and org.springframework.data.geo.Point, used by the Spring Data domain.

Those Modules are imported once web support is enabled and com.fasterxml.jackson.databind.ObjectMapper is available.
During initialization SpringDataJacksonModules, like the SpringDataJacksonConfiguration, get picked up by the infrastructure, so that the declared com.fasterxml.jackson.databind.Modules are made available to the Jackson ObjectMapper.
Data binding mixins for the following domain types are registered by the common infrastructure.
org.springframework.data.geo.Distance
org.springframework.data.geo.Point
org.springframework.data.geo.Box
org.springframework.data.geo.Circle
org.springframework.data.geo.Polygon
Web Databinding Support

You can use Spring Data projections (described in Projections) to bind incoming request payloads by using either JSONPath expressions (requires Jayway JsonPath) or XPath expressions (requires XmlBeam), as the following example shows:
Example 47. HTTP payload binding using JSONPath or XPath expressions
@ProjectedPayload
public interface UserPayload {
  @XBRead("//firstname")
  @JsonPath("$..firstname")
  String getFirstname();
  @XBRead("/lastname")
  @JsonPath({ "$.lastname", "$.user.lastname" })
  String getLastname();
You can use the type shown in the preceding example as a Spring MVC handler method argument or by using ParameterizedTypeReference on one of methods of the RestTemplate.
The preceding method declarations would try to find firstname anywhere in the given document.
The lastname XML lookup is performed on the top-level of the incoming document.
The JSON variant of that tries a top-level lastname first but also tries lastname nested in a user sub-document if the former does not return a value.
That way, changes in the structure of the source document can be mitigated easily without having clients calling the exposed methods (usually a drawback of class-based payload binding).
Nested projections are supported as described in Projections.
If the method returns a complex, non-interface type, a Jackson ObjectMapper is used to map the final value.
For Spring MVC, the necessary converters are registered automatically as soon as @EnableSpringDataWebSupport is active and the required dependencies are available on the classpath.
For usage with RestTemplate, register a ProjectingJackson2HttpMessageConverter (JSON) or XmlBeamHttpMessageConverter manually.
For more information, see the web projection example in the canonical Spring Data Examples repository.
Querydsl Web Support

For those stores that have QueryDSL integration, you can derive queries from the attributes contained in a Request query string.
Consider the following query string:
  @Autowired UserRepository repository;
  @RequestMapping(value = "/", method = RequestMethod.GET)
  String index(Model model, @QuerydslPredicate(root = User.class) Predicate predicate,    (1)
          Pageable pageable, @RequestParam MultiValueMap<String, String> parameters) {
    model.addAttribute("users", repository.findAll(predicate, pageable));
    return "index";
interface UserRepository extends CrudRepository<User, String>,
                                 QuerydslPredicateExecutor<User>,                (1)
                                 QuerydslBinderCustomizer<QUser> {               (2)
  @Override
  default void customize(QuerydslBindings bindings, QUser user) {
    bindings.bind(user.username).first((path, value) -> path.contains(value))    (3)
    bindings.bind(String.class)
      .first((StringPath path, String value) -> path.containsIgnoreCase(value)); (4)
    bindings.excluding(user.password);                                           (5)
QuerydslBinderCustomizer defined on the repository interface is automatically picked up and shortcuts @QuerydslPredicate(bindings=…).
Define the binding for the username property to be a simple contains binding.
Define the default binding for String properties to be a case-insensitive contains match.
Exclude the password property from Predicate resolution.
This chapter points out the specialties for repository support for JDBC.This builds on the core repository support explained in Working with Spring Data Repositories.
You should have a sound understanding of the basic concepts explained there.
9.1. Why Spring Data JDBC?

The main persistence API for relational databases in the Java world is certainly JPA, which has its own Spring Data module.
Why is there another one?
JPA does a lot of things in order to help the developer.
Among other things, it tracks changes to entities.
It does lazy loading for you.
It lets you map a wide array of object constructs to an equally wide array of database designs.
This is great and makes a lot of things really easy.
Just take a look at a basic JPA tutorial.
But it often gets really confusing as to why JPA does a certain thing.
Also, things that are really simple conceptually get rather difficult with JPA.
Spring Data JDBC aims to be much simpler conceptually, by embracing the following design decisions:
If you load an entity, SQL statements get run.
Once this is done, you have a completely loaded entity.
No lazy loading or caching is done.
If you save an entity, it gets saved.
If you do not, it does not.
There is no dirty tracking and no session.
There is a simple model of how to map entities to tables.
It probably only works for rather simple cases.
If you do not like that, you should code your own strategy.
Spring Data JDBC offers only very limited support for customizing the strategy with annotations.
9.2. Domain Driven Design and Relational Databases.

All Spring Data modules are inspired by the concepts of “repository”, “aggregate”, and “aggregate root” from Domain Driven Design.
These are possibly even more important for Spring Data JDBC, because they are, to some extent, contrary to normal practice when working with relational databases.
An aggregate is a group of entities that is guaranteed to be consistent between atomic changes to it.
A classic example is an Order with OrderItems.
A property on Order (for example, numberOfItems is consistent with the actual number of OrderItems) remains consistent as changes are made.
References across aggregates are not guaranteed to be consistent at all times.
They are guaranteed to become consistent eventually.
Each aggregate has exactly one aggregate root, which is one of the entities of the aggregate.
The aggregate gets manipulated only through methods on that aggregate root.
These are the atomic changes mentioned earlier.
A repository is an abstraction over a persistent store that looks like a collection of all the aggregates of a certain type.
For Spring Data in general, this means you want to have one Repository per aggregate root.
In addition, for Spring Data JDBC this means that all entities reachable from an aggregate root are considered to be part of that aggregate root.
Spring Data JDBC assumes that only the aggregate has a foreign key to a table storing non-root entities of the aggregate and no other entity points toward non-root entities.
9.3. Getting Started

An easy way to bootstrap setting up a working environment is to create a Spring-based project in Spring Tools or from Spring Initializr.
First, you need to set up a running database server. Refer to your vendor documentation on how to configure your database for JDBC access.
To create a Spring project in STS:
Go to File → New → Spring Template Project → Simple Spring Utility Project, and press Yes when prompted. Then enter a project and a package name, such as org.spring.jdbc.example.
Add the following to the pom.xml files dependencies element:
<dependencies>
  <!-- other dependency elements omitted -->
  <dependency>
    <groupId>org.springframework.data</groupId>
    <artifactId>spring-data-jdbc</artifactId>
    <version>3.1.2</version>
  </dependency>
</dependencies>
Add the following location of the Spring Milestone repository for Maven to your pom.xml such that it is at the same level of your <dependencies/> element:
<repositories>
  <repository>
    <id>spring-milestone</id>
    <name>Spring Maven MILESTONE Repository</name>
    <url>https://repo.spring.io/milestone</url>
  </repository>
</repositories>
9.5. Annotation-based Configuration

The Spring Data JDBC repositories support can be activated by an annotation through Java configuration, as the following example shows:
Example 48. Spring Data JDBC repositories using Java configuration
@Configuration
@EnableJdbcRepositories                                                                (1)
class ApplicationConfig extends AbstractJdbcConfiguration {                            (2)
    @Bean
    DataSource dataSource() {                                                         (3)
        EmbeddedDatabaseBuilder builder = new EmbeddedDatabaseBuilder();
        return builder.setType(EmbeddedDatabaseType.HSQL).build();
    @Bean
    NamedParameterJdbcOperations namedParameterJdbcOperations(DataSource dataSource) { (4)
        return new NamedParameterJdbcTemplate(dataSource);
    @Bean
    TransactionManager transactionManager(DataSource dataSource) {                     (5)
        return new DataSourceTransactionManager(dataSource);
Creates a DataSource connecting to a database.
This is required by the following two bean methods.
Creates the NamedParameterJdbcOperations used by Spring Data JDBC to access the database.
Spring Data JDBC utilizes the transaction management provided by Spring JDBC.
The configuration class in the preceding example sets up an embedded HSQL database by using the EmbeddedDatabaseBuilder API of spring-jdbc.
The DataSource is then used to set up NamedParameterJdbcOperations and a TransactionManager.
We finally activate Spring Data JDBC repositories by using the @EnableJdbcRepositories.
If no base package is configured, it uses the package in which the configuration class resides.
Extending AbstractJdbcConfiguration ensures various beans get registered.
Overwriting its methods can be used to customize the setup (see below).
This configuration can be further simplified by using Spring Boot.
With Spring Boot a DataSource is sufficient once the starter spring-boot-starter-data-jdbc is included in the dependencies.
Everything else is done by Spring Boot.
There are a couple of things one might want to customize in this setup.
9.5.1. Dialects

Spring Data JDBC uses implementations of the interface Dialect to encapsulate behavior that is specific to a database or its JDBC driver.
By default, the AbstractJdbcConfiguration tries to determine the database in use and register the correct Dialect.
This behavior can be changed by overwriting jdbcDialect(NamedParameterJdbcOperations).
If you use a database for which no dialect is available, then your application won’t startup. In that case, you’ll have to ask your vendor to provide a Dialect implementation. Alternatively, you can:
Register the provider by creating a spring.factories  resource under META-INF and perform the registration by adding a line

org.springframework.data.jdbc.repository.config.DialectResolver$JdbcDialectProvider=<fully qualified name of your JdbcDialectProvider>
9.6. Persisting Entities

Saving an aggregate can be performed with the CrudRepository.save(…) method.
If the aggregate is new, this results in an insert for the aggregate root, followed by insert statements for all directly or indirectly referenced entities.
If the aggregate root is not new, all referenced entities get deleted, the aggregate root gets updated, and all referenced entities get inserted again.
Note that whether an instance is new is part of the instance’s state.
This approach has some obvious downsides.
If only few of the referenced entities have been actually changed, the deletion and insertion is wasteful.
While this process could and probably will be improved, there are certain limitations to what Spring Data JDBC can offer.
It does not know the previous state of an aggregate.
So any update process always has to take whatever it finds in the database and make sure it converts it to whatever is the state of the entity passed to the save method.
9.6.1. 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:
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 single static factory method annotated with @PersistenceCreator then it is used.
If there is a single constructor, it is used.
If there are multiple constructors and exactly one is annotated with @PersistenceCreator, it is used.
If the type is a Java Record the canonical constructor is used.
If there’s a no-argument constructor, it is used.
Other constructors will be ignored.
The value resolution assumes constructor/factory method 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) { … }
class PersonObjectInstantiator implements ObjectInstantiator {
  Object newInstance(Object... args) {
    return new Person((String) args[0], (String) args[1]);
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 with… method (see below), we use the with… method to create a new entity instance with the new property value.
If property access (i.e. access through getters and setters) is defined, we’re invoking the setter method.
If the property is mutable we set the field directly.
If the property is immutable we’re using the constructor to be used by persistence operations (see Object creation) to create a copy of the instance.
By default, we set the field value directly.
  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;
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)
PropertyAccessor’s hold a mutable instance of the underlying object. This is, to enable mutations of otherwise immutable properties.
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.
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.
Using property-access allows direct method invocations without using MethodHandles.
  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;
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.
The firstname and lastname properties are ordinary immutable properties potentially exposed through getters.
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.
The comment property is mutable and is populated by setting its field directly.
The remarks property is mutable and is populated by invoking the setter method.
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.
If you want Spring Data to use the factory method for object instantiation, annotate it with @PersistenceCreator.
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 @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 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.
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:
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:
Which property should be persisted (default to all declared properties)?
You can exclude properties by annotating these with @Transient.
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.
Using @AccessType(PROPERTY) cannot be used as the super-property cannot be generally set without making any further assumptions of the setter implementation.
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.
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 single static factory method annotated with @PersistenceCreator then it is used.
If there is a single constructor, it is used.
If there are multiple constructors and exactly one is annotated with @PersistenceCreator, it is used.
If the type is a Java Record the canonical constructor is used.
If there’s a no-argument constructor, it is used.
Other constructors will be ignored.
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
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:
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:
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:
Which property should be persisted (default to all declared properties)?
You can exclude properties by annotating these with @Transient.
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.
Using @AccessType(PROPERTY) cannot be used as the super-property cannot be set.
Arrays and Collections of the types mentioned above can be mapped to columns of array type if your database supports that.
Anything your database driver accepts.
References to other entities.
They are considered a one-to-one relationship, or an embedded type.
It is optional for one-to-one relationship entities to have an id attribute.
The table of the referenced entity is expected to have an additional column with a name based on the referencing entity see Back References.
Embedded entities do not need an id.
If one is present it gets ignored.
Set<some entity> is considered a one-to-many relationship.
The table of the referenced entity is expected to have an additional column with a name based on the referencing entity see Back References.
Map<simple type, some entity> is considered a qualified one-to-many relationship.
The table of the referenced entity is expected to have two additional columns: One named based on the referencing entity for the foreign key (see Back References) and one with the same name and an additional _key suffix for the map key.
You can change this behavior by implementing NamingStrategy.getReverseColumnName(PersistentPropertyPathExtension path) and NamingStrategy.getKeyColumn(RelationalPersistentProperty property), respectively.
Alternatively you may annotate the attribute with @MappedCollection(idColumn="your_column_name", keyColumn="your_key_column_name")
List<some entity> is mapped as a  Map<Integer, some entity>.
The handling of referenced entities is limited.
This is based on the idea of aggregate roots as described above.
If you reference another entity, that entity is, by definition, part of your aggregate.
So, if you remove the reference, the previously referenced entity gets deleted.
This also means references are 1-1 or 1-n, but not n-1 or n-m.
If you have n-1 or n-m references, you are, by definition, dealing with two separate aggregates.
References between those may be encoded as simple id values, which map properly with Spring Data JDBC.
A better way to encode these, is to make them instances of AggregateReference.
An AggregateReference is a wrapper around an id value which marks that value as a reference to a different aggregate.
Also, the type of that aggregate is encoded in a type parameter.




    

Back References

All references in an aggregate result in a foreign key relationship in the opposite direction in the database.
By default, the name of the foreign key column is the table name of the referencing entity.
Alternatively you may choose to have them named by the entity name of the referencing entity ignoreing @Table annotations.
You activate this behaviour by calling setForeignKeyNaming(ForeignKeyNaming.IGNORE_RENAMING) on the RelationalMappingContext.
For List and Map references an additional column is required for holding the list index or map key. It is based on the foreign key column with an additional _KEY suffix.
If you want a completely different way of naming these back references you may implement NamingStrategy.getReverseColumnName(PersistentPropertyPathExtension path) in a way that fits your needs.
Example 51. Declaring and setting an AggregateReference
class Person {
	@Id long id;
	AggregateReference<Person, Long> bestFriend;
// ...
Person p1, p2 = // some initialization
p1.bestFriend = AggregateReference.to(p2.id);
9.6.3. NamingStrategy

When you use the standard implementations of CrudRepository that Spring Data JDBC provides, they expect a certain table structure.
You can tweak that by providing a NamingStrategy in your application context.
9.6.4. Custom table names

When the NamingStrategy does not matching on your database table names, you can customize the names with the @Table annotation.
The element value of this annotation provides the custom table name.
The following example maps the MyEntity class to the CUSTOM_TABLE_NAME table in the database:
9.6.5. Custom column names

When the NamingStrategy does not matching on your database column names, you can customize the names with the @Column annotation.
The element value of this annotation provides the custom column name.
The following example maps the name property of the MyEntity class to the CUSTOM_COLUMN_NAME column in the database:
The @MappedCollection
annotation can be used on a reference type (one-to-one relationship) or on Sets, Lists, and Maps (one-to-many relationship).
idColumn element of the annotation provides a custom name for the foreign key column referencing the id column in the other table.
In the following example the corresponding table for the MySubEntity class has a NAME column, and the CUSTOM_MY_ENTITY_ID_COLUMN_NAME column of the MyEntity id for relationship reasons:
    @MappedCollection(idColumn = "CUSTOM_MY_ENTITY_ID_COLUMN_NAME")
    Set<MySubEntity> subEntities;
class MySubEntity {
    String name;
When using List and Map you must have an additional column for the position of a dataset in the List or the key value of the entity in the Map.
This additional column name may be customized with the keyColumn Element of the @MappedCollection annotation:
    Integer id;
    @MappedCollection(idColumn = "CUSTOM_COLUMN_NAME", keyColumn = "CUSTOM_KEY_COLUMN_NAME")
    List<MySubEntity> name;
class MySubEntity {
    String name;
9.6.6. Embedded entities

Embedded entities are used to have value objects in your java data model, even if there is only one table in your database.
In the following example you see, that MyEntity is mapped with the @Embedded annotation.
The consequence of this is, that in the database a table my_entity with the two columns id and name (from the EmbeddedEntity class) is expected.
However, if the name column is actually null within the result set, the entire property embeddedEntity will be set to null according to the onEmpty of @Embedded, which nulls objects when all nested properties are null.

Opposite to this behavior USE_EMPTY tries to create a new instance using either a default constructor or one that accepts nullable parameter values from the result set.
Example 52. Sample Code of embedding objects
class MyEntity {
    Integer id;
    @Embedded(onEmpty = USE_NULL) (1)
    EmbeddedEntity embeddedEntity;
class EmbeddedEntity {
    String name;
If you need a value object multiple times in an entity, this can be achieved with the optional prefix element of the @Embedded annotation.
This element represents a prefix and is prepend for each column name in the embedded object.
Embedded entities containing a Collection or a Map will always be considered non empty since they will at least contain the empty collection or map.
Such an entity will therefore never be null even when using @Embedded(onEmpty = USE_NULL).
9.6.7. Entity State Detection Strategies

The following table describes the strategies that Spring Data offers for detecting whether an entity is new:
Table 3. Options for detection whether an entity is new in Spring Data
@Id-Property inspection (the default)
By default, Spring Data inspects the identifier property of the given entity.
If the identifier property is null or 0 in case of primitive types, then the entity is assumed to be new.
Otherwise, it is assumed to not be new.
@Version-Property inspection
If a property annotated with @Version is present and null, or in case of a version property of primitive type 0 the entity is considered new.
If the version property is present but has a different value, the entity is considered to not be new.
If no version property is present Spring Data falls back to inspection of the identifier property.
Implementing Persistable
If an entity implements Persistable, Spring Data delegates the new detection to the isNew(…) method of the entity.
See the Javadoc for details.
Note: Properties of Persistable will get detected and persisted if you use AccessType.PROPERTY.
To avoid that, use @Transient.
Providing a custom EntityInformation implementation
You can customize the EntityInformation abstraction used in the repository base implementation by creating a subclass of the module specific repository factory and overriding the getEntityInformation(…) method.
You then have to register the custom implementation of module specific repository factory as a Spring bean.
Note that this should rarely be necessary.
Spring Data JDBC uses the ID to identify entities.
The ID of an entity must be annotated with Spring Data’s @Id annotation.
When your database has an auto-increment column for the ID column, the generated value gets set in the entity after inserting it into the database.
One important constraint is that, after saving an entity, the entity must not be new any more.
Note that whether an entity is new is part of the entity’s state.
With auto-increment columns, this happens automatically, because the ID gets set by Spring Data with the value from the ID column.
If you are not using auto-increment columns, you can use a BeforeConvertCallback to set the ID of the entity (covered later in this document).
9.6.9. Read Only Properties

Attributes annotated with @ReadOnlyProperty will not be written to the database by Spring Data JDBC, but they will be read when an entity gets loaded.
Spring Data JDBC will not automatically reload an entity after writing it.
Therefore, you have to reload it explicitly if you want to see data that was generated in the database for such columns.
If the annotated attribute is an entity or collection of entities, it is represented by one or more separate rows in separate tables.
Spring Data JDBC will not perform any insert, delete or update for these rows.
9.6.10. Insert Only Properties

Attributes annotated with @InsertOnlyProperty will only be written to the database by Spring Data JDBC during insert operations.
For updates these properties will be ignored.
@InsertOnlyProperty is only supported for the aggregate root.
9.6.11. Optimistic Locking

Spring Data JDBC supports optimistic locking by means of a numeric attribute that is annotated with
@Version on the aggregate root.
Whenever Spring Data JDBC saves an aggregate with such a version attribute two things happen:
The update statement for the aggregate root will contain a where clause checking that the version stored in the database is actually unchanged.
If this isn’t the case an OptimisticLockingFailureException will be thrown.
Also the version attribute gets increased both in the entity and in the database so a concurrent action will notice the change and throw an OptimisticLockingFailureException if applicable as described above.
This process also applies to inserting new aggregates, where a null or 0 version indicates a new instance and the increased instance afterwards marks the instance as not new anymore, making this work rather nicely with cases where the id is generated during object construction for example when UUIDs are used.
During deletes the version check also applies but no version is increased.
9.7. Query Methods

This section offers some specific information about the implementation and use of Spring Data JDBC.
Most of the data access operations you usually trigger on a repository result in a query being run against the databases.
Defining such a query is a matter of declaring a method on the repository interface, as the following example shows:
Example 53. PersonRepository with query methods
interface PersonRepository extends PagingAndSortingRepository<Person, String> {
  List<Person> findByFirstname(String firstname);                                   (1)
  List<Person> findByFirstnameOrderByLastname(String firstname, Pageable pageable); (2)
  Slice<Person> findByLastname(String lastname, Pageable pageable);                 (3)
  Page<Person> findByLastname(String lastname, Pageable pageable);                  (4)
  Person findByFirstnameAndLastname(String firstname, String lastname);             (5)
  Person findFirstByLastname(String lastname);                                      (6)
  @Query("SELECT * FROM person WHERE lastname = :lastname")
  List<Person> findByLastname(String lastname);                                     (7)
  @Query("SELECT * FROM person WHERE lastname = :lastname")
  Stream<Person> streamByLastname(String lastname);                                     (8)
  @Query("SELECT * FROM person WHERE username = :#{ principal?.username }")
  Person findActiveUser();															(6)
The method shows a query for all people with the given firstname.
The query is derived by parsing the method name for constraints that can be concatenated with And and Or.
Thus, the method name results in a query expression of SELECT … FROM person WHERE firstname = :firstname.
Use Pageable to pass offset and sorting parameters to the database.
Return a Slice<Person>. Selects LIMIT+1 rows to determine whether there’s more data to consume. ResultSetExtractor customization is not supported.
Run a paginated query returning Page<Person>. Selects only data within the given page bounds and potentially a count query to determine the total count. ResultSetExtractor customization is not supported.
Find a single entity for the given criteria.
It completes with IncorrectResultSizeDataAccessException on non-unique results.
In contrast to <3>, the first entity is always emitted even if the query yields more result documents.
The findByLastname method shows a query for all people with the given lastname.
The streamByLastname method returns a Stream, which makes values possible as soon as they are returned from the database.
You can use the Spring Expression Language to dynamically resolve parameters. In the sample, Spring Security is used to resolve the username of the current user.
Containing on String
findByFirstnameContaining(String name)
firstname LIKE '%' + name + '%'
NotContaining on String
findByFirstnameNotContaining(String name)
firstname NOT LIKE '%' + name + '%'
(No keyword)
findByFirstname(String name)
firstname = name
findByFirstnameNot(String name)
firstname != name
IsTrue, True
findByActiveIsTrue()
active IS TRUE
IsFalse,  False




    

findByActiveIsFalse()
active IS FALSE
9.7.1. Query Lookup Strategies

The JDBC module supports defining a query manually as a String in a @Query annotation or as named query in a property file.
Deriving a query from the name of the method is is currently limited to simple properties, that means properties present in the aggregate root directly.
Also, only select queries are supported by this approach.
9.7.2. Using @Query

The following example shows how to use @Query to declare a query method:
Example 54. Declare a query method by using @Query
interface UserRepository extends CrudRepository<User, Long> {
  @Query("select firstName, lastName from User u where u.emailAddress = :email")
  User findByEmailAddress(@Param("email") String email);
For converting the query result into entities the same RowMapper is used by default as for the queries Spring Data JDBC generates itself.
The query you provide must match the format the RowMapper expects.
Columns for all properties that are used in the constructor of an entity must be provided.
Columns for properties that get set via setter, wither or field access are optional.
Properties that don’t have a matching column in the result will not be set.
The query is used for populating the aggregate root, embedded entities and one-to-one relationships including arrays of primitive types which get stored and loaded as SQL-array-types.
Separate queries are generated for maps, lists, sets and arrays of entities.
Spring fully supports Java 8’s parameter name discovery based on the -parameters compiler flag.
By using this flag in your build as an alternative to debug information, you can omit the @Param annotation for named parameters.
9.7.3. Named Queries

If no query is given in an annotation as described in the previous section Spring Data JDBC will try to locate a named query.
There are two ways how the name of the query can be determined.
The default is to take the domain class of the query, i.e. the aggregate root of the repository, take its simple name and append the name of the method separated by a ..
Alternatively the @Query annotation has a name attribute which can be used to specify the name of a query to be looked up.
Named queries are expected to be provided in the property file META-INF/jdbc-named-queries.properties on the classpath.
The location of that file may be changed by setting a value to @EnableJdbcRepositories.namedQueriesLocation.
Streaming Results

When you specify Stream as the return type of a query method, Spring Data JDBC returns elements as soon as they become available.
When dealing with large amounts of data this is suitable for reducing latency and memory requirements.
The stream contains an open connection to the database.
To avoid memory leaks, that connection needs to be closed eventually, by closing the stream.
The recommended way to do that is a try-with-resource clause.
It also means that, once the connection to the database is closed, the stream cannot obtain further elements and likely throws an exception.
Custom RowMapper

You can configure which RowMapper to use, either by using the @Query(rowMapperClass = ….) or by registering a RowMapperMap bean and registering a RowMapper per method return type.
The following example shows how to register DefaultQueryMappingConfiguration:
@Bean
QueryMappingConfiguration rowMappers() {
  return new DefaultQueryMappingConfiguration()
    .register(Person.class, new PersonRowMapper())
    .register(Address.class, new AddressRowMapper());
The entity classes in the QueryMappingConfiguration are iterated until one is found that is a superclass or interface of the return type in question.
The RowMapper registered for that class is used.
Iterating happens in the order of registration, so make sure to register more general types after specific ones.
Modifying queries are executed directly against the database.
No events or callbacks get called.
Therefore also fields with auditing annotations do not get updated if they don’t get updated in the annotated query.
9.8.1. Introduction

This chapter provides an introduction to Query by Example and explains how to use it.
Query by Example (QBE) is a user-friendly querying technique with a simple interface.
It allows dynamic query creation and does not require you to write queries that contain field names.
In fact, Query by Example does not require you to write queries by using store-specific query languages at all.
9.8.2. Usage

The Query by Example API consists of four parts:
ExampleMatcher: The ExampleMatcher carries details on how to match particular fields.
It can be reused across multiple Examples.
Example: An Example consists of the probe and the ExampleMatcher.
It is used to create the query.
FetchableFluentQuery: A FetchableFluentQuery offers a fluent API, that allows further customization of a query derived from an Example.
Using the fluent API lets you to specify ordering projection and result processing for your query.
Frequent refactoring of the domain objects without worrying about breaking existing queries.
Working independently from the underlying data store API.
No support for nested or grouped property constraints, such as firstname = ?0 or (firstname = ?1 and lastname = ?2).
Only supports starts/contains/ends/regex matching for strings and exact matching for other property types.
Before getting started with Query by Example, you need to have a domain object.
To get started, create an interface for your repository, as shown in the following example:
Example 55. Sample Person object
public class Person {
  private String id;
  private String firstname;
  private String lastname;
  private Address address;
  // … getters and setters omitted
Examples can be built by either using the of factory method or by using ExampleMatcher. Example is immutable.
The following listing shows a simple Example:
Example 56. Simple Example
Person person = new Person();                         (1)
person.setFirstname("Dave");                          (2)
Example<Person> example = Example.of(person);         (3)
You can run the example queries by using repositories.
To do so, let your repository interface extend QueryByExampleExecutor<T>.
The following listing shows an excerpt from the QueryByExampleExecutor interface:
Example 57. The QueryByExampleExecutor
public interface QueryByExampleExecutor<T> {
  <S extends T> S findOne(Example<S> example);
  <S extends T> Iterable<S> findAll(Example<S> example);
  // … more functionality omitted.
Examples are not limited to default settings.
You can specify your own defaults for string matching, null handling, and property-specific settings by using the ExampleMatcher, as shown in the following example:
Example 58. Example matcher with customized matching
Person person = new Person();                          (1)
person.setFirstname("Dave");                           (2)
ExampleMatcher matcher = ExampleMatcher.matching()     (3)
  .withIgnorePaths("lastname")                         (4)
  .withIncludeNullValues()                             (5)
  .withStringMatcher(StringMatcher.ENDING);            (6)
Example<Person> example = Example.of(person, matcher); (7)
Create an ExampleMatcher to expect all values to match.
It is usable at this stage even without further configuration.
Construct a new ExampleMatcher to ignore the lastname property path.
Construct a new ExampleMatcher to ignore the lastname property path and to include null values.
Construct a new ExampleMatcher to ignore the lastname property path, to include null values, and to perform suffix string matching.
Create a new Example based on the domain object and the configured ExampleMatcher.
By default, the ExampleMatcher expects all values set on the probe to match.
If you want to get results matching any of the predicates defined implicitly, use ExampleMatcher.matchingAny().
You can specify behavior for individual properties (such as "firstname" and "lastname" or, for nested properties, "address.city").
You can tune it with matching options and case sensitivity, as shown in the following example:
Example 59. Configuring matcher options
ExampleMatcher matcher = ExampleMatcher.matching()
  .withMatcher("firstname", endsWith())
  .withMatcher("lastname", startsWith().ignoreCase());
Another way to configure matcher options is to use lambdas (introduced in Java 8).
This approach creates a callback that asks the implementor to modify the matcher.
You need not return the matcher, because configuration options are held within the matcher instance.
The following example shows a matcher that uses lambdas:
Example 60. Configuring matcher options with lambdas
ExampleMatcher matcher = ExampleMatcher.matching()
  .withMatcher("firstname", match -> match.endsWith())
  .withMatcher("firstname", match -> match.startsWith());
Queries created by Example use a merged view of the configuration.
Default matching settings can be set at the ExampleMatcher level, while individual settings can be applied to particular property paths.
Settings that are set on ExampleMatcher are inherited by property path settings unless they are defined explicitly.
Settings on a property patch have higher precedence than default settings.
The following table describes the scope of the various ExampleMatcher settings:
Table 5. Scope of ExampleMatcher settings
9.8.4. Fluent API

QueryByExampleExecutor offers one more method, which we did not mention so far: <S extends T, R> R findBy(Example<S> example, Function<FluentQuery.FetchableFluentQuery<S>, R> queryFunction).
As with other methods, it executes a query derived from an Example.
However, with the second argument, you can control aspects of that execution that you cannot dynamically control otherwise.
You do so by invoking the various methods of the FetchableFluentQuery in the second argument.
sortBy lets you specify an ordering for your result.
as lets you specify the type to which you want the result to be transformed.
project limits the queried attributes.
first, firstValue, one, oneValue, all, page, stream, count, and exists define what kind of result you get and how the query behaves when more than the expected number of results are available.
Example 61. Use the fluent API to get the last of potentially many results, ordered by lastname.
Optional<Person> match = repository.findBy(example,
    q -> q
        .sortBy(Sort.by("lastname").descending())
        .first()
9.8.5. Running an Example

In Spring Data JDBC, you can use Query by Example with Repositories, as shown in the following example:
Example 62. Query by Example using a Repository
public interface PersonRepository
        extends CrudRepository<Person, String>,
        QueryByExampleExecutor<Person> { … }
public class PersonService {
  @Autowired PersonRepository personRepository;
  public List<Person> findPeople(Person probe) {
    return personRepository.findAll(Example.of(probe));
The property specifier accepts property names (such as firstname and lastname). You can navigate by chaining properties together with dots (address.city). You can also tune it with matching options and case sensitivity.
The following table shows the various StringMatcher options that you can use and the result of using them on a field named firstname:
Table 6. StringMatcher options
9.9. Projections

Spring Data query methods usually return one or multiple instances of the aggregate root managed by the repository.
However, it might sometimes be desirable to create projections based on certain attributes of those types.
Spring Data allows modeling dedicated return types, to more selectively retrieve partial views of the managed aggregates.
Imagine a repository and aggregate root type such as the following example:
Example 63. A sample aggregate and repository
class Person {
  @Id UUID id;
  String firstname, lastname;
  Address address;
  static class Address {
    String zipCode, city, street;
interface PersonRepository extends Repository<Person, UUID> {
  Collection<Person> findByLastname(String lastname);
Now imagine that we want to retrieve the person’s name attributes only.
What means does Spring Data offer to achieve this? The rest of this chapter answers that question.
9.9.1. Interface-based Projections

The easiest way to limit the result of the queries to only the name attributes is by declaring an interface that exposes accessor methods for the properties to be read, as shown in the following example:
Example 64. A projection interface to retrieve a subset of attributes
interface NamesOnly {
  String getFirstname();
  String getLastname();
The important bit here is that the properties defined here exactly match properties in the aggregate root.
Doing so lets a query method be added as follows:




    

Example 65. A repository using an interface based projection with a query method
interface PersonRepository extends Repository<Person, UUID> {
  Collection<NamesOnly> findByLastname(String lastname);
Declaring a method in your Repository that overrides a base method (e.g. declared in  CrudRepository, a store-specific repository interface, or the Simple…Repository) results in a call to the base method regardless of the declared return type. Make sure to use a compatible return type as base methods cannot be used for projections. Some store modules support @Query annotations to turn an overridden base method into a query method that then can be used to return projections.
Projections can be used recursively. If you want to include some of the Address information as well, create a projection interface for that and return that interface from the declaration of getAddress(), as shown in the following example:
Example 66. A projection interface to retrieve a subset of attributes
interface PersonSummary {
  String getFirstname();
  String getLastname();
  AddressSummary getAddress();
  interface AddressSummary {
    String getCity();
On method invocation, the address property of the target instance is obtained and wrapped into a projecting proxy in turn.
Closed Projections

A projection interface whose accessor methods all match properties of the target aggregate is considered to be a closed projection. The following example (which we used earlier in this chapter, too) is a closed projection:
Example 67. A closed projection
interface NamesOnly {
  String getFirstname();
  String getLastname();
If you use a closed projection, Spring Data can optimize the query execution, because we know about all the attributes that are needed to back the projection proxy.
For more details on that, see the module-specific part of the reference documentation.
Open Projections

Accessor methods in projection interfaces can also be used to compute new values by using the @Value annotation, as shown in the following example:
Example 68. An Open Projection
interface NamesOnly {
  @Value("#{target.firstname + ' ' + target.lastname}")
  String getFullName();
The aggregate root backing the projection is available in the target variable.
A projection interface using @Value is an open projection.
Spring Data cannot apply query execution optimizations in this case, because the SpEL expression could use any attribute of the aggregate root.
The expressions used in @Value should not be too complex — you want to avoid programming in String variables.
For very simple expressions, one option might be to resort to default methods (introduced in Java 8), as shown in the following example:
Example 69. A projection interface using a default method for custom logic
interface NamesOnly {
  String getFirstname();
  String getLastname();
  default String getFullName() {
    return getFirstname().concat(" ").concat(getLastname());
This approach requires you to be able to implement logic purely based on the other accessor methods exposed on the projection interface.
A second, more flexible, option is to implement the custom logic in a Spring bean and then invoke that from the SpEL expression, as shown in the following example:
Example 70. Sample Person object
@Component
class MyBean {
  String getFullName(Person person) {
interface NamesOnly {
  @Value("#{@myBean.getFullName(target)}")
  String getFullName();
Notice how the SpEL expression refers to myBean and invokes the getFullName(…) method and forwards the projection target as a method parameter.
Methods backed by SpEL expression evaluation can also use method parameters, which can then be referred to from the expression.
The method parameters are available through an Object array named args. The following example shows how to get a method parameter from the args array:
Example 71. Sample Person object
interface NamesOnly {
  @Value("#{args[0] + ' ' + target.firstname + '!'}")
  String getSalutation(String prefix);
If the underlying projection value is not null, then values are returned using the present-representation of the wrapper type.
In case the backing value is null, then the getter method returns the empty representation of the used wrapper type.
9.9.2. Class-based Projections (DTOs)

Another way of defining projections is by using value type DTOs (Data Transfer Objects) that hold properties for the fields that are supposed to be retrieved.
These DTO types can be used in exactly the same way projection interfaces are used, except that no proxying happens and no nested projections can be applied.
If the store optimizes the query execution by limiting the fields to be loaded, the fields to be loaded are determined from the parameter names of the constructor that is exposed.
The following example shows a projecting DTO:
Example 73. A projecting DTO
record NamesOnly(String firstname, String lastname) {
Java Records are ideal to define DTO types since they adhere to value semantics:
All fields are private final and equals(…)/hashCode()/toString() methods are created automatically.
Alternatively, you can use any class that defines the properties you want to project.
9.9.3. Dynamic Projections

So far, we have used the projection type as the return type or element type of a collection.
However, you might want to select the type to be used at invocation time (which makes it dynamic).
To apply dynamic projections, use a query method such as the one shown in the following example:
Example 74. A repository using a dynamic projection parameter
interface PersonRepository extends Repository<Person, UUID> {
  <T> Collection<T> findByLastname(String lastname, Class<T> type);
This way, the method can be used to obtain the aggregates as is or with a projection applied, as shown in the following example:
Example 75. Using a repository with dynamic projections
void someMethod(PersonRepository people) {
  Collection<Person> aggregates =
    people.findByLastname("Matthews", Person.class);
  Collection<NamesOnly> aggregates =
    people.findByLastname("Matthews", NamesOnly.class);
Query parameters of type Class are inspected whether they qualify as dynamic projection parameter.
If the actual return type of the query equals the generic parameter type of the Class parameter, then the matching Class parameter is not available for usage within the query or SpEL expressions.
If you want to use a Class parameter as query argument then make sure to use a different generic parameter, for example Class<?>.
9.10. MyBatis Integration

The CRUD operations and query methods can be delegated to MyBatis.
This section describes how to configure Spring Data JDBC to integrate with MyBatis and which conventions to follow to hand over the running of the queries as well as the mapping to the library.
9.10.1. Configuration

The easiest way to properly plug MyBatis into Spring Data JDBC is by importing MyBatisJdbcConfiguration into you application configuration:
@Configuration
@EnableJdbcRepositories
@Import(MyBatisJdbcConfiguration.class)
class Application {
  @Bean
  SqlSessionFactoryBean sqlSessionFactoryBean() {
    // Configure MyBatis here
9.10.2. Usage conventions

For each operation in CrudRepository, Spring Data JDBC runs multiple statements.
If there is a SqlSessionFactory in the application context, Spring Data checks, for each step, whether the SessionFactory offers a statement.
If one is found, that statement (including its configured mapping to an entity) is used.
The name of the statement is constructed by concatenating the fully qualified name of the entity type with Mapper. and a String determining the kind of statement.
For example, if an instance of org.example.User is to be inserted, Spring Data JDBC looks for a statement named org.example.UserMapper.insert.
When the statement is run, an instance of [MyBatisContext] gets passed as an argument, which makes various arguments available to the statement.
The following table describes the available MyBatis statements:
insert
Inserts a single entity. This also applies for entities referenced by the aggregate root.
save, saveAll.
getInstance: the instance to be saved
getDomainType: The type of the entity to be saved.
get(<key>): ID of the referencing entity, where <key> is the name of the back reference column provided by the NamingStrategy.
update
Updates a single entity. This also applies for entities referenced by the aggregate root.
save, saveAll.
getInstance: The instance to be saved
getDomainType: The type of the entity to be saved.
delete
Deletes a single entity.
delete, deleteById.
getId: The ID of the instance to be deleted
getDomainType: The type of the entity to be deleted.
deleteAll-<propertyPath>
Deletes all entities referenced by any aggregate root of the type used as prefix with the given property path.
Note that the type used for prefixing the statement name is the name of the aggregate root, not the one of the entity to be deleted.
deleteAll.
getDomainType: The types of the entities to be deleted.
deleteAll
Deletes all aggregate roots of the type used as the prefix
deleteAll.
getDomainType: The type of the entities to be deleted.
delete-<propertyPath>
Deletes all entities referenced by an aggregate root with the given propertyPath
deleteById.
getId: The ID of the aggregate root for which referenced entities are to be deleted.
getDomainType: The type of the entities to be deleted.
findById
Selects an aggregate root by ID
findById.
getId: The ID of the entity to load.
getDomainType: The type of the entity to load.
findAll
Select all aggregate roots
findAll.
getDomainType: The type of the entity to load.
findAllById
Select a set of aggregate roots by ID values
findAllById.
getId: A list of ID values of the entities to load.
getDomainType: The type of the entity to load.
findAllByProperty-<propertyName>
Select a set of entities that is referenced by another entity. The type of the referencing entity is used for the prefix. The referenced entities type is used as the suffix. This method is deprecated. Use findAllByPath instead
All find* methods. If no query is defined for findAllByPath
getId: The ID of the entity referencing the entities to be loaded.
getDomainType: The type of the entity to load.
findAllByPath-<propertyPath>
Select a set of entities that is referenced by another entity via a property path.
All find* methods.
getIdentifier: The Identifier holding the id of the aggregate root plus the keys and list indexes of all path elements.
getDomainType: The type of the entity to load.
findAllSorted
Select all aggregate roots, sorted
findAll(Sort).
getSort: The sorting specification.
findAllPaged
Select a page of aggregate roots, optionally sorted
findAll(Page).
getPageable: The paging specification.
count
Count the number of aggregate root of the type used as prefix
count
getDomainType: The type of aggregate roots to count.
9.11. Lifecycle Events

Spring Data JDBC publishes lifecycle events to ApplicationListener objects, typically beans in the application context.
Events are notifications about a certain lifecycle phase.
In contrast to entity callbacks, events are intended for notification. Transactional listeners will receive events when the transaction completes.
Events and callbacks get only triggered for aggregate roots.
If you want to process non-root entities, you need to do that through a listener for the containing aggregate root.
Entity lifecycle events can be costly, and you may notice a change in the performance profile when loading large result sets.
You can disable lifecycle events on the Template API.




    

For example, the following listener gets invoked before an aggregate gets saved:
If you want to handle events only for a specific domain type you may derive your listener from AbstractRelationalEventListener and overwrite one or more of the onXXX methods, where XXX stands for an event type.
Callback methods will only get invoked for events related to the domain type and their subtypes, therefore you don’t require further casting.
	@Override
	protected void onAfterLoad(AfterLoadEvent<Person> personLoad) {
		LOG.info(personLoad.getEntity());
The following table describes the available events. For more details about the exact relation between process steps see the description of available callbacks which map 1:1 to events.
Table 7. Available events
BeforeConvertEvent
Before an aggregate root gets converted into a plan for executing SQL statements, but after the decision was made if the aggregate is new or not, i.e. if an update or an insert is in order.
BeforeSaveEvent
Before an aggregate root gets saved (that is, inserted or updated but after the decision about whether if it gets inserted or updated was made).
AfterSaveEvent
After an aggregate root gets saved (that is, inserted or updated).
AfterConvertEvent
After an aggregate root gets created from a database ResultSet and all its properties get set.
9.11.1. Store-specific EntityCallbacks

Spring Data JDBC uses the EntityCallback API for its auditing support and reacts on the callbacks listed in the following table.
Table 8. Process Steps and Callbacks of the Different Processes performed by Spring Data JDBC.
Determine if an insert or an update of the aggregate is to be performed dependen on if it is new or not.
BeforeConvertCallback
This is the correct callback if you want to set an id programmatically. In the previous step new aggregates got detected as such and a Id generated in this step would be used in the following step.
Convert the aggregate to a aggregate change, it is a sequence of SQL statements to be executed against the database. In this step the decision is made if an Id is provided by the aggregate or if the Id is still empty and is expected to be generated by the database.
BeforeSaveCallback
Changes made to the aggregate root may get considered, but the decision if an id value will be sent to the database is already made in the previous step.
Do not use this for creating Ids for new aggregates. Use BeforeConvertCallback instead.
The SQL statements determined above get executed against the database.
AfterSaveCallback
After an aggregate root gets saved (that is, inserted or updated).
Load the aggregate using 1 or more SQL queries. Construct the aggregate from the resultset.
AfterConvertCallback
9.12. Entity Callbacks

The Spring Data infrastructure provides hooks for modifying an entity before and after certain methods are invoked.
Those so called EntityCallback instances provide a convenient way to check and potentially modify an entity in a callback fashioned style.

An EntityCallback looks pretty much like a specialized ApplicationListener.
Some Spring Data modules publish store specific events (such as BeforeSaveEvent) that allow modifying the given entity. In some cases, such as when working with immutable types, these events can cause trouble.
Also, event publishing relies on ApplicationEventMulticaster. If configuring that with an asynchronous TaskExecutor it can lead to unpredictable outcomes, as event processing can be forked onto a Thread.
Entity callbacks provide integration points with both synchronous and reactive APIs to guarantee in-order execution at well-defined checkpoints within the processing chain, returning a potentially modified entity or an reactive wrapper type.
Entity callbacks are typically separated by API type. This separation means that a synchronous API considers only synchronous entity callbacks and a reactive implementation considers only reactive entity callbacks.
The Entity Callback API has been introduced with Spring Data Commons 2.2. It is the recommended way of applying entity modifications.
Existing store specific ApplicationEvents are still published before the invoking potentially registered EntityCallback instances.
9.12.1. Implementing Entity Callbacks

An EntityCallback is directly associated with its domain type through its generic type argument.
Each Spring Data module typically ships with a set of predefined EntityCallback interfaces covering the entity lifecycle.
Example 76. Anatomy of an EntityCallback
@FunctionalInterface
public interface BeforeSaveCallback<T> extends EntityCallback<T> {
	 * Entity callback method invoked before a domain object is saved.
	 * Can return either the same or a modified instance.
	 * @return the domain object to be persisted.
	T onBeforeSave(T entity <2>, String collection <3>); (1)
BeforeSaveCallback specific method to be called before an entity is saved. Returns a potentially modifed instance.
The entity right before persisting.
A number of store specific arguments like the collection the entity is persisted to.
@FunctionalInterface
public interface ReactiveBeforeSaveCallback<T> extends EntityCallback<T> {
	 * Entity callback method invoked on subscription, before a domain object is saved.
	 * The returned Publisher can emit either the same or a modified instance.
	 * @return Publisher emitting the domain object to be persisted.
	Publisher<T> onBeforeSave(T entity <2>, String collection <3>); (1)
BeforeSaveCallback specific method to be called on subscription, before an entity is saved. Emits a potentially modifed instance.
The entity right before persisting.
A number of store specific arguments like the collection the entity is persisted to.
class DefaultingEntityCallback implements BeforeSaveCallback<Person>, Ordered {      (2)
	@Override
	public Object onBeforeSave(Person entity, String collection) {                   (1)
		if(collection == "user") {
		    return // ...
		return // ...
	@Override
	public int getOrder() {
		return 100;                                                                  (2)
9.12.2. Registering Entity Callbacks

EntityCallback beans are picked up by the store specific implementations in case they are registered in the ApplicationContext.
Most template APIs already implement ApplicationContextAware and therefore have access to the ApplicationContext
The following example explains a collection of valid entity callback registrations:
Example 79. Example EntityCallback Bean registration
@Order(1)                                                           (1)
@Component
class First implements BeforeSaveCallback<Person> {
	@Override
	public Person onBeforeSave(Person person) {
		return // ...
@Component
class DefaultingEntityCallback implements BeforeSaveCallback<Person>,
                                                           Ordered { (2)
	@Override
	public Object onBeforeSave(Person entity, String collection) {
		// ...
	@Override
	public int getOrder() {
		return 100;                                                  (2)
@Configuration
public class EntityCallbackConfiguration {
    @Bean
    BeforeSaveCallback<Person> unorderedLambdaReceiverCallback() {   (3)
        return (BeforeSaveCallback<Person>) it -> // ...
@Component
class UserCallbacks implements BeforeConvertCallback<User>,
                                        BeforeSaveCallback<User> {   (4)
	@Override
	public Person onBeforeConvert(User user) {
		return // ...
	@Override
	public Person onBeforeSave(User user) {
		return // ...
BeforeSaveCallback using a lambda expression. Unordered by default and invoked last. Note that callbacks implemented by a lambda expression do not expose typing information hence invoking these with a non-assignable entity affects the callback throughput. Use a class or enum to enable type filtering for the callback bean.
Combine multiple entity callback interfaces in a single implementation class.
9.13. Custom Conversions

Spring Data JDBC allows registration of custom converters to influence how values are mapped in the database.
Currently, converters are only applied on property-level.
9.13.1. Writing a Property by Using a Registered Spring Converter

The following example shows an implementation of a Converter that converts from a Boolean object to a String value:
import org.springframework.core.convert.converter.Converter;
@WritingConverter
public class BooleanToStringConverter implements Converter<Boolean, String> {
    @Override
    public String convert(Boolean source) {
        return source != null && source ? "T" : "F";
There are a couple of things to notice here: Boolean and String are both simple types hence Spring Data requires a hint in which direction this converter should apply (reading or writing).
By annotating this converter with @WritingConverter you instruct Spring Data to write every Boolean property as String in the database.
9.13.2. Reading by Using a Spring Converter

The following example shows an implementation of a Converter that converts from a String to a Boolean value:
@ReadingConverter
public class StringToBooleanConverter implements Converter<String, Boolean> {
    @Override
    public Boolean convert(String source) {
        return source != null && source.equalsIgnoreCase("T") ? Boolean.TRUE : Boolean.FALSE;
There are a couple of things to notice here: String and Boolean are both simple types hence Spring Data requires a hint in which direction this converter should apply (reading or writing).
By annotating this converter with @ReadingConverter you instruct Spring Data to convert every String value from the database that should be assigned to a Boolean property.
9.13.3. Registering Spring Converters with the JdbcConverter

class MyJdbcConfiguration extends AbstractJdbcConfiguration {
    @Override
    protected List<?> userConverters() {
	return Arrays.asList(new BooleanToStringConverter(), new StringToBooleanConverter());
In previous versions of Spring Data JDBC it was recommended to directly overwrite AbstractJdbcConfiguration.jdbcCustomConversions().
This is no longer necessary or even recommended, since that method assembles conversions intended for all databases, conversions registered by the Dialect used and conversions registered by the user.
If you are migrating from an older version of Spring Data JDBC and have AbstractJdbcConfiguration.jdbcCustomConversions() overwritten conversions from your Dialect will not get registered.
9.13.4. JdbcValue

Value conversion uses JdbcValue to enrich values propagated to JDBC operations with a java.sql.Types type.
Register a custom write converter if you need to specify a JDBC-specific type instead of using type derivation.
This converter should convert the value to JdbcValue which has a field for the value and for the actual JDBCType.
The following example of a Spring Converter implementation converts from a String to a custom Email value object:
@ReadingConverter
public class EmailReadConverter implements Converter<String, Email> {
  public Email convert(String source) {
    return Email.valueOf(source);
If you write a Converter whose source and target type are native types, we cannot determine whether we should consider it as a reading or a writing converter.
Registering the converter instance as both might lead to unwanted results.
For example, a Converter<String, Long> is ambiguous, although it probably does not make sense to try to convert all String instances into Long instances when writing.
To let you force the infrastructure to register a converter for only one way, we provide @ReadingConverter and @WritingConverter annotations to be used in the converter implementation.
Converters are subject to explicit registration as instances are not picked up from a classpath or container scan to avoid unwanted registration with a conversion service and the side effects resulting from such a registration. Converters are registered with CustomConversions as the central facility that allows registration and querying for registered converters based on source- and target type.




    

CustomConversions ships with a pre-defined set of converter registrations:
Converter Disambiguation

Generally, we inspect the Converter implementations for the source and target types they convert from and to.
Depending on whether one of those is a type the underlying data access API can handle natively, we register the converter instance as a reading or a writing converter.
The following examples show a writing-  and a read converter (note the difference is in the order of the qualifiers on Converter):
// Write converter as only the target type is one that can be handled natively
class MyConverter implements Converter<Person, String> { … }
// Read converter as only the source type is one that can be handled natively
class MyConverter implements Converter<String, Person> { … }
Spring Data JDBC does little to no logging on its own.
Instead, the mechanics of JdbcTemplate to issue SQL statements provide logging.
Thus, if you want to inspect what SQL statements are run, activate logging for Spring’s NamedParameterJdbcTemplate or MyBatis.
9.15. Transactionality

The methods of CrudRepository instances are transactional by default.
For reading operations, the transaction configuration readOnly flag is set to true.
All others are configured with a plain @Transactional annotation so that default transaction configuration applies.
For details, see the Javadoc of SimpleJdbcRepository.
If you need to tweak transaction configuration for one of the methods declared in a repository, redeclare the method in your repository interface, as follows:
Example 80. Custom transaction configuration for CRUD
interface UserRepository extends CrudRepository<User, Long> {
  @Override
  @Transactional(timeout = 10)
  List<User> findAll();
  // Further query method declarations
The preceding causes the findAll() method to be run with a timeout of 10 seconds and without the readOnly flag.
Another way to alter transactional behavior is by using a facade or service implementation that typically covers more than one repository.
Its purpose is to define transactional boundaries for non-CRUD operations.
The following example shows how to create such a facade:
Example 81. Using a facade to define transactions for multiple repository calls
@Service
public class UserManagementImpl implements UserManagement {
  private final UserRepository userRepository;
  private final RoleRepository roleRepository;
  UserManagementImpl(UserRepository userRepository,
    RoleRepository roleRepository) {
    this.userRepository = userRepository;
    this.roleRepository = roleRepository;
  @Transactional
  public void addRoleToAllUsers(String roleName) {
    Role role = roleRepository.findByName(roleName);
    for (User user : userRepository.findAll()) {
      user.addRole(role);
      userRepository.save(user);
The preceding example causes calls to addRoleToAllUsers(…) to run inside a transaction (participating in an existing one or creating a new one if none are already running).
The transaction configuration for the repositories is neglected, as the outer transaction configuration determines the actual repository to be used.
Note that you have to explicitly activate <tx:annotation-driven /> or use @EnableTransactionManagement to get annotation-based configuration for facades working.
Note that the preceding example assumes you use component scanning.
9.15.1. Transactional Query Methods

To let your query methods be transactional, use @Transactional at the repository interface you define, as the following example shows:
Example 82. Using @Transactional at query methods
@Transactional(readOnly = true)
interface UserRepository extends CrudRepository<User, Long> {
  List<User> findByLastname(String lastname);
  @Modifying
  @Transactional
  @Query("delete from User u where u.active = false")
  void deleteInactiveUsers();
Typically, you want the readOnly flag to be set to true, because most of the query methods only read data.
In contrast to that, deleteInactiveUsers() uses the @Modifying annotation and overrides the transaction configuration.
Thus, the method is with the readOnly flag set to false.
It is highly recommended to make query methods transactional. These methods might execute more then one query in order to populate an entity.
Without a common transaction Spring Data JDBC executes the queries in different connections.
This may put excessive strain on the connection pool and might even lead to dead locks when multiple methods request a fresh connection while holding on to one.
It is definitely reasonable to mark read-only queries as such by setting the readOnly flag.
This does not, however, act as a check that you do not trigger a manipulating query (although some databases reject INSERT and UPDATE statements inside a read-only transaction).
Instead, the readOnly flag is propagated as a hint to the underlying JDBC driver for performance optimizations.
9.16.1. Basics

Spring Data provides sophisticated support to transparently keep track of who created or changed an entity and when the change happened.To benefit from that functionality, you have to equip your entity classes with auditing metadata that can be defined either using annotations or by implementing an interface.
Additionally, auditing has to be enabled either through Annotation configuration or XML configuration to register the required infrastructure components.
Please refer to the store-specific section for configuration samples.
Annotation-based Auditing Metadata

We provide @CreatedBy and @LastModifiedBy to capture the user who created or modified the entity as well as @CreatedDate and @LastModifiedDate to capture when the change happened.
Example 83. An audited entity
class Customer {
  @CreatedBy
  private User user;
  @CreatedDate
  private Instant createdDate;
  // … further properties omitted
As you can see, the annotations can be applied selectively, depending on which information you want to capture.
The annotations, indicating to capture when changes are made, can be used on properties of type JDK8 date and time types, long, Long, and legacy Java Date and Calendar.
Auditing metadata does not necessarily need to live in the root level entity but can be added to an embedded one (depending on the actual store in use), as shown in the snippet below.
Example 84. Audit metadata in embedded entity
class Customer {
  private AuditMetadata auditingMetadata;
  // … further properties omitted
class AuditMetadata {
  @CreatedBy
  private User user;
  @CreatedDate
  private Instant createdDate;
AuditorAware

In case you use either @CreatedBy or @LastModifiedBy, the auditing infrastructure somehow needs to become aware of the current principal. To do so, we provide an AuditorAware<T> SPI interface that you have to implement to tell the infrastructure who the current user or system interacting with the application is. The generic type T defines what type the properties annotated with @CreatedBy or @LastModifiedBy have to be.
The following example shows an implementation of the interface that uses Spring Security’s Authentication object:
Example 85. Implementation of AuditorAware based on Spring Security
class SpringSecurityAuditorAware implements AuditorAware<User> {
  @Override
  public Optional<User> getCurrentAuditor() {
    return Optional.ofNullable(SecurityContextHolder.getContext())
            .map(SecurityContext::getAuthentication)
            .filter(Authentication::isAuthenticated)
            .map(Authentication::getPrincipal)
            .map(User.class::cast);
The implementation accesses the Authentication object provided by Spring Security and looks up the custom UserDetails instance that you have created in your UserDetailsService implementation. We assume here that you are exposing the domain user through the UserDetails implementation but that, based on the Authentication found, you could also look it up from anywhere.
ReactiveAuditorAware

When using reactive infrastructure you might want to make use of contextual information to provide @CreatedBy or @LastModifiedBy information.
We provide an ReactiveAuditorAware<T> SPI interface that you have to implement to tell the infrastructure who the current user or system interacting with the application is. The generic type T defines what type the properties annotated with @CreatedBy or @LastModifiedBy have to be.
The following example shows an implementation of the interface that uses reactive Spring Security’s Authentication object:
Example 86. Implementation of ReactiveAuditorAware based on Spring Security
class SpringSecurityAuditorAware implements ReactiveAuditorAware<User> {
  @Override
  public Mono<User> getCurrentAuditor() {
    return ReactiveSecurityContextHolder.getContext()
                .map(SecurityContext::getAuthentication)
                .filter(Authentication::isAuthenticated)
                .map(Authentication::getPrincipal)
                .map(User.class::cast);
The implementation accesses the Authentication object provided by Spring Security and looks up the custom UserDetails instance that you have created in your UserDetailsService implementation. We assume here that you are exposing the domain user through the UserDetails implementation but that, based on the Authentication found, you could also look it up from anywhere.
9.17. JDBC Auditing

In order to activate auditing, add @EnableJdbcAuditing to your configuration, as the following example shows:
Example 87. Activating auditing with Java configuration
@Configuration
@EnableJdbcAuditing
class Config {
  @Bean
  AuditorAware<AuditableUser> auditorProvider() {
    return new AuditorAwareImpl();
If you expose a bean of type AuditorAware to the ApplicationContext, the auditing infrastructure automatically picks it up and uses it to determine the current user to be set on domain types.
If you have multiple implementations registered in the ApplicationContext, you can select the one to be used by explicitly setting the auditorAwareRef attribute of @EnableJdbcAuditing.
9.18. JDBC Locking

Spring Data JDBC supports locking on derived query methods.
To enable locking on a given derived query method inside a repository, you annotate it with @Lock.
The required value of type LockMode offers two values: PESSIMISTIC_READ which guarantees that the data you are reading doesn’t get modified and PESSIMISTIC_WRITE which obtains a lock to modify the data.
Some databases do not make this distinction.
In that cases both modes are equivalent of PESSIMISTIC_WRITE.
Example 88. Using @Lock on derived query method
interface UserRepository extends CrudRepository<User, Long> {
  @Lock(LockMode.PESSIMISTIC_READ)
  List<User> findByLastname(String lastname);
As you can see above, the method findByLastname(String lastname) will be executed with a pessimistic read lock. If you are using a databse with the MySQL Dialect this will result for example in the following query:
Example 89. Resulting Sql query for MySQL dialect
Select * from user u where u.lastname = lastname LOCK IN SHARE MODE
Dependency Injection
Pattern to hand a component’s dependency to the component from outside, freeing the component to lookup the dependent itself.
For more information, see https://en.wikipedia.org/wiki/Dependency_Injection.
Java Persistence API
Spring
Java application framework — https://projects.spring.io/spring-framework
The <populator /> element

The <populator /> element allows to populate a data store via the Spring Data repository infrastructure.^[1]
Table 9. Attributes
Supported query method subject keywords

The following table lists the subject keywords generally supported by the Spring Data repository query derivation mechanism to express the predicate.
Consult the store-specific documentation for the exact list of supported keywords, because some keywords listed here might not be supported in a particular store.
Table 10. Query subject keywords
find…By, read…By, get…By, query…By, search…By, stream…By
General query method returning typically the repository type, a Collection or Streamable subtype or a result wrapper such as Page, GeoResults or any other store-specific result wrapper. Can be used as findBy…, findMyDomainTypeBy… or in combination with additional keywords.
exists…By
Exists projection, returning typically a boolean result.
count…By
Count projection returning a numeric result.
delete…By, remove…By
Delete query method returning either no result (void) or the delete count.
…First<number>…, …Top<number>…
Limit the query results to the first <number> of results. This keyword can occur in any place of the subject between find (and the other keywords) and by.
…Distinct…
Use a distinct query to return only unique results. Consult the store-specific documentation whether that feature is supported. This keyword can occur in any place of the subject between find (and the other keywords) and by.
Supported query method predicate keywords and modifiers

The following table lists the predicate keywords generally supported by the Spring Data repository query derivation mechanism.
However, consult the store-specific documentation for the exact list of supported keywords, because some keywords listed here might not be supported in a particular store.
Table 11. Query predicate keywords
AllIgnoreCase, AllIgnoringCase
Ignore case for all suitable properties. Used somewhere in the query method predicate.
OrderBy…
Specify a static sorting order followed by the property path and direction (e. g. OrderByFirstnameAscLastnameDesc).
Supported Query Return Types

The following table lists the return types generally supported by Spring Data repositories.
However, consult the store-specific documentation for the exact list of supported return types, because some types listed here might not be supported in a particular store.
Geospatial types (such as GeoResult, GeoResults, and GeoPage) are available only for data stores that support geospatial queries.
Some store modules may define their own result wrapper types.
A unique entity. Expects the query method to return one result at most. If no result is found, null is returned. More than one result triggers an IncorrectResultSizeDataAccessException.
Iterator<T>
An Iterator.
Collection<T>
A Collection.
List<T>
A List.
Optional<T>
A Java 8 or Guava Optional. Expects the query method to return one result at most. If no result is found, Optional.empty() or Optional.absent() is returned. More than one result triggers an IncorrectResultSizeDataAccessException.
Option<T>
Either a Scala or Vavr Option type. Semantically the same behavior as Java 8’s Optional, described earlier.
Stream<T>
A Java 8 Stream.
Streamable<T>
A convenience extension of Iterable that directy exposes methods to stream, map and filter results, concatenate them etc.
Types that implement Streamable and take a Streamable constructor or factory method argument
Types that expose a constructor or ….of(…)/….valueOf(…) factory method taking a Streamable as argument. See Returning Custom Streamable Wrapper Types for details.
Vavr Seq, List, Map, Set
Vavr collection types. See Support for Vavr Collections for details.
Future<T>
A Future. Expects a method to be annotated with @Async and requires Spring’s asynchronous method execution capability to be enabled.
CompletableFuture<T>
A Java 8 CompletableFuture. Expects a method to be annotated with @Async and requires Spring’s asynchronous method execution capability to be enabled.
Slice<T>
A sized chunk of data with an indication of whether there is more data available. Requires a Pageable method parameter.
Page<T>
A Slice with additional information, such as the total number of results. Requires a Pageable method parameter.
GeoResult<T>
A result entry with additional information, such as the distance to a reference location.
GeoResults<T>
A list of GeoResult<T> with additional information, such as the average distance to a reference location.
GeoPage<T>
A Page with GeoResult<T>, such as the average distance to a reference location.
Mono<T>
A Project Reactor Mono emitting zero or one element using reactive repositories. Expects the query method to return one result at most. If no result is found, Mono.empty() is returned. More than one result triggers an IncorrectResultSizeDataAccessException.
Flux<T>
A Project Reactor Flux emitting zero, one, or many elements using reactive repositories. Queries returning Flux can emit also an infinite number of elements.
Single<T>
A RxJava Single emitting a single element using reactive repositories. Expects the query method to return one result at most. If no result is found, Mono.empty() is returned. More than one result triggers an IncorrectResultSizeDataAccessException.
Maybe<T>
A RxJava Maybe emitting zero or one element using reactive repositories. Expects the query method to return one result at most. If no result is found, Mono.empty() is returned. More than one result triggers an IncorrectResultSizeDataAccessException.
Flowable<T>
A RxJava Flowable emitting zero, one, or many elements using reactive repositories. Queries returning Flowable can emit also an infinite number of elements.