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【转】Spring Data JDBC - Reference Documentation

Spring Data JDBC - Reference Documentation

Jens Schauder, Jay Bryant, Mark Paluch, Bastian Wilhelm
Version 2.1.7,
2021-03-31

© 2018-2021 The original authors.
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在这里插入图片描述Copies of this document may be made for your own use and for distribution to others, provided that you do not charge any fee for such copies and further provided that each copy contains this Copyright Notice, whether distributed in print or electronically.

Preface

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.

1. Learning Spring

Spring Data uses Spring framework’s core functionality, including:

  • IoC container

  • type conversion system

  • expression language

  • JMX integration

  • DAO exception hierarchy.

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.

2.Requirements

The Spring Data JDBC binaries require JDK level 8.0 and above and Spring Framework 5.3.5 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:

  • DB2

  • H2

  • HSQLDB

  • MariaDB

  • Microsoft SQL Server

  • MySQL

  • Oracle

  • Postgres

If you use a different database then your application won’t startup. The dialect section contains further detail on how to proceed in such case.

3. Additional Help Resources

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.

Professional Support

Professional, from-the-source support, with guaranteed response time, is available from Pivotal Sofware, Inc., the company behind Spring Data and Spring.

4. Following Development

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).

5. Project Metadata

  • Release repository: https://repo.spring.io/libs-release

  • Milestone repository: https://repo.spring.io/libs-milestone

  • Snapshot repository: https://repo.spring.io/libs-snapshot

6. New & Noteworthy

This section covers the significant changes for each version.

6.1. What’s New in Spring Data JDBC 2.1

  • Dialect for Oracle databases.

  • Support for @Value in persistence constructors.

6.2. What’s New in Spring Data JDBC 2.0

  • Optimistic Locking support.

  • Support for PagingAndSortingRepository.

  • Query Derivation.

  • Full Support for H2.

  • All SQL identifiers know get quoted by default.

  • Missing columns no longer cause exceptions.

6.3. What’s New in Spring Data JDBC 1.1

  • @Embedded entities support.

  • Store byte[] as BINARY.

  • Dedicated insert method in the JdbcAggregateTemplate.

  • Read only property support.

6.4. What’s New in Spring Data JDBC 1.0

  • Basic support for CrudRepository.

  • @Query support.

  • MyBatis support.

  • Id generation.

  • Event support.

  • Auditing.

  • CustomConversions.

7. Dependencies

Due to the different inception dates of individual Spring Data modules, most of them carry different major and minor version numbers. The easiest way to find compatible ones is to rely on the Spring Data Release Train BOM that we ship with the compatible versions defined. In a Maven project, you would declare this dependency in the section of your POM as follows:

Example 1. Using the Spring Data release train BOM


    
        
            org.springframework.data
            spring-data-bom
            2020.0.7
            import
            pom

The current release train version is 2020.0.7. 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:

The current release train version is 2020.0.7. 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: c a l v e r − {calver}- calver−{modifier}, where modifier can be one of the following:

SNAPSHOT: Current snapshots

M1, M2, and so on: Milestones

RC1, RC2, and so on: Release candidates

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

Example 2. Declaring a dependency to a Spring Data module

<dependencies>
    <dependency>
        <groupId>org.springframework.datagroupId>
        <artifactId>spring-data-jpaartifactId>
    dependency>
<dependencies>

7.1. Dependency Management with Spring Boot

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

7.2. Spring Framework

The current version of Spring Data modules require Spring Framework 5.3.5 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.

8. Working with Spring Data Repositories

The goal of the Spring Data repository abstraction is to significantly reduce the amount of boilerplate code required to implement data access layers for various persistence stores.

在这里插入图片描述 Spring Data repository documentation and your module

​ This chapter explains the core concepts and interfaces of Spring Data repositories. The information in this chapter is pulled from the Spring Data Commons module. It uses the configuration and code samples for the Java Persistence API (JPA) module. You should adapt the XML namespace declaration and the types to be extended to the equivalents of the particular module that you use. “Namespace reference” covers XML configuration, which is supported across all Spring Data modules that support the repository API. “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 ID type of the domain class as type arguments. This interface acts primarily as a marker interface to capture the types to work with and to help you to discover interfaces that extend this one. The CrudRepository interface provides 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);      	//Saves the given entity.

	Optional<T> findById(ID primaryKey);	//Returns the entity identified by the given ID.

	Iterable<T> findAll();					//Returns all entities.

	long count();							//Returns the number of entities.

	void delete(T entity);					//Deletes the given entity.

	boolean existsById(ID primaryKey);		//Indicates whether an entity with the given ID exists.

	// … more functionality omitted.
}

在这里插入图片描述We also provide persistence technology-specific abstractions, such as JpaRepository or MongoRepository. Those interfaces extend CrudRepository and expose the capabilities of the underlying persistence technology in addition to the rather generic persistence technology-agnostic interfaces such as CrudRepository.

On top of the CrudRepository, there is a PagingAndSortingRepository abstraction that adds additional methods to ease paginated access to entities:

Example 4. PagingAndSortingRepository interface

public interface PagingAndSortingRepository<T, ID> extends CrudRepository<T, ID> {

	Iterable<T> findAll(Sort sort);

	Page<T> findAll(Pageable pageable);
}

To access the second page of User by a page size of 20, you could do something like the following:

PagingAndSortingRepository<User, Long> repository = // … get access to a bean
Page<User> users = repository.findAll(PageRequest.of(1, 20));

In addition to query methods, query derivation for both count and delete queries is available. The following list shows the interface definition for a derived count query:

Example 5. Derived Count Query

interface UserRepository extends CrudRepository<User, Long> {

	long countByLastname(String lastname);
}

The following listing shows the interface definition for a derived delete query:

Example 6. Derived Delete Query

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:

  1. Declare an interface extending Repository or one of its subinterfaces and type it to the domain class and ID type that it should handle, as shown in the following example:
interface PersonRepository extends Repository<Person, Long> { … }
  1. Declare query methods on the interface.
interface PersonRepository extends Repository<Person, Long> {
	List<Person> findByLastname(String lastname);
}
  1. Set up Spring to create proxy instances for those interfaces, either with JavaConfig or with XML configuration.
    a. To use Java configuration, create a class similar to the following:
import org.springframework.data.jpa.repository.config.EnableJpaRepositories;

@EnableJpaRepositories
class Config { … }

​ b. To use XML configuration, define a bean similar to the following:


<beans xmlns="http://www.springframework.org/schema/beans"
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xmlns:jpa="http://www.springframework.org/schema/data/jpa"
    xsi:schemaLocation="http://www.springframework.org/schema/beans
        https://www.springframework.org/schema/beans/spring-beans.xsd
        http://www.springframework.org/schema/data/jpa
        https://www.springframework.org/schema/data/jpa/spring-jpa.xsd">

    <jpa:repositories base-package="com.acme.repositories"/>

beans>

The JPA namespace is used in this example. If you use the repository abstraction for any other store, you need to change this to the appropriate namespace declaration of your store module. In other words, you should exchange jpa in favor of, for example, mongodb.

Also, note that the JavaConfig variant does not configure a package explicitly, because the package of the annotated class is used by default. To customize the package to scan, use one of the basePackage… attributes of the data-store-specific repository’s @Enable${store}Repositories-annotation.

  1. Inject the repository instance and use it, as shown in the following example:
class SomeClient {

	private final PersonRepository repository;

	SomeClient(PersonRepository repository) {
		this.repository = repository;
	}

	void doSomething() {
		List<Person> persons = repository.findByLastname("Matthews");
	}
}

The sections that follow explain each step in detail:

  • Defining Repository Interfaces

  • Defining Query Methods

  • Creating Repository Instances

  • Custom Implementations for Spring Data Repositories

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, extend CrudRepository instead of Repository.

8.3.1. Fine-tuning Repository Definition

Typically, your repository interface extends Repository, CrudRepository, or PagingAndSortingRepository. Alternatively, if you do not want to extend Spring Data interfaces, you can also annotate your repository interface with @RepositoryDefinition. Extending CrudRepository exposes a complete set of methods to manipulate your entities. If you prefer to be selective about the methods being exposed, copy the methods you want to expose from CrudRepository into your domain repository.

在这里插入图片描述Doing so lets you define your own abstractions on top of the provided Spring Data Repositories functionality.

The following example shows how to selectively expose CRUD methods (findById and save, in this case):

Example 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.

在这里插入图片描述The intermediate repository interface is annotated with @NoRepositoryBean. Make sure you add that annotation to all repository interfaces for which Spring Data should not create instances at runtime.

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:

  1. If the repository definition extends the module-specific repository, it is a valid candidate for the particular Spring Data module.

  2. 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> { … }

MyRepository and UserRepository extend JpaRepository in their type hierarchy. They are valid candidates for the Spring Data JPA module.

The following example shows a repository that uses generic interfaces:

Example 9. Repository definitions using generic interfaces

interface AmbiguousRepository extends Repository<User, Long> { … }

@NoRepositoryBean
interface MyBaseRepository<T, ID> extends CrudRepository<T, ID> { … }

interface AmbiguousUserRepository 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 example shows a repository that uses domain classes with annotations:

Example 10. Repository definitions using domain classes with annotations

interface PersonRepository extends Repository<Person, Long> { … }

@Entity
class Person { … }

interface UserRepository extends Repository<User, Long> { … }

@Document
class User { … }

PersonRepository references Person, which is annotated with the JPA @Entity annotation, so this repository clearly belongs to Spring Data JPA. UserRepository references User, which is annotated with Spring Data MongoDB’s @Document annotation.

The following bad example shows a repository that uses domain classes with mixed annotations:

Example 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 { … }

8.4. Defining Query Methods

The repository proxy has two ways to derive a store-specific query from the method name:

  • By deriving the query from the method name directly.

  • By using a manually defined query.

Available options depend on the actual store. However, there must be a strategy that decides what actual query is created. The next section describes the available options.

8.4.1. Query Lookup Strategies

The following strategies are available for the repository infrastructure to resolve the query. With XML configuration, you can configure the strategy at the namespace through the query-lookup-strategy attribute. For Java configuration, you can use the queryLookupStrategy attribute of the Enable${store}Repositories annotation. Some strategies may not be supported for particular datastores.

  • CREATE attempts to construct a store-specific query from the query method name. The general approach is to remove a given set of well known prefixes from the method name and parse the rest of the method. You can read more about query construction in “Query Creation”.

  • 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 “Special parameter handling”.

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:

List<Person> findByAddressZipCode(ZipCode zipCode);

Assume a Person has an Address with a ZipCode. In that case, the method creates the x.address.zipCode property traversal. The resolution algorithm starts by interpreting the entire part (AddressZipCode) as the property and checks the domain class for a property with that name (uncapitalized). If the algorithm succeeds, it uses that property. If not, the algorithm splits up the source at the camel-case parts from the right side into a head and a tail and tries to find the corresponding property — in our example, AddressZip and Code. If the algorithm finds a property with that head, it takes the tail and continues building the tree down from there, splitting the tail up in the way just described. If the first split does not match, the algorithm moves the split point to the left (Address, ZipCode) and continues.

Although this should work for most cases, it is possible for the algorithm to select the wrong property. Suppose the Person class has an addressZip property as well. The algorithm would match in the first split round already, choose the wrong property, and fail (as the type of addressZip probably has no code property).

To resolve this ambiguity you can use _ inside your method name to manually define traversal points. So our method name would be as follows:

List<Person> findByAddress_ZipCode(ZipCode zipCode);

Because we treat the underscore character as a reserved character, we strongly advise following standard Java naming conventions (that is, not using underscores in property names but using camel case instead).

8.4.4. Special parameter handling

To handle parameters in your query, define method parameters as already seen in the preceding examples. Besides that, the infrastructure recognizes certain specific types like Pageable and Sort, to apply pagination and sorting to your queries dynamically. The following example demonstrates these features:

Example 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);

在这里插入图片描述APIs taking Sort and Pageable expect non-null values to be handed into methods. If you do not want to apply any sorting or pagination, use Sort.unsorted() and Pageable.unpaged().

The first method lets you pass an org.springframework.data.domain.Pageable instance to the query method to dynamically add paging to your statically defined query. A Page knows about the total number of elements and pages available. It does so by the infrastructure triggering a count query to calculate the overall number. As this might be expensive (depending on the store used), you can instead return a Slice. A Slice knows only about whether a next Slice is available, which might be sufficient when walking through a larger result set.

Sorting options are handled through the Pageable instance, too. If you need only sorting, add an org.springframework.data.domain.Sort parameter to your method. As you can see, returning a List is also possible. In this case, the additional metadata required to build the actual Page instance is not created (which, in turn, means that the additional count query that would have been necessary is not issued). Rather, it restricts the query to look up only the given range of entities.

在这里插入图片描述To find out how many pages you get for an entire query, you have to trigger an additional count query. By default, this query is derived from the query you actually trigger.

Paging and Sorting

You can define simple sorting expressions by using property names. You can concatenate expressions to collect multiple criteria into one expression.

Example 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());

在这里插入图片描述TypedSort.by(…) makes use of runtime proxies by (typically) using CGlib, which may interfere with native image compilation when using tools such as Graal VM Native.

If your store implementation supports Querydsl, you can also use the generated metamodel types to define sort expressions:

Example 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.

在这里插入图片描述Limiting the results in combination with dynamic sorting by using a Sort parameter lets you express query methods for the ‘K’ smallest as well as for the ‘K’ biggest elements.

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:

  1. The type implements Streamable.

  2. The type exposes either a constructor or a static factory method named of(…) or valueOf(…) that takes Streamable as an argument.

The following listing shows an example:

class Product {												//[1]
	MonetaryAmount getPrice() { … }
}

@RequiredArgConstructor(staticName = "of")
class Products implements Streamable<Product> {				//[2]

    private 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]
}

[1] A Product entity that exposes API to access the product’s price.
[2] A wrapper type for a Streamable that can be constructed by using Products.of(…) (factory method created with the Lombok annotation).
A standard constructor taking the Streamable will do as well.
[3] The wrapper type exposes an additional API, calculating new values on the Streamable.
[4] Implement the Streamable interface and delegate to the actual result.
[5] That wrapper type Products can be used directly as a query method return type.
You do not need to return Streamable and manually wrap it after the query in the repository client.

Support for Vavr Collections

Vavr is a library that embraces functional programming concepts in Java. It ships with a custom set of collection types that you can use as query method return types, as the following table shows:

Vavr collection type Used Vavr implementation type Valid Java source types
io.vavr.collection.Seq io.vavr.collection.List java.util.Iterable
io.vavr.collection.Set io.vavr.collection.LinkedHashSet java.util.Iterable
io.vavr.collection.Map io.vavr.collection.LinkedHashMap java.util.Map

You can use the types in the first column (or subtypes thereof) as query method return types and get the types in the second column used as implementation type, depending on the Java type of the actual query result (third column). Alternatively, you can declare Traversable (the Vavr Iterable equivalent), and we then derive the implementation class from the actual return value. That is, a java.util.List is turned into a Vavr List or Seq, a java.util.Set becomes a Vavr LinkedHashSet Set, and so on.

8.4.7. Null Handling of Repository Methods

As of Spring Data 2.0, repository CRUD methods that return an individual aggregate instance use Java 8’s Optional to indicate the potential absence of a value. Besides that, Spring Data supports returning the following wrapper types on query methods:

  • com.google.common.base.Optional

  • scala.Option

  • io.vavr.control.Option

Alternatively, query methods can choose not to use a wrapper type at all. The absence of a query result is then indicated by returning null. Repository methods returning collections, collection alternatives, wrappers, and streams are guaranteed never to return null but rather the corresponding empty representation. See “Repository query return types” 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 20. 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 21. 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]
}

[1] The repository resides in a package (or sub-package) for which we have defined non-null behavior.
[2] Throws an EmptyResultDataAccessException when the query does not produce a result.
Throws an IllegalArgumentException when the emailAddress handed to the method is null.
[3] Returns null when the query does not produce a result.
Also accepts null as the value for emailAddress.
[4] Returns Optional.empty() when the query does not produce a result.
Throws an IllegalArgumentException when the emailAddress handed to the method is null.

Nullability in Kotlin-based Repositories

Kotlin has the definition of nullability constraints 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 22. Using nullability constraints on Kotlin repositories

interface UserRepository : Repository<User, String> {

    fun findByUsername(username: String): User		//[1]

    fun findByFirstname(firstname: String?): User?	//[2]
}

[1] The method defines both the parameter and the result as non-nullable (the Kotlin default).
The Kotlin compiler rejects method invocations that pass null to the method.
If the query yields an empty result, an EmptyResultDataAccessException is thrown.
[2] This method accepts null for the firstname parameter and returns null if the query does not produce a result.

8.4.8. Streaming Query Results

You can process the results of query methods incrementally by using a Java 8 Stream as the return type. Instead of wrapping the query results in a Stream, data store-specific methods are used to perform the streaming, as shown in the following example:

Example 23. Stream the result of a query with Java 8 Stream

@Query("select u from User u")
Stream<User> findAllByCustomQueryAndStream();

Stream<User> readAllByFirstnameNotNull();

@Query("select u from User u")
Stream<User> streamAllPaged(Pageable pageable);

在这里插入图片描述A Stream potentially wraps underlying data store-specific resources and must, therefore, be closed after usage. You can either manually close the Stream by using the close() method or by using a Java 7 try-with-resources block, as shown in the following example:

Example 24. Working with a Stream result in a try-with-resources block

try (Stream<User> stream = repository.findAllByCustomQueryAndStream()) {
	stream.forEach(…);
}

在这里插入图片描述Not all Spring Data modules currently support Stream as a return type.

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:

@Async
Future<User> findByFirstname(String firstname);					//[1]

@Async
CompletableFuture<User> findOneByFirstname(String firstname);	//[2]

@Async
ListenableFuture<User> findOneByLastname(String lastname);		//[3]

[1] Use java.util.concurrent.Future as the return type.
[2] Use a Java 8 java.util.concurrent.CompletableFuture as the return type.
[3] Use a org.springframework.util.concurrent.ListenableFuture as the return type.

8.5. Creating Repository Instances

This section covers how to create instances and bean definitions for the defined repository interfaces. One way to do so is by using the Spring namespace that is shipped with each Spring Data module that supports the repository mechanism, although we generally recommend using Java configuration.

8.5.1. XML Configuration

Each Spring Data module includes a repositories element that lets you define a base package that Spring scans for you, as shown in the following example:

Example 25. Enabling Spring Data repositories via XML


<beans:beans xmlns:beans="http://www.springframework.org/schema/beans"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xmlns="http://www.springframework.org/schema/data/jpa"
xsi:schemaLocation="http://www.springframework.org/schema/beans
https://www.springframework.org/schema/beans/spring-beans.xsd
http://www.springframework.org/schema/data/jpa
https://www.springframework.org/schema/data/jpa/spring-jpa.xsd">

  <repositories base-package="com.acme.repositories" />

beans:beans>

In the preceding example, Spring is instructed to scan com.acme.repositories and all its sub-packages for interfaces extending Repository or one of its sub-interfaces. For each interface found, the infrastructure registers the persistence technology-specific FactoryBean to create the appropriate proxies that handle invocations of the query methods. Each bean is registered under a bean name that is derived from the interface name, so an interface of UserRepository would be registered under userRepository. Bean names for nested repository interfaces are prefixed with their enclosing type name. The base-package attribute allows wildcards so that you can define a pattern of scanned packages.

Using Filters

By default, the infrastructure picks up every interface that extends the persistence technology-specific Repository sub-interface located under the configured base package and creates a bean instance for it. However, you might want more fine-grained control over which interfaces have bean instances created for them. To do so, use and elements inside the element. The semantics are exactly equivalent to the elements in Spring’s context namespace. For details, see the Spring reference documentation for these elements.

For example, to exclude certain interfaces from instantiation as repository beans, you could use the following configuration:

Example 26. Using exclude-filter element

<repositories base-package="com.acme.repositories">
<context:exclude-filter type="regex" expression=".*SomeRepository" />
repositories>

The preceding example excludes all interfaces ending in SomeRepository from being instantiated.

8.5.2. Java Configuration

You can also trigger the repository infrastructure by using a store-specific @Enable${store}Repositories annotation on a Java configuration class. For an introduction to Java-based configuration of the Spring container, see JavaConfig in the Spring reference documentation.

A sample configuration to enable Spring Data repositories resembles the following:

Example 27. Sample annotation-based repository configuration

@Configuration
@EnableJpaRepositories("com.acme.repositories")
class ApplicationConfiguration {

	@Bean
	EntityManagerFactory entityManagerFactory() {
	// …
	}
}

在这里插入图片描述The preceding example uses the JPA-specific annotation, which you would change according to the store module you actually use. The same applies to the definition of the EntityManagerFactory bean. See the sections covering the store-specific configuration.

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 28. 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

This section covers repository customization and how fragments form a composite repository.

When a query method requires a different behavior or cannot be implemented by query derivation, you need to provide a custom implementation. Spring Data repositories let you provide custom repository code and integrate it with generic CRUD abstraction and query method functionality.

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 29. Interface for custom repository functionality

interface CustomizedUserRepository {
	void someCustomMethod(User user);
}

Example 30. Implementation of custom repository functionality

class CustomizedUserRepositoryImpl implements CustomizedUserRepository {

    public void someCustomMethod(User user) {
        // Your custom implementation
        }
}

在这里插入图片描述The most important part of the class name that corresponds to the fragment interface is the Impl postfix.

The implementation itself does not depend on Spring Data and can be a regular Spring bean. Consequently, you can use standard dependency injection behavior to inject references to other beans (such as a JdbcTemplate), take part in aspects, and so on.

Then you can let your repository interface extend the fragment interface, as follows:

Example 31. 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 32. 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 33. 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 34. 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
    }
}

The following example shows a repository that uses the preceding repository fragment:

Example 35. Customized repository interfaces

interface UserRepository extends CrudRepository<User, Long>, CustomizedSave<User> {
}

interface PersonRepository extends CrudRepository<Person, Long>, CustomizedSave<Person> {
}
Configuration

If you use namespace configuration, the repository infrastructure tries to autodetect custom implementation fragments by scanning for classes below the package in which it found a repository. These classes need to follow the naming convention of appending the namespace element’s repository-impl-postfix attribute to the fragment interface name. This postfix defaults to Impl. The following example shows a repository that uses the default postfix and a repository that sets a custom value for the postfix:

Example 36. Configuration example

<repositories base-package="com.acme.repository" />

<repositories base-package="com.acme.repository" repository-impl-postfix="MyPostfix" />

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 37. Resolution of ambiguous implementations

package com.acme.impl.one;

class CustomizedUserRepositoryImpl implements CustomizedUserRepository {

	// Your custom implementation
}

package com.acme.impl.two;

@Component("specialCustomImpl")
class CustomizedUserRepositoryImpl implements CustomizedUserRepository {

	// Your custom implementation
}

If you annotate the UserRepository interface with @Component("specialCustom"), the bean name plus Impl then matches the one defined for the repository implementation in com.acme.impl.two, and it is used instead of the first one.

Manual Wiring

If your custom implementation uses annotation-based configuration and autowiring only, the preceding approach shown works well, because it is treated as any other Spring bean. If your implementation fragment bean needs special wiring, you can declare the bean and name it according to the conventions described in the preceding section. 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 38. Manual wiring of custom implementations

<repositories base-package="com.acme.repository" />

<beans:bean id="userRepositoryImpl" class="…">
  
beans:bean>

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 39. 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
	}
}

在这里插入图片描述The class needs to have a constructor of the super class which the store-specific repository factory implementation uses. If the repository base class has multiple constructors, override the one taking an EntityInformation plus a store specific infrastructure object (such as an EntityManager or a template class).

The final step is to make the Spring Data infrastructure aware of the customized repository base class. In Java configuration, you can do so by using the repositoryBaseClass attribute of the @Enable${store}Repositories annotation, as shown in the following example:

Example 40. Configuring a custom repository base class using JavaConfig

@Configuration
@EnableJpaRepositories(repositoryBaseClass = MyRepositoryImpl.class)
class ApplicationConfiguration { … }

A corresponding attribute is available in the XML namespace, as shown in the following example:

Example 41. Configuring a custom repository base class using XML

<repositories base-package="com.acme.repository"
base-class="….MyRepositoryImpl" />

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 42. 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
    }

}

[1] The method that uses @DomainEvents can return either a single event instance or a collection of events.
It must not take any arguments.
[2] 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).
The methods are called every time one of a Spring Data repository’s save(…), saveAll(…), delete(…) or deleteAll(…) methods are called.

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 43. 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.
}

[1] Finds and returns a single entity matching the Predicate.
[2] Finds and returns all entities matching the Predicate.
[3] Returns the number of entities matching the Predicate.
[4] Returns whether an entity that matches the Predicate exists.
To use the Querydsl support, extend QuerydslPredicateExecutor on your repository interface, as the following example shows:

Example 44. Querydsl integration on repositories

interface UserRepository extends CrudRepository<User, Long>, QuerydslPredicateExecutor<User> {
}

The preceding example lets you write type-safe queries by using Querydsl Predicate instances, as the following example shows:

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 45. Enabling Spring Data web support

@Configuration
@EnableWebMvc
@EnableSpringDataWebSupport
class WebConfiguration {}

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.

Alternatively, if you use XML configuration, register either SpringDataWebConfiguration or HateoasAwareSpringDataWebConfiguration as Spring beans, as the following example shows (for SpringDataWebConfiguration):

Example 46. Enabling Spring Data web support in XML

<bean class="org.springframework.data.web.config.SpringDataWebConfiguration" />


<bean class="org.springframework.data.web.config.HateoasAwareSpringDataWebConfiguration" />
Basic Web Support

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 47. 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";
	}
}

The method receives a User instance directly, and no further lookup is necessary. The instance can be resolved by letting Spring MVC convert the path variable into the id type of the domain class first and eventually access the instance through calling findById(…) on the repository instance registered for the domain type.

在这里插入图片描述Currently, the repository has to implement CrudRepository to be eligible to be discovered for conversion.

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 48. 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:

Table1. Request parameters evaluated for Pageable instances

page Page you want to retrieve. 0-indexed and defaults to 0.
size Size of the page you want to retrieve. Defaults to 20.
sort 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:

String showUsers(Model model,
	@Qualifier("thing1") Pageable first,
	@Qualifier("thing2") Pageable second) { … }

You have to populate thing1_page, thing2_page, and so on.

The default Pageable passed into the method is equivalent to a PageRequest.of(0, 20), but you can customize it by using the @PageableDefault annotation on the Pageable parameter.

Hypermedia Support for Pageables

Spring HATEOAS ships with a representation model class (PagedResources) that allows enriching the content of a Page instance with the necessary Page metadata as well as links to let the clients easily navigate the pages. The conversion of a Page to a PagedResources is done by an implementation of the Spring HATEOAS ResourceAssembler interface, called the PagedResourcesAssembler. The following example shows how to use a PagedResourcesAssembler as a controller method argument:

Example 49. Using a PagedResourcesAssembler as controller method argument

@Controller
class PersonController {

	@Autowired PersonRepository repository;

    @RequestMapping(value = "/persons", method = RequestMethod.GET)
	HttpEntity<PagedResources<Person>> persons(Pageable pageable,
	PagedResourcesAssembler assembler) {

    	Page<Person> persons = repository.findAll(pageable);
    	return new ResponseEntity<>(assembler.toResources(persons), HttpStatus.OK);

	}
}

Enabling the configuration, as shown in the preceding example, lets the PagedResourcesAssembler be used as a controller method argument. Calling toResources(…) on it has the following effects:

The content of the Page becomes the content of the PagedResources instance.

The PagedResources object gets a PageMetadata instance attached, and it is populated with information from the Page and the underlying PageRequest.

The PagedResources 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.

Assume we have 30 Person instances in the database. You can now trigger a request (GET http://localhost:8080/persons) and see output similar to the following:

{ "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 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.toResource(…) 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

在这里插入图片描述The individual module may provide additional SpringDataJacksonModules.
Please refer to the store specific section for more details.

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 50. 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:

?firstname=Dave&lastname=Matthews

Given the User object from the previous examples, you can resolve a query string to the following value by using the QuerydslPredicateArgumentResolver, as follows:

QUser.user.firstname.eq("Dave").and(QUser.user.lastname.eq("Matthews"))

在这里插入图片描述The feature is automatically enabled, along with @EnableSpringDataWebSupport, when Querydsl is found on the classpath.

Adding a @QuerydslPredicate to the method signature provides a ready-to-use Predicate, which you can run by using the QuerydslPredicateExecutor.

在这里插入图片描述Type information is typically resolved from the method’s return type. Since that information does not necessarily match the domain type, it might be a good idea to use the root attribute of QuerydslPredicate.

The following example shows how to use @QuerydslPredicate in a method signature:

@Controller
class UserController {

	@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";

	}
}

[1] Resolve query string arguments to matching Predicate for User.
The default binding is as follows:

  • Object on simple properties as eq.

  • Object on collection like properties as contains.

  • Collection on simple properties as in.

You can customize those bindings through the bindings attribute of @QuerydslPredicate or by making use of Java 8 default methods and adding the QuerydslBinderCustomizer method to the repository interface, as follows:

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]

	}
}

[1] QuerydslPredicateExecutor provides access to specific finder methods for Predicate.
[2] QuerydslBinderCustomizer defined on the repository interface is automatically picked up and shortcuts @QuerydslPredicate(bindings=…​).
[3] Define the binding for the username property to be a simple contains binding.
[4] Define the default binding for String properties to be a case-insensitive contains match.
[5] Exclude the password property from Predicate resolution.

8.8.3. Repository Populators

If you work with the Spring JDBC module, you are probably familiar with the support for populating a DataSource with SQL scripts. A similar abstraction is available on the repositories level, although it does not use SQL as the data definition language because it must be store-independent. Thus, the populators support XML (through Spring’s OXM abstraction) and JSON (through Jackson) to define data with which to populate the repositories.

Assume you have a file called data.json with the following content:

Example 51. Data defined in JSON

[ { "_class" : "com.acme.Person",
 "firstname" : "Dave",
  "lastname" : "Matthews" },
  { "_class" : "com.acme.Person",
 "firstname" : "Carter",
  "lastname" : "Beauford" } ]

You can populate your repositories by using the populator elements of the repository namespace provided in Spring Data Commons. To populate the preceding data to your PersonRepository, declare a populator similar to the following:

Example 52. Declaring a Jackson repository populator


<beans xmlns="http://www.springframework.org/schema/beans"
	xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
	xmlns:repository="http://www.springframework.org/schema/data/repository"
	xsi:schemaLocation="http://www.springframework.org/schema/beans
	https://www.springframework.org/schema/beans/spring-beans.xsd
	http://www.springframework.org/schema/data/repository
	https://www.springframework.org/schema/data/repository/spring-repository.xsd">

	<repository:jackson2-populator locations="classpath:data.json" />

beans>

The preceding declaration causes the data.json file to be read and deserialized by a Jackson ObjectMapper.

The type to which the JSON object is unmarshalled is determined by inspecting the _class attribute of the JSON document. The infrastructure eventually selects the appropriate repository to handle the object that was deserialized.

To instead use XML to define the data the repositories should be populated with, you can use the unmarshaller-populator element. You configure it to use one of the XML marshaller options available in Spring OXM. See the Spring reference documentation for details. The following example shows how to unmarshall a repository populator with JAXB:

Example 53. Declaring an unmarshalling repository populator (using JAXB)


<beans xmlns="http://www.springframework.org/schema/beans"
	xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
	xmlns:repository="http://www.springframework.org/schema/data/repository"
	xmlns:oxm="http://www.springframework.org/schema/oxm"
	xsi:schemaLocation="http://www.springframework.org/schema/beans
		https://www.springframework.org/schema/beans/spring-beans.xsd
		http://www.springframework.org/schema/data/repository
		https://www.springframework.org/schema/data/repository/spring-repository.xsd
		http://www.springframework.org/schema/oxm
		https://www.springframework.org/schema/oxm/spring-oxm.xsd">

	<repository:unmarshaller-populator locations="classpath:data.json"
		unmarshaller-ref="unmarshaller" />

	<oxm:jaxb2-marshaller contextPath="com.acme" />

beans>

Reference Documentation

9. JDBC Repositories

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.

在这里插入图片描述In the current implementation, entities referenced from an aggregate root are deleted and recreated by Spring Data JDBC.

You can overwrite the repository methods with implementations that match your style of working and designing your database.

9.3. Getting Started

An easy way to bootstrap setting up a working environment is to create a Spring-based project in STS 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:

  1. 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.

  2. Add the following to the pom.xml files dependencies element:

<dependencies>

  

  <dependency>
    <groupId>org.springframework.datagroupId>
    <artifactId>spring-data-jdbcartifactId>
    <version>2.1.7version>
  dependency>

dependencies>
  1. Change the version of Spring in the pom.xml to be
<spring.framework.version>5.3.5spring.framework.version>
  1. 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 element:
<repositories>
  <repository>
    <id>spring-milestoneid>
    <name>Spring Maven MILESTONE Repositoryname>
    <url>https://repo.spring.io/libs-milestoneurl>
  repository>
repositories>

The repository is also browseable here.

9.4. Examples Repository

There is a GitHub repository with several examples that you can download and play around with to get a feel for how the library works.

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 54. Spring Data JDBC repositories using Java configuration

@Configuration
@EnableJdbcRepositories                                                                	//[1]
class ApplicationConfig extends AbstractJdbcConfiguration {								//[2]

    @Bean
    public 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);
    }

}

[1] @EnableJdbcRepositories creates implementations for interfaces derived from Repository
[2] AbstractJdbcConfiguration provides various default beans required by Spring Data JDBC
[3] Creates a DataSource connecting to a database.
This is required by the following two bean methods.
[4] Creates the NamedParameterJdbcOperations used by Spring Data JDBC to access the database.
[5] 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:

  1. Implement your own Dialect.

  2. Implement a JdbcDialectProvider returning the Dialect.

  3. 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=

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.

在这里插入图片描述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:

  1. Instance creation by using one of the constructors exposed.

  2. Instance population to materialize all exposed properties.

Object creation

Spring Data automatically tries to detect a persistent entity’s constructor to be used to materialize objects of that type. The resolution algorithm works as follows:

  1. If there’s a no-argument constructor, it will be used. Other constructors will be ignored.

  2. If there’s a single constructor taking arguments, it will be used.

  3. If there are multiple constructors taking arguments, the one to be used by Spring Data will have to be annotated with @PersistenceConstructor.

The value resolution assumes constructor argument names to match the property names of the entity, i.e. the resolution will be performed as if the property was to be populated, including all customizations in mapping (different datastore column or field name etc.). This also requires either parameter names information available in the class file or an @ConstructorProperties annotation being present on the constructor.

The value resolution can be customized by using Spring Framework’s @Value value annotation using a store-specific SpEL expression. Please consult the section on store specific mappings for further details.
Object creation internals

To avoid the overhead of reflection, Spring Data object creation uses a factory class generated at runtime by default, which will call the domain classes constructor directly. I.e. for this example type:

class Person {
	Person(String firstname, String lastname) { … }
}

we will create a factory class semantically equivalent to this one at runtime:

class PersonObjectInstantiator implements ObjectInstantiator {

	Object newInstance(Object... args) {
		return new Person((String) args[0], (String) args[1]);
	}
}

This gives us a roundabout 10% performance boost over reflection. For the domain class to be eligible for such optimization, it needs to adhere to a set of constraints:

  • it must not be a private class

  • it must not be a non-static inner class

  • it must not be a CGLib proxy class

  • the constructor to be used by Spring Data must not be private

If any of these criteria match, Spring Data will fall back to entity instantiation via reflection.

Property population

Once an instance of the entity has been created, Spring Data populates all remaining persistent properties of that class. Unless already populated by the entity’s constructor (i.e. consumed through its constructor argument list), the identifier property will be populated first to allow the resolution of cyclic object references. After that, all non-transient properties that have not already been populated by the constructor are set on the entity instance. For that we use the following algorithm:

  1. If the property is immutable but exposes a with… method (see below), we use the with… method to create a new entity instance with the new property value.

  2. If property access (i.e. access through getters and setters) is defined, we’re invoking the setter method.

  3. If the property is mutable we set the field directly.

  4. If the property is immutable we’re using the constructor to be used by persistence operations (see Object creation) to create a copy of the instance.

  5. By default, we set the field value directly.
Property population internals

Similarly to our optimizations in object construction we also use Spring Data runtime generated accessor classes to interact with the entity instance.

class Person {

	private final Long id;
	private String firstname;
	private @AccessType(Type.PROPERTY) String lastname;

	Person() {
		this.id = null;
	}

	Person(Long id, String firstname, String lastname) {
		// Field assignments
	}

	Person withId(Long id) {
		return new Person(id, this.firstname, this.lastame);
	}

	void setLastname(String lastname) {
	this.lastname = lastname;
	}
}

Example 55. A generated Property Accessor

class PersonPropertyAccessor implements PersistentPropertyAccessor {

private static final MethodHandle firstname;			//[2]

private Person person;									//[1]

public void setProperty(PersistentProperty property, Object value) {

    String name = property.getName();
    
    if ("firstname".equals(name)) {
      firstname.invoke(person, (String) value);       	 //[2]
    } else if ("id".equals(name)) {
      this.person = person.withId((Long) value);         //[3]
    } else if ("lastname".equals(name)) {
      this.person.setLastname((String) value);           //[4]   
    }

}
}

[1] PropertyAccessor’s hold a mutable instance of the underlying object. This is, to enable mutations of otherwise immutable properties.
[2] By default, Spring Data uses field-access to read and write property values. As per visibility rules of private fields, MethodHandles are used to interact with fields.
[3] The class exposes a withId(…) method that’s used to set the identifier, e.g. when an instance is inserted into the datastore and an identifier has been generated. Calling withId(…) creates a new Person object. All subsequent mutations will take place in the new instance leaving the previous untouched.
[4] Using property-access allows direct method invocations without using MethodHandles.

This gives us a roundabout 25% performance boost over reflection. For the domain class to be eligible for such optimization, it needs to adhere to a set of constraints:

  • Types must not reside in the default or under the java package.

  • Types and their constructors must be public

  • Types that are inner classes must be static.

  • The used Java Runtime must allow for declaring classes in the originating ClassLoader. Java 9 and newer impose certain limitations.

By default, Spring Data attempts to use generated property accessors and falls back to reflection-based ones if a limitation is detected.

Let’s have a look at the following entity:

Example 56. A sample entity

class Person {

	private final @Id Long id;                                                	//[1]
	private final String firstname, lastname;                                 	//[2]
	private final LocalDate birthday;
	private final int age;														//[3]

	private String comment;                                                   	//[4]
	private @AccessType(Type.PROPERTY) String remarks;							//[5]

	static Person of(String firstname, String lastname, LocalDate birthday) {	//[6]

    	return new Person(null, firstname, lastname, birthday,
     		 Period.between(birthday, LocalDate.now()).getYears());

	}

	Person(Long id, String firstname, String lastname, LocalDate birthday, int age) {//[6]

    	this.id = id;
    	this.firstname = firstname;
    	this.lastname = lastname;
    	this.birthday = birthday;
    	this.age = age;

	}

	Person withId(Long id) {                                                  	//[1]
		return new Person(id, this.firstname, this.lastname, this.birthday, this.age);
	}

	void setRemarks(String remarks) {                                         	//[5]
		this.remarks = remarks;
	}
}

[1] The identifier property is final but set to null in the constructor.
The class exposes a withId(…) method that’s used to set the identifier, e.g. when an instance is inserted into the datastore and an identifier has been generated.
The original Person instance stays unchanged as a new one is created.
The same pattern is usually applied for other properties that are store managed but might have to be changed for persistence operations.
The wither method is optional as the persistence constructor (see 6) is effectively a copy constructor and setting the property will be translated into creating a fresh instance with the new identifier value applied.
[2] The firstname and lastname properties are ordinary immutable properties potentially exposed through getters.
[3] The age property is an immutable but derived one from the birthday property.
With the design shown, the database value will trump the defaulting as Spring Data uses the only declared constructor.
Even if the intent is that the calculation should be preferred, it’s important that this constructor also takes age as parameter (to potentially ignore it) as otherwise the property population step will attempt to set the age field and fail due to it being immutable and no with… method being present.
[4] The comment property is mutable is populated by setting its field directly.
[5] The remarks properties are mutable and populated by setting the comment field directly or by invoking the setter method for
[6] The class exposes a factory method and a constructor for object creation.
The core idea here is to use factory methods instead of additional constructors to avoid the need for constructor disambiguation through @PersistenceConstructor.
Instead, defaulting of properties is handled within the factory method.

General recommendations
  • Try to stick to immutable objects — Immutable objects are straightforward to create as materializing an object is then a matter of calling its constructor only. Also, this avoids your domain objects to be littered with setter methods that allow client code to manipulate the objects state. If you need those, prefer to make them package protected so that they can only be invoked by a limited amount of co-located types. Constructor-only materialization is up to 30% faster than properties population.

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 is populated by setting its field directly.
The remarks properties are mutable and populated by setting the comment field directly or by invoking the setter method for
The class exposes a factory method and a constructor for object creation.
The core idea here is to use factory methods instead of additional constructors to avoid the need for constructor disambiguation through @PersistenceConstructor.
Instead, defaulting of properties is handled within the factory method.
General recommendations
Try to stick to immutable objects — Immutable objects are straightforward to create as materializing an object is then a matter of calling its constructor only. Also, this avoids your domain objects to be littered with setter methods that allow client code to manipulate the objects state. If you need those, prefer to make them package protected so that they can only be invoked by a limited amount of co-located types. Constructor-only materialization is up to 30% faster than properties population.

  • Provide an all-args constructor — Even if you cannot or don’t want to model your entities as immutable values, there’s still value in providing a constructor that takes all properties of the entity as arguments, including the mutable ones, as this allows the object mapping to skip the property population for optimal performance.

  • Use factory methods instead of overloaded constructors to avoid @PersistenceConstructor — With an all-argument constructor needed for optimal performance, we usually want to expose more application use case specific constructors that omit things like auto-generated identifiers etc. It’s an established pattern to rather use static factory methods to expose these variants of the all-args constructor.

  • Make sure you adhere to the constraints that allow the generated instantiator and property accessor classes to be used —

  • For identifiers to be generated, still use a final field in combination with an all-arguments persistence constructor (preferred) or a with… method —

  • Use Lombok to avoid boilerplate code — As persistence operations usually require a constructor taking all arguments, their declaration becomes a tedious repetition of boilerplate parameter to field assignments that can best be avoided by using Lombok’s @AllArgsConstructor.

Kotlin support

Spring Data adapts specifics of Kotlin to allow object creation and mutation.

Kotlin object creation

Kotlin classes are supported to be instantiated , all classes are immutable by default and require explicit property declarations to define mutable properties. Consider the following data class Person:

data class Person(val id: String, val name: String)

The class above compiles to a typical class with an explicit constructor.We can customize this class by adding another constructor and annotate it with @PersistenceConstructor to indicate a constructor preference:

data class Person(var id: String, val name: String) {

    @PersistenceConstructor
    constructor(id: String) : this(id, "unknown")

}

Kotlin supports parameter optionality by allowing default values to be used if a parameter is not provided. When Spring Data detects a constructor with parameter defaulting, then it leaves these parameters absent if the data store does not provide a value (or simply returns null) so Kotlin can apply parameter defaulting.Consider the following class that applies parameter defaulting for name

data class Person(var id: String, val name: String = "unknown")

Every time the name parameter is either not part of the result or its value is null, then the name defaults to unknown.

Property population of Kotlin data classes

In Kotlin, all classes are immutable by default and require explicit property declarations to define mutable properties. Consider the following data class Person:

data class Person(val id: String, val name: String)

This class is effectively immutable. It allows creating new instances as Kotlin generates a copy(…) method that creates new object instances copying all property values from the existing object and applying property values provided as arguments to the method.

9.6.2. Supported Types in Your Entity

The properties of the following types are currently supported:

  • All primitive types and their boxed types (int, float, Integer, Float, and so on)

  • Enums get mapped to their name.

  • String

  • java.util.Date, java.time.LocalDate, java.time.LocalDateTime, and java.time.LocalTime

  • 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 named the same as the table of the referencing entity. You can change this name by implementing NamingStrategy.getReverseColumnName(PersistentPropertyPathExtension path). Embedded entities do not need an id. If one is present it gets ignored.

  • Set is considered a one-to-many relationship. The table of the referenced entity is expected to have an additional column named the same as the table of the referencing entity. You can change this name by implementing NamingStrategy.getReverseColumnName(PersistentPropertyPathExtension path).

  • Map is considered a qualified one-to-many relationship. The table of the referenced entity is expected to have two additional columns: One named the same as the table of the referencing entity for the foreign key 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 is mapped as a Map.

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 should be encoded as simple id values, which should map properly with Spring Data JDBC.

9.6.3. Custom converters

Custom converters can be registered, for types that are not supported by default, by inheriting your configuration from AbstractJdbcConfiguration and overwriting the method jdbcCustomConversions().

@Configuration
public class DataJdbcConfiguration extends AbstractJdbcConfiguration {

    @Override
    public JdbcCustomConversions jdbcCustomConversions() {
    
      return new JdbcCustomConversions(Collections.singletonList(TimestampTzToDateConverter.INSTANCE));
    
    }
    
    @ReadingConverter
    enum TimestampTzToDateConverter implements Converter<TIMESTAMPTZ, Date> {
    
        INSTANCE;
    
        @Override
        public Date convert(TIMESTAMPTZ source) {
            //...
        }
    }

}

The constructor of JdbcCustomConversions accepts a list of org.springframework.core.convert.converter.Converter.

Converters should be annotated with @ReadingConverter or @WritingConverter in order to control their applicability to only reading from or to writing to the database.

TIMESTAMPTZ in the example is a database specific data type that needs conversion into something more suitable for a domain model.

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.

9.6.4. 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.

9.6.5. 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:

@Table("CUSTOM_TABLE_NAME")
public class MyEntity {
	@Id
	Integer id;

    String name;

}

9.6.6. 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:

public class MyEntity {
	@Id
	Integer id;

    @Column("CUSTOM_COLUMN_NAME")
    String name;

}

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:

public class MyEntity {
	@Id
	Integer id;

    @MappedCollection(idColumn = "CUSTOM_MY_ENTITY_ID_COLUMN_NAME")
    Set<MySubEntity> subEntities;

}

public 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:

public class MyEntity {
	@Id
	Integer id;

    @MappedCollection(idColumn = "CUSTOM_COLUMN_NAME", keyColumn = "CUSTOM_KEY_COLUMN_NAME")
    List<MySubEntity> name;

}

public class MySubEntity {
	String name;
}

9.6.7. 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 57. Sample Code of embedding objects

public class MyEntity {

    @Id
    Integer id;
    
    @Embedded(onEmpty = USE_NULL) //[1]
    EmbeddedEntity embeddedEntity;

}

public class EmbeddedEntity {
	String name;
}

[1] Null S embeddedEntity if name in null.
Use USE_EMPTY to instantiate embeddedEntity with a potential null value for the name property.
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.

在这里插入图片描述Make use of the shortcuts @Embedded.Nullable & @Embedded.Empty for @Embedded(onEmpty = USE_NULL) and @Embedded(onEmpty = USE_EMPTY) to reduce verbosity and simultaneously set JSR-305 @javax.annotation.Nonnull accordingly.

public class MyEntity {

    @Id
    Integer id;
    
    @Embedded.Nullable //[1]
    EmbeddedEntity embeddedEntity;

}

[1] Shortcut for @Embedded(onEmpty = USE_NULL).

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).

9.6.8. Entity State Detection Strategies

The following table describes the strategies that Spring Data JDBC offers for detecting whether an entity is new:

Table2.Options for detection whether an entity is new in Spring Data JDBC

Id-Property inspection (the default) By default, Spring Data JDBC inspects the identifier property of the given entity. If the identifier property is null, then the entity is assumed to be new. Otherwise, it is assumed to not be new.
Implementing Persistable If an entity implements Persistable, Spring Data JDBC delegates the new detection to the isNew(…) method of the entity. See the Javadoc for details.
Implementing EntityInformation You can customize the EntityInformation abstraction used in the SimpleJdbcRepository implementation by creating a subclass of JdbcRepositoryFactory and overriding the getEntityInformation(…) method. You then have to register the custom implementation of JdbcRepositoryFactory as a Spring bean. Note that this should rarely be necessary. See the Javadoc for details.

9.6.9. ID Generation

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 data base 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 BeforeSave listener, which sets the ID of the entity (covered later in this document).

9.6.10. 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 58. PersonRepository with query methods

interface PersonRepository extends PagingAndSortingRepository<Person, String> {

    List<Person> findByFirstname(String firstname);										//[1]

    List<Person> findByFirstnameOrderByLastname(String firstname, Pageable pageable);	//[2]

    Person findByFirstnameAndLastname(String firstname, String lastname);				//[3]

    Person findFirstByLastname(String lastname);										//[4]

    @Query("SELECT * FROM person WHERE lastname = :lastname")
    List<Person> findByLastname(String lastname);                                     	//[5]
}

[1] The method shows a query for all people with the given lastname.
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.
[2] Use Pageable to pass offset and sorting parameters to the database.
[3] Find a single entity for the given criteria.
It completes with IncorrectResultSizeDataAccessException on non-unique results.
[4] In contrast to <3>, the first entity is always emitted even if the query yields more result documents.
[5] The findByLastname method shows a query for all people with the given last name.

The following table shows the keywords that are supported for query methods:

Table 3.Supported keywords for query methods

Keyword Sample Logical result
After findByBirthdateAfter(Date date) birthdate > date
GreaterThan findByAgeGreaterThan(int age) age > age
GreaterThanEqual findByAgeGreaterThanEqual(int age) age >= age
Before findByBirthdateBefore(Date date) birthdate < date
LessThan findByAgeLessThan(int age) age < age
LessThanEqual findByAgeLessThanEqual(int age) age <= age
Between findByAgeBetween(int from, int to) age BETWEEN from AND to
NotBetween findByAgeBetween(int from, int to) age NOT BETWEEN from AND to
In findByAgeIn(Collection ages) age IN (age1, age2, ageN)
NotIn findByAgeNotIn(Collection ages) age NOT IN (age1, age2, ageN)
IsNotNull, NotNull findByFirstnameNotNull() firstname IS NOT NULL
IsNull, Null findByFirstnameNull() firstname IS NULL
Like, StartingWith, EndingWith findByFirstnameLike(String name) firstname LIKE name
NotLike, IsNotLike findByFirstnameNotLike(String name) firstname NOT LIKE name
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
Not findByFirstnameNot(String name) firstname != name
IsTrue, True findByActiveIsTrue() active IS TRUE
IsFalse, False findByActiveIsFalse() active IS FALSE

在这里插入图片描述Query derivation is limited to properties that can be used in a WHERE clause without using joins.

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 59. Declare a query method by using @Query

public 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.

在这里插入图片描述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.

在这里插入图片描述Spring Data JDBC supports only 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.

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());
}

When determining which RowMapper to use for a method, the following steps are followed, based on the return type of the method:

  1. If the type is a simple type, no RowMapper is used.

Instead, the query is expected to return a single row with a single column, and a conversion to the return type is applied to that value.

  1. 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.

If applicable, wrapper types such as collections or Optional are unwrapped. Thus, a return type of Optional uses the Person type in the preceding process.

在这里插入图片描述Using a custom RowMapper through QueryMappingConfiguration, @Query(rowMapperClass=…), or a custom ResultSetExtractor disables Entity Callbacks and Lifecycle Events as the result mapping can issue its own events/callbacks if needed.

Modifying Query

You can mark a query as being a modifying query by using the @Modifying on query method, as the following example shows:

@Modifying
@Query("UPDATE DUMMYENTITY SET name = :name WHERE id = :id")
boolean updateName(@Param("id") Long id, @Param("name") String name);

You can specify the following return types:

  • void

  • int (updated record count)

  • boolean(whether a record was updated)

9.8. 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.

9.8.1. 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
    }
}

As you can see, all you need to declare is a SqlSessionFactoryBean as MyBatisJdbcConfiguration relies on a SqlSession bean to be available in the ApplicationContext eventually.

9.8.2. 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:

Name Purpose CrudRepository methods that might trigger this statement Attributes available in the MyBatisContext
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(): ID of the referencing entity, where 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- 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- 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- 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- 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.

9.9. Lifecycle Events

Spring Data JDBC triggers events that get published to any matching ApplicationListener beans in the application context. For example, the following listener gets invoked before an aggregate gets saved:

@Bean
public ApplicationListener<BeforeSaveEvent<Object>> loggingSaves() {

	return event -> {
	
		Object entity = event.getEntity();
		LOG.info("{} is getting saved.", entity);
	};

}

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 so you don’t require further casting.

public class PersonLoadListener extends AbstractRelationalEventListener<Person> {

	@Override
	protected void onAfterLoad(AfterLoadEvent<Person> personLoad) {
		LOG.info(personLoad.getEntity());
	}

}

The following table describes the available events:

Table 4. Available events

Event When It Is Published
BeforeDeleteEvent Before an aggregate root gets deleted.
AfterDeleteEvent After an aggregate root gets deleted.
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. This is the correct event if you want to set an id programmatically.
BeforeSaveEvent Before an aggregate root gets saved (that is, inserted or updated but after the decision about whether if it gets updated or deleted was made).
AfterSaveEvent After an aggregate root gets saved (that is, inserted or updated).
AfterLoadEvent After an aggregate root gets created from a database ResultSet and all its properties get set.

在这里插入图片描述Lifecycle events depend on an ApplicationEventMulticaster, which in case of the SimpleApplicationEventMulticaster can be configured with a TaskExecutor, and therefore gives no guarantees when an Event is processed.

9.10. 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.

在这里插入图片描述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.

9.10.1. 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 60. 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]

}

[1] BeforeSaveCallback specific method to be called before an entity is saved. Returns a potentially modifed instance.
[2] The entity right before persisting.
[3] A number of store specific arguments like the collection the entity is persisted to.
Example 61. Anatomy of a reactive EntityCallback

@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]

}

[1] BeforeSaveCallback specific method to be called on subscription, before an entity is saved. Emits a potentially modifed instance.
[2] The entity right before persisting.
[3] A number of store specific arguments like the collection the entity is persisted to.

在这里插入图片描述Optional entity callback parameters are defined by the implementing Spring Data module and inferred from call site of EntityCallback.callback().

Implement the interface suiting your application needs like shown in the example below:

Example 62. Example BeforeSaveCallback

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]
	}

}

[1] Callback implementation according to your requirements.
[2] Potentially order the entity callback if multiple ones for the same domain type exist. Ordering follows lowest precedence.

9.10.2. 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 63. 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 // ...
	}

}

[1] BeforeSaveCallback receiving its order from the @Order annotation.
[2] BeforeSaveCallback receiving its order via the Ordered interface implementation.
[3] 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.
[4] Combine multiple entity callback interfaces in a single implementation class.

9.10.3. Store-specific EntityCallbacks

Spring Data JDBC uses the EntityCallback API for its auditing support and reacts on the following callbacks:

Table 5. Available Callbacks

EntityCallback When It Is Published
BeforeDeleteCallback Before an aggregate root gets deleted.
AfterDeleteCallback After an aggregate root gets deleted.
BeforeConvertCallback 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. This is the correct callback if you want to set an id programmatically.
BeforeSaveCallback Before an aggregate root gets saved (that is, inserted or updated but after the decision about whether if it gets updated or deleted was made).
AfterSaveCallback After an aggregate root gets saved (that is, inserted or updated).
AfterLoadCallback After an aggregate root gets created from a database ResultSet and all its property get set.

9.11. 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.

9.11.1. 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.

9.11.2. 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.

9.11.3. Registering Spring Converters with the JdbcConverter

class MyJdbcConfiguration extends AbstractJdbcConfiguration {

    // …
    
    @Overwrite
    @Bean
    public JdbcCustomConversions jdbcCustomConversions() {
        return new JdbcCustomConversions(Arrays.asList(new BooleanToStringConverter(), new StringToBooleanConverter()));
    }

}

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 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:

  • JSR-310 Converters for conversion between java.time, java.util.Date and String types.

  • Deprecated: Joda Time Converters for conversion between org.joda.time, JSR-310, and java.util.Date.

  • Deprecated: ThreeTenBackport Converters for conversion between org.joda.time, JSR-310, and java.util.Date.

在这里插入图片描述Default converters for local temporal types (e.g. LocalDateTime to java.util.Date) rely on system-default timezone settings to convert between those types. You can override the default converter, by registering your own converter.

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> { … }

9.12. Logging

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.

9.13. Transactionality

CRUD methods on repository 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 64. Custom transaction configuration for CRUD

public interface UserRepository extends CrudRepository<User, Long> {

	@Override
	@Transactional(timeout = 10)
	public 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 65. Using a facade to define transactions for multiple repository calls

@Service
class UserManagementImpl implements UserManagement {

	private final UserRepository userRepository;
	private final RoleRepository roleRepository;

@Autowired
public 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 or use @EnableTransactionManagement to get annotation-based configuration for facades working. Note that the preceding example assumes you use component scanning.

9.13.1. Transactional Query Methods

To let your query methods be transactional, use @Transactional at the repository interface you define, as the following example shows:

Example 66. Using @Transactional at query methods

@Transactional(readOnly = true)
public 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.

在这里插入图片描述It is definitely reasonable to use transactions for read-only queries, and we can mark them 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.

9.14. Auditing

9.14.1. 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.

在这里插入图片描述Applications that only track creation and modification dates do not need to specify an AuditorAware.

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 67. 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 capturing when changes were made can be used on properties of type Joda-Time, DateTime, legacy Java Date and Calendar, JDK8 date and time types, and long or Long.

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 snipped below.

Example 68. Audit metadata in embedded entity

class Customer {

	private AuditMetadata auditingMetadata;

	// … further properties omitted
}

class AuditMetadata {

	@CreatedBy
	private User user;

	@CreatedDate
	private Instant createdDate;

}
Interface-based Auditing Metadata

In case you do not want to use annotations to define auditing metadata, you can let your domain class implement the Auditable interface. It exposes setter methods for all of the auditing properties.

There is also a convenience base class, AbstractAuditable, which you can extend to avoid the need to manually implement the interface methods. Doing so increases the coupling of your domain classes to Spring Data, which might be something you want to avoid. Usually, the annotation-based way of defining auditing metadata is preferred as it is less invasive and more flexible.

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 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 69. 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 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 70. 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.

9.15. JDBC Auditing

In order to activate auditing, add @EnableJdbcAuditing to your configuration, as the following example shows:

Example 71. Activating auditing with Java configuration

@Configuration
@EnableJdbcAuditing
class Config {

	@Bean
	public 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.

Appendix

Appendix A: Glossary

AOP
Aspect-Oriented Programming

CRUD
Create, Read, Update, Delete - Basic persistence operations

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.

JPA
Java Persistence API

Spring
Java application framework — https://projects.spring.io/spring-framework

Appendix B: Namespace reference

The Element

The element triggers the setup of the Spring Data repository infrastructure. The most important attribute is base-package, which defines the package to scan for Spring Data repository interfaces. See “XML Configuration”. The following table describes the attributes of the element:

Table 6. Attributes

Name Description
base-package Defines the package to be scanned for repository interfaces that extend *Repository (the actual interface is determined by the specific Spring Data module) in auto-detection mode. All packages below the configured package are scanned, too. Wildcards are allowed.
repository-impl-postfix Defines the postfix to autodetect custom repository implementations. Classes whose names end with the configured postfix are considered as candidates. Defaults to Impl.
query-lookup-strategy Determines the strategy to be used to create finder queries. See “Query Lookup Strategies” for details. Defaults to create-if-not-found.
named-queries-location Defines the location to search for a Properties file containing externally defined queries.
consider-nested-repositories Whether nested repository interface definitions should be considered. Defaults to false.

Appendix C: Populators namespace reference

The element

The element allows to populate the a data store via the Spring Data repository infrastructure.

Table 7. Attributes

Name Description
locations Where to find the files to read the objects from the repository shall be populated with.

Appendix D: Repository query keywords

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 8. Query subject keywords

Keyword Description
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…, …Top… Limit the query results to the first 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 9. Query predicate keywords

Logical keyword Keyword expressions
AND And
OR Or
AFTER After, IsAfter
BEFORE Before, IsBefore
CONTAINING Containing, IsContaining, Contains
BETWEEN Between, IsBetween
ENDING_WITH EndingWith, IsEndingWith, EndsWith
EXISTS Exists
FALSE False, IsFalse
GREATER_THAN GreaterThan, IsGreaterThan
GREATER_THAN_EQUALS GreaterThanEqual, IsGreaterThanEqual
IN In, IsIn
IS Is, Equals, (or no keyword)
IS_EMPTY IsEmpty, Empty
IS_NOT_EMPTY IsNotEmpty, NotEmpty
IS_NOT_NULL NotNull, IsNotNull
IS_NULL Null, IsNull
LESS_THAN LessThan, IsLessThan
LESS_THAN_EQUAL LessThanEqual, IsLessThanEqual
LIKE Like, IsLike
NEAR Near, IsNear
NOT Not, IsNot
NOT_IN NotIn, IsNotIn
NOT_LIKE NotLike, IsNotLike
REGEX Regex, MatchesRegex, Matches
STARTING_WITH StartingWith, IsStartingWith, StartsWith
TRUE True, IsTrue
WITHIN Within, IsWithin

In addition to filter predicates, the following list of modifiers is supported:

Table 10. Query predicate modifier keywords

Keyword Description
IgnoreCase, IgnoringCase Used with a predicate keyword for case-insensitive comparison.
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).

Appendix E: Repository query return types

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.

在这里插入图片描述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.

Table 11. Query return types

Return type Description
void Denotes no return value.
Primitives Java primitives.
Wrapper types Java wrapper types.
T 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 An Iterator.
Collection A Collection.
List A List.
Optional 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 Either a Scala or Vavr Option type. Semantically the same behavior as Java 8’s Optional, described earlier.
Stream A Java 8 Stream.
Streamable 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 A Future. Expects a method to be annotated with @Async and requires Spring’s asynchronous method execution capability to be enabled.
CompletableFuture A Java 8 CompletableFuture. Expects a method to be annotated with @Async and requires Spring’s asynchronous method execution capability to be enabled.
ListenableFuture A org.springframework.util.concurrent.ListenableFuture. Expects a method to be annotated with @Async and requires Spring’s asynchronous method execution capability to be enabled.
Slice A sized chunk of data with an indication of whether there is more data available. Requires a Pageable method parameter.
Page A Slice with additional information, such as the total number of results. Requires a Pageable method parameter.
GeoResult A result entry with additional information, such as the distance to a reference location.
GeoResults A list of GeoResult with additional information, such as the average distance to a reference location.
GeoPage A Page with GeoResult, such as the average distance to a reference location.
Mono 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 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 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 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 A RxJava Flowable emitting zero, one, or many elements using reactive repositories. Queries returning Flowable can emit also an infinite number of elements.

Version 2.1.7
Last updated 2021-03-31 18:35:59 +0200

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