| 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 5.3.9 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. Page
Slice
Page
Slice
6.2. What’s New in Spring Data JDBC 2.1
- Dialect for Oracle databases.
- Support for
@Value
6.3. 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.
6.4. What’s New in Spring Data JDBC 1.1
-
@Embedded
- Store
byte[]
BINARY
- Dedicated
insert
JdbcAggregateTemplate
- Read only property support.
6.5. What’s New in Spring Data JDBC 1.0
- Basic support for
CrudRepository
-
@Query
- 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
<dependencyManagement />
section of your POM as follows:
Example 1. Using the Spring Data release train BOM
<dependencyManagement>
<dependencies>
<dependency>
<groupId>org.springframework.data</groupId>
<artifactId>spring-data-bom</artifactId>
<version>2021.0.4</version>
<scope>import</scope>
<type>pom</type>
</dependency>
</dependencies>
</dependencyManagement>
The current release train version is
2021.0.4
. 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:
-
SNAPSHOT
-
M1
M2
-
RC1
RC2
You can find a working example of using the BOMs in our Spring Data examples repository. With that in place, you can declare the Spring Data modules you would like to use without a version in the
<dependencies />
block, as follows:
Example 2. Declaring a dependency to a Spring Data module
<dependencies>
<dependency>
<groupId>org.springframework.data</groupId>
<artifactId>spring-data-jpa</artifactId>
</dependency>
<dependencies>
7.1. Dependency Management with Spring Boot
Spring Boot selects a recent version of 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 5.3.9 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.
| 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);
Optional<T> findById(ID primaryKey);
Iterable<T> findAll();
long count();
void delete(T entity);
boolean existsById(ID primaryKey);
// … more functionality omitted.
}
| Saves the given entity. |
| Returns the entity identified by the given ID. |
| Returns all entities. |
| Returns the number of entities. |
| Deletes the given entity. |
| Indicates whether an entity with the given ID exists. |
We also provide persistence technology-specific abstractions, such as |
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:
- 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> { … } - Declare query methods on the interface.
interface PersonRepository extends Repository<Person, Long> { List<Person> findByLastname(String lastname); } - Set up Spring to create proxy instances for those interfaces, either with JavaConfig or with XML configuration.
- To use Java configuration, create a class similar to the following:
import org.springframework.data.jpa.repository.config.EnableJpaRepositories; @EnableJpaRepositories class Config { … } - To use XML configuration, define a bean similar to the following:
The JPA namespace is used in this example. If you use the repository abstraction for any other store, you need to change this to the appropriate namespace declaration of your store module. In other words, you should exchange<?xml version="1.0" encoding="UTF-8"?> <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>jpa
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…
@Enable${store}Repositories
- To use Java configuration, create a class similar to the following:
- 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.
| 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.
The intermediate repository interface is annotated with |
8.3.2. Using Repositories with Multiple Spring Data Modules
Using a unique Spring Data module in your application makes things simple, because all repository interfaces in the defined scope are bound to the Spring Data module. Sometimes, applications require using more than one Spring Data module. In such cases, a repository definition must distinguish between persistence technologies. When it detects multiple repository factories on the class path, Spring Data enters strict repository configuration mode. Strict configuration uses details on the repository or the domain class to decide about Spring Data module binding for a repository definition:
- If the repository definition extends the module-specific repository, it is a valid candidate for the particular Spring Data module.
- If the domain class is annotated with the module-specific type annotation, it is a valid candidate for the particular Spring Data module. Spring Data modules accept either third-party annotations (such as JPA’s
@Entity
@Document
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
-
USE_DECLARED_QUERY
-
CREATE_IF_NOT_FOUND
CREATE
USE_DECLARED_QUERY
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
OR
Between
LessThan
GreaterThan
Like
- The method parser supports setting an
IgnoreCase
findByLastnameIgnoreCase(…)
String
findByLastnameAndFirstnameAllIgnoreCase(…)
- You can apply static ordering by appending an
OrderBy
Asc
Desc
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);
APIs taking |
The first method lets you pass an
org.springframework.data.domain.Pageable
instance to the query method to dynamically add paging to your statically defined query. A
Page
knows about the total number of elements and pages available. It does so by the infrastructure triggering a count query to calculate the overall number. As this might be expensive (depending on the store used), you can instead return a
Slice
. A
Slice
knows only about whether a next
Slice
is available, which might be sufficient when walking through a larger result set.
Sorting options are handled through the
Pageable
instance, too. If you need only sorting, add an
org.springframework.data.domain.Sort
parameter to your method. As you can see, returning a
List
is also possible. In this case, the additional metadata required to build the actual
Page
instance is not created (which, in turn, means that the additional count query that would have been necessary is not issued). Rather, it restricts the query to look up only the given range of entities.
| To find out how many pages you get for an entire query, you have to trigger an additional count query. By default, this query is derived from the query you actually trigger. |
Paging and Sorting
You can define simple sorting expressions by using property names. You can concatenate expressions to collect multiple criteria into one expression.
Example 15. Defining sort expressions
Sort sort = Sort.by("firstname").ascending()
.and(Sort.by("lastname").descending());
For a more type-safe way to define sort expressions, start with the type for which to define the sort expression and use method references to define the properties on which to sort.
Example 16. Defining sort expressions by using the type-safe API
TypedSort<Person> person = Sort.sort(Person.class);
Sort sort = person.by(Person::getFirstname).ascending()
.and(person.by(Person::getLastname).descending());
|
If your store implementation supports Querydsl, you can also use the generated metamodel types to define sort expressions:
Example 17. Defining sort expressions by using the Querydsl API
QSort sort = QSort.by(QPerson.firstname.asc())
.and(QSort.by(QPerson.lastname.desc()));
8.4.5. Limiting Query Results
You can limit the results of query methods by using the
first
or
top
keywords, which you can use interchangeably. You can append an optional numeric value to
top
or
first
to specify the maximum result size to be returned. If the number is left out, a result size of 1 is assumed. The following example shows how to limit the query size:
Example 18. Limiting the result size of a query with
Top
and
First
User findFirstByOrderByLastnameAsc();
User findTopByOrderByAgeDesc();
Page<User> queryFirst10ByLastname(String lastname, Pageable pageable);
Slice<User> findTop3ByLastname(String lastname, Pageable pageable);
List<User> findFirst10ByLastname(String lastname, Sort sort);
List<User> findTop10ByLastname(String lastname, Pageable pageable);
The limiting expressions also support the
Distinct
keyword for datastores that support distinct queries. Also, for the queries that limit the result set to one instance, wrapping the result into with the
Optional
keyword is supported.
If pagination or slicing is applied to a limiting query pagination (and the calculation of the number of available pages), it is applied within the limited result.
Limiting the results in combination with dynamic sorting by using a |
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:
- The type implements
Streamable
- The type exposes either a constructor or a static factory method named
of(…)
valueOf(…)
Streamable
The following listing shows an example:
class Product {
MonetaryAmount getPrice() { … }
}
@RequiredArgsConstructor(staticName = "of")
class Products implements Streamable<Product> {
private final Streamable<Product> streamable;
public MonetaryAmount getTotal() {
return streamable.stream()
.map(Priced::getPrice)
.reduce(Money.of(0), MonetaryAmount::add);
}
@Override
public Iterator<Product> iterator() {
return streamable.iterator();
}
}
interface ProductRepository implements Repository<Product, Long> {
Products findAllByDescriptionContaining(String text);
}
A |
A wrapper type for a |
The wrapper type exposes an additional API, calculating new values on the |
Implement the |
That wrapper type |
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 |
|---|---|---|
| | |
| | |
| | |
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
null
-
@NonNull
null
@NonNullApi
-
@Nullable
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;
import org.springframework.lang.Nullable;
interface UserRepository extends Repository<User, Long> {
User getByEmailAddress(EmailAddress emailAddress);
@Nullable
User findByEmailAddress(@Nullable EmailAddress emailAdress);
Optional<User> findOptionalByEmailAddress(EmailAddress emailAddress);
}
| The repository resides in a package (or sub-package) for which we have defined non-null behavior. |
Throws an |
Returns |
Returns |
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
fun findByFirstname(firstname: String?): User?
}
The method defines both the parameter and the result as non-nullable (the Kotlin default). The Kotlin compiler rejects method invocations that pass |
This method accepts |
8.4.8. Streaming Query Results
You can process the results of query methods incrementally by using a Java 8
Stream<T>
as the return type. Instead of wrapping the query results in a
Stream
, data store-specific methods are used to perform the streaming, as shown in the following example:
Example 23. Stream the result of a query with Java 8
Stream<T>
@Query("select u from User u")
Stream<User> findAllByCustomQueryAndStream();
Stream<User> readAllByFirstnameNotNull();
@Query("select u from User u")
Stream<User> streamAllPaged(Pageable pageable);
A |
Example 24. Working with a
Stream<T>
result in a
try-with-resources
block
try (Stream<User> stream = repository.findAllByCustomQueryAndStream()) {
stream.forEach(…);
}
Not all Spring Data modules currently support |
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);
@Async
CompletableFuture<User> findOneByFirstname(String firstname);
@Async
ListenableFuture<User> findOneByLastname(String lastname);
Use |
Use a Java 8 |
Use a |
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
<?xml version="1.0" encoding="UTF-8"?>
<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
<include-filter />
and
<exclude-filter />
elements inside the
<repositories />
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() {
// …
}
}
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 |
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
Spring Data provides various options to create query methods with little coding. But when those options don’t fit your needs you can also provide your own custom implementation for repository methods. This section describes how to do that.
8.6.1. Customizing Individual Repositories
To enrich a repository with custom functionality, you must first define a fragment interface and an implementation for the custom functionality, as follows:
Example 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
}
}
The most important part of the class name that corresponds to the fragment interface is the |
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="…">
<!-- further configuration -->
</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
}
}
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 |
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
Collection<Object> domainEvents() {
// … return events you want to get published here
}
@AfterDomainEventPublication
void callbackMethod() {
// … potentially clean up domain events list
}
}
The method that uses |
After all events have been published, we have a method annotated with |
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);
Iterable<T> findAll(Predicate predicate);
long count(Predicate predicate);
boolean exists(Predicate predicate);
// … more functionality omitted.
}
Finds and returns a single entity matching the |
Finds and returns all entities matching the |
Returns the number of entities matching the |
Returns whether an entity that matches the |
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" />
<!-- If you use Spring HATEOAS, register this one *instead* of the former -->
<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
-
HandlerMethodArgumentResolver
Pageable
Sort
- Jackson Modules to de-/serialize types like
Point
Distance
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.
Currently, the repository has to implement |
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:
| Page you want to retrieve. 0-indexed and defaults to 0. |
| Size of the page you want to retrieve. Defaults to 20. |
| Properties that should be sorted by in the format |
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
PagedResources
- The
PagedResources
PageMetadata
Page
PageRequest
- The
PagedResources
prev
next
PageableHandlerMethodArgumentResolver
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.Module
s 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 The individual module may provide additional . 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"))
The feature is automatically enabled, along with |
Adding a
@QuerydslPredicate
to the method signature provides a ready-to-use
Predicate
, which you can run by using the
QuerydslPredicateExecutor
.
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 |
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,
Pageable pageable, @RequestParam MultiValueMap<String, String> parameters) {
model.addAttribute("users", repository.findAll(predicate, pageable));
return "index";
}
}
Resolve query string arguments to matching |
The default binding is as follows:
-
Object
eq
-
Object
contains
-
Collection
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>,
QuerydslBinderCustomizer<QUser> {
@Override
default void customize(QuerydslBindings bindings, QUser user) {
bindings.bind(user.username).first((path, value) -> path.contains(value))
bindings.bind(String.class)
.first((StringPath path, String value) -> path.containsIgnoreCase(value));
bindings.excluding(user.password);
}
}
|
|
Define the binding for the |
Define the default binding for |
Exclude the |
You can register a |
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
<?xml version="1.0" encoding="UTF-8"?>
<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)
<?xml version="1.0" encoding="UTF-8"?>
<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.
| 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:
- Go to File → New → Spring Template Project → Simple Spring Utility Project, and press Yes when prompted. Then enter a project and a package name, such as
org.spring.jdbc.example
- Add the following to the
pom.xml
dependencies
<dependencies> <!-- other dependency elements omitted --> <dependency> <groupId>org.springframework.data</groupId> <artifactId>spring-data-jdbc</artifactId> <version>2.2.4</version> </dependency> </dependencies> - Change the version of Spring in the pom.xml to be
<spring.framework.version>5.3.9</spring.framework.version> - Add the following location of the Spring Milestone repository for Maven to your
pom.xml
<dependencies/>
<repositories> <repository> <id>spring-milestone</id> <name>Spring Maven MILESTONE Repository</name> <url>https://repo.spring.io/libs-milestone</url> </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
class ApplicationConfig extends AbstractJdbcConfiguration {
@Bean
public DataSource dataSource() {
EmbeddedDatabaseBuilder builder = new EmbeddedDatabaseBuilder();
return builder.setType(EmbeddedDatabaseType.HSQL).build();
}
@Bean
NamedParameterJdbcOperations namedParameterJdbcOperations(DataSource dataSource) {
return new NamedParameterJdbcTemplate(dataSource);
}
@Bean
TransactionManager transactionManager(DataSource dataSource) {
return new DataSourceTransactionManager(dataSource);
}
}
|
|
Creates a |
Creates the |
| 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:
- Implement your own
Dialect
- Implement a
JdbcDialectProvider
Dialect
- Register the provider by creating a
spring.factories
META-INF
org.springframework.data.jdbc.repository.config.DialectResolver$JdbcDialectProvider=<fully qualified name of your JdbcDialectProvider>
9.6. Persisting Entities
Saving an aggregate can be performed with the
CrudRepository.save(…)
method. If the aggregate is new, this results in an insert for the aggregate root, followed by insert statements for all directly or indirectly referenced entities.
If the aggregate root is not new, all referenced entities get deleted, the aggregate root gets updated, and all referenced entities get inserted again. Note that whether an instance is new is part of the instance’s state.
| This approach has some obvious downsides. If only few of the referenced entities have been actually changed, the deletion and insertion is wasteful. While this process could and probably will be improved, there are certain limitations to what Spring Data JDBC can offer. It does not know the previous state of an aggregate. So any update process always has to take whatever it finds in the database and make sure it converts it to whatever is the state of the entity passed to the save method. |
9.6.1. Object Mapping Fundamentals
This section covers the fundamentals of Spring Data object mapping, object creation, field and property access, mutability and immutability. Note, that this section only applies to Spring Data modules that do not use the object mapping of the underlying data store (like JPA). Also be sure to consult the store-specific sections for store-specific object mapping, like indexes, customizing column or field names or the like.
Core responsibility of the Spring Data object mapping is to create instances of domain objects and map the store-native data structures onto those. This means we need two fundamental steps:
- Instance creation by using one of the constructors exposed.
- Instance population to materialize all exposed properties.
Object creation
Spring Data automatically tries to detect a persistent entity’s constructor to be used to materialize objects of that type. The resolution algorithm works as follows:
- If there is a single constructor, it is used.
- If there are multiple constructors and exactly one is annotated with
@PersistenceConstructor
- If there’s a no-argument constructor, it is used. Other constructors will be ignored.
The value resolution assumes constructor argument names to match the property names of the entity, i.e. the resolution will be performed as if the property was to be populated, including all customizations in mapping (different datastore column or field name etc.). This also requires either parameter names information available in the class file or an
@ConstructorProperties
annotation being present on the constructor.
The value resolution can be customized by using Spring Framework’s
@Value
value annotation using a store-specific SpEL expression. Please consult the section on store specific mappings for further details.
Object creation internals
To avoid the overhead of reflection, Spring Data object creation uses a factory class generated at runtime by default, which will call the domain classes constructor directly. I.e. for this example type:
class Person {
Person(String firstname, String lastname) { … }
}
we will create a factory class semantically equivalent to this one at runtime:
class PersonObjectInstantiator implements ObjectInstantiator {
Object newInstance(Object... args) {
return new Person((String) args[0], (String) args[1]);
}
}
This gives us a roundabout 10% performance boost over reflection. For the domain class to be eligible for such optimization, it needs to adhere to a set of constraints:
- it must not be a private class
- it must not be a non-static inner class
- it must not be a CGLib proxy class
- the constructor to be used by Spring Data must not be private
If any of these criteria match, Spring Data will fall back to entity instantiation via reflection.
Property population
Once an instance of the entity has been created, Spring Data populates all remaining persistent properties of that class. Unless already populated by the entity’s constructor (i.e. consumed through its constructor argument list), the identifier property will be populated first to allow the resolution of cyclic object references. After that, all non-transient properties that have not already been populated by the constructor are set on the entity instance. For that we use the following algorithm:
- If the property is immutable but exposes a
with…
with…
- If property access (i.e. access through getters and setters) is defined, we’re invoking the setter method.
- If the property is mutable we set the field directly.
- If the property is immutable we’re using the constructor to be used by persistence operations (see Object creation) to create a copy of the instance.
- By default, we set the field value directly.
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;
private Person person;
public void setProperty(PersistentProperty property, Object value) {
String name = property.getName();
if ("firstname".equals(name)) {
firstname.invoke(person, (String) value);
} else if ("id".equals(name)) {
this.person = person.withId((Long) value);
} else if ("lastname".equals(name)) {
this.person.setLastname((String) value);
}
}
}
| PropertyAccessor’s hold a mutable instance of the underlying object. This is, to enable mutations of otherwise immutable properties. |
By default, Spring Data uses field-access to read and write property values. As per visibility rules of |
The class exposes a |
Using property-access allows direct method invocations without using |
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
- 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
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;
private final String firstname, lastname;
private final LocalDate birthday;
private final int age;
private String comment;
private @AccessType(Type.PROPERTY) String remarks;
static Person of(String firstname, String lastname, LocalDate birthday) {
return new Person(null, firstname, lastname, birthday,
Period.between(birthday, LocalDate.now()).getYears());
}
Person(Long id, String firstname, String lastname, LocalDate birthday, int age) {
this.id = id;
this.firstname = firstname;
this.lastname = lastname;
this.birthday = birthday;
this.age = age;
}
Person withId(Long id) {
return new Person(id, this.firstname, this.lastname, this.birthday, this.age);
}
void setRemarks(String remarks) {
this.remarks = remarks;
}
}
The identifier property is final but set to |
The |
The |
The |
The |
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 |
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
- 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…
- 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
- Enums get mapped to their name.
-
String
-
java.util.Date
java.time.LocalDate
java.time.LocalDateTime
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
NamingStrategy.getReverseColumnName(PersistentPropertyPathExtension path)
id
-
Set<some entity>
NamingStrategy.getReverseColumnName(PersistentPropertyPathExtension path)
-
Map<simple type, some entity>
_key
NamingStrategy.getReverseColumnName(PersistentPropertyPathExtension path)
NamingStrategy.getKeyColumn(RelationalPersistentProperty property)
@MappedCollection(idColumn="your_column_name", keyColumn="your_key_column_name")
-
List<some entity>
Map<Integer, some entity>
The handling of referenced entities is limited. This is based on the idea of aggregate roots as described above. If you reference another entity, that entity is, by definition, part of your aggregate. So, if you remove the reference, the previously referenced entity gets deleted. This also means references are 1-1 or 1-n, but not n-1 or n-m.
If you have n-1 or n-m references, you are, by definition, dealing with two separate aggregates. References between those 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
null
s 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)
EmbeddedEntity embeddedEntity;
}
public class EmbeddedEntity {
String name;
}
|
If you need a value object multiple times in an entity, this can be achieved with the optional
prefix
element of the
@Embedded
annotation. This element represents a prefix and is prepend for each column name in the embedded object.
Make use of the shortcuts
|
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 offers for detecting whether an entity is new:
| By default, Spring Data inspects the version property of the given entity. If the identifier property is |
| If a property annotated with |
Implementing | If an entity implements method of the entity. See the Javadoc for details. Note: Properties of |
Providing a custom | You can customize the |
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
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);
List<Person> findByFirstnameOrderByLastname(String firstname, Pageable pageable);
Slice<Person> findByLastname(String lastname, Pageable pageable);
Page<Person> findByLastname(String lastname, Pageable pageable);
Person findByFirstnameAndLastname(String firstname, String lastname);
Person findFirstByLastname(String lastname);
@Query("SELECT * FROM person WHERE lastname = :lastname")
List<Person> findByLastname(String lastname);
}
The method shows a query for all people with the given |
Use |
Return a |
Run a paginated query returning |
Find a single entity for the given criteria. It completes with |
| In contrast to <3>, the first entity is always emitted even if the query yields more result documents. |
The |
The following table shows the keywords that are supported for query methods:
| Keyword | Sample | Logical result |
|---|---|---|
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
Query derivation is limited to properties that can be used in a |
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.
Spring fully supports Java 8’s parameter name discovery based on the |
| 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:
- 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.
- The entity classes in the
QueryMappingConfiguration
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<Person>
uses the
Person
type in the preceding process.
Using a custom |
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
-
boolean
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 |
|---|---|---|---|
| Inserts a single entity. This also applies for entities referenced by the aggregate root. | | |
| Updates a single entity. This also applies for entities referenced by the aggregate root. | | |
| Deletes a single entity. | | |
| 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. | | |
| Deletes all aggregate roots of the type used as the prefix | | |
| Deletes all entities referenced by an aggregate root with the given propertyPath | | |
| Selects an aggregate root by ID | | |
| Select all aggregate roots | | |
| Select a set of aggregate roots by ID values | | |
| 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 | All | |
| Select a set of entities that is referenced by another entity via a property path. | All | |
| Select all aggregate roots, sorted | | |
| Select a page of aggregate roots, optionally sorted | | |
| Count the number of aggregate root of the type used as prefix | | |
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:
| Event | When It Is Published |
|---|---|
| Before an aggregate root gets deleted. |
| After an aggregate root gets deleted. |
| 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. |
| 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). |
| After an aggregate root gets saved (that is, inserted or updated). |
| After an aggregate root gets created from a database |
Lifecycle events depend on an |
9.9.1. Store-specific EntityCallbacks
Spring Data JDBC uses the
EntityCallback
API for its auditing support and reacts on the following callbacks:
| When It Is Published |
|---|---|
| Before an aggregate root gets deleted. |
| After an aggregate root gets deleted. |
| 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. |
| 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). |
| After an aggregate root gets saved (that is, inserted or updated). |
| After an aggregate root gets created from a database |
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.
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 |
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>);
}
|
| The entity right before persisting. |
| 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>);
}
|
| The entity right before persisting. |
| A number of store specific arguments like the collection the entity is persisted to. |
Optional entity callback parameters are defined by the implementing Spring Data module and inferred from call site of |
Implement the interface suiting your application needs like shown in the example below:
Example 62. Example
BeforeSaveCallback
class DefaultingEntityCallback implements BeforeSaveCallback<Person>, Ordered {
@Override
public Object onBeforeSave(Person entity, String collection) {
if(collection == "user") {
return // ...
}
return // ...
}
@Override
public int getOrder() {
return 100;
}
}
| Callback implementation according to your requirements. |
| 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)
@Component
class First implements BeforeSaveCallback<Person> {
@Override
public Person onBeforeSave(Person person) {
return // ...
}
}
@Component
class DefaultingEntityCallback implements BeforeSaveCallback<Person>,
Ordered {
@Override
public Object onBeforeSave(Person entity, String collection) {
// ...
}
@Override
public int getOrder() {
return 100;
}
}
@Configuration
public class EntityCallbackConfiguration {
@Bean
BeforeSaveCallback<Person> unorderedLambdaReceiverCallback() {
return (BeforeSaveCallback<Person>) it -> // ...
}
}
@Component
class UserCallbacks implements BeforeConvertCallback<User>,
BeforeSaveCallback<User> {
@Override
public Person onBeforeConvert(User user) {
return // ...
}
@Override
public Person onBeforeSave(User user) {
return // ...
}
}
|
|
|
| Combine multiple entity callback interfaces in a single implementation class. |
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<String, Long>
is ambiguous, although it probably does not make sense to try to convert all
String
instances into
Long
instances when writing. To let you force the infrastructure to register a converter for only one way, we provide
@ReadingConverter
and
@WritingConverter
annotations to be used in the converter implementation.
Converters are subject to explicit registration as instances are not picked up from a classpath or container scan to avoid unwanted registration with a conversion service and the side effects resulting from such a registration. Converters are registered with
CustomConversions
as the central facility that allows registration and querying for registered converters based on source- and target type.
CustomConversions
ships with a pre-defined set of converter registrations:
- JSR-310 Converters for conversion between
java.time
java.util.Date
String
- Deprecated: Joda Time Converters for conversion between
org.joda.time
java.util.Date
- Deprecated: ThreeTenBackport Converters for conversion between
org.joda.time
java.util.Date
Default converters for local temporal types (e.g. |
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
<tx:annotation-driven />
or use
@EnableTransactionManagement
to get annotation-based configuration for facades working. Note that the preceding example assumes you use component scanning.
9.13.1. 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
.
It is definitely reasonable to use transactions for read-only queries, and we can mark them as such by setting the |
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.
Applications that only track creation and modification dates do not need to specify an |
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<T>
SPI interface that you have to implement to tell the infrastructure who the current user or system interacting with the application is. The generic type
T
defines what type the properties annotated with
@CreatedBy
or
@LastModifiedBy
have to be.
The following example shows an implementation of the interface that uses Spring Security’s
Authentication
object:
Example 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<T>
SPI interface that you have to implement to tell the infrastructure who the current user or system interacting with the application is. The generic type
T
defines what type the properties annotated with
@CreatedBy
or
@LastModifiedBy
have to be.
The following example shows an implementation of the interface that uses reactive Spring Security’s
Authentication
object:
Example 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 <repositories />
<repositories />
The
<repositories />
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
<repositories />
element:
| Name | Description |
|---|---|
| Defines the package to be scanned for repository interfaces that extend |
| Defines the postfix to autodetect custom repository implementations. Classes whose names end with the configured postfix are considered as candidates. Defaults to |
| Determines the strategy to be used to create finder queries. See “Query Lookup Strategies” for details. Defaults to |
| Defines the location to search for a Properties file containing externally defined queries. |
| Whether nested repository interface definitions should be considered. Defaults to |
Appendix C: Populators namespace reference
The <populator /> element
The
<populator />
element allows to populate the a data store via the Spring Data repository infrastructure.[1]
| Name | Description |
|---|---|
| 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.
| Keyword | Description |
|---|---|
| General query method returning typically the repository type, a |
| Exists projection, returning typically a |
| Count projection returning a numeric result. |
| Delete query method returning either no result ( |
| Limit the query results to the first |
| 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 |
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.
| Logical keyword | Keyword expressions |
|---|---|
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
In addition to filter predicates, the following list of modifiers is supported:
| Keyword | Description |
|---|---|
| Used with a predicate keyword for case-insensitive comparison. |
| Ignore case for all suitable properties. Used somewhere in the query method predicate. |
| Specify a static sorting order followed by the property path and direction (e. g. |
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.
Geospatial types (such as |
| Return type | Description |
|---|---|
| Denotes no return value. |
| Primitives | Java primitives. |
| Wrapper types | Java wrapper types. |
| A unique entity. Expects the query method to return one result at most. If no result is found, |
| An |
| A |
| A |
| A Java 8 or Guava |
| Either a Scala or Vavr |
| A Java 8 |
| A convenience extension of |
Types that implement | Types that expose a constructor or |
Vavr | Vavr collection types. See Support for Vavr Collections for details. |
| A |
| A Java 8 |
| A |
| A sized chunk of data with an indication of whether there is more data available. Requires a |
| A |
| A result entry with additional information, such as the distance to a reference location. |
| A list of |
| A |
| A Project Reactor |
| A Project Reactor |
| A RxJava |
| A RxJava |
| A RxJava |
1. see XML Configuration
Version 2.2.4
Last updated 2021-08-12 11:42:18 +0200
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