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Table of Contents

Preface

The Spring Data MongoDB project applies core Spring concepts to the development of solutions using the MongoDB document style data store. We provide a "template" as a high-level abstraction for storing and querying documents. You will notice similarities to the JDBC support in the Spring Framework.

This document is the reference guide for Spring Data - Document Support. It explains Document module concepts and semantics and the syntax for various store namespaces.

This section provides some basic introduction to Spring and Document database. The rest of the document refers only to Spring Data Document features and assumes the user is familiar with document databases such as MongoDB and CouchDB as well as Spring concepts.

1. Knowing Spring

Spring Data uses Spring framework’s core functionality, such as the IoC container, type conversion system, expression language, JMX integration, and portable DAO exception hierarchy. While it is not important to know the Spring APIs, understanding the concepts behind them is. At a minimum, the idea behind IoC should be familiar for whatever IoC container you choose to use.

The core functionality of the MongoDB and CouchDB 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 document, such as the repository support, you will need to configure some parts of the library using Spring.

To learn more about Spring, you can refer to the comprehensive (and sometimes disarming) documentation that explains in detail the Spring Framework. There are a lot of articles, blog entries and books on the matter - take a look at the Spring framework home page for more information.

2. Knowing NoSQL and Document databases

NoSQL stores have taken the storage world by storm. It is a vast domain with a plethora of solutions, terms and patterns (to make things worse even the term itself has multiple meanings). While some of the principles are common, it is crucial that the user is familiar to some degree with the stores supported by DATADOC. The best way to get acquainted to this solutions is to read their documentation and follow their examples - it usually doesn’t take more then 5-10 minutes to go through them and if you are coming from an RDMBS-only background many times these exercises can be an eye opener.

The jumping off ground for learning about MongoDB is www.mongodb.org. Here is a list of other useful resources:

3. Requirements

Spring Data MongoDB 1.x binaries requires JDK level 6.0 and above, and Spring Framework 4.2.8.RELEASE and above.

In terms of document stores, MongoDB at least 2.6.

4. Additional Help Resources

Learning a new framework is not always straight forward. In this section, we try to provide what we think is an easy to follow guide for starting with Spring Data Document module. However, if you encounter issues or you are just looking for an advice, feel free to use one of the links below:

4.1. Support

There are a few support options available:

4.1.1. Community Forum

Spring Data on Stackoverflow Stackoverflow 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.

4.1.2. Professional Support

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

4.2. Following Development

For information on the Spring Data Mongo source code repository, nightly builds and snapshot artifacts please see the Spring Data Mongo homepage. You can help make Spring Data best serve the needs of the Spring community by interacting with developers through the Community on Stackoverflow. To follow developer activity look for the mailing list information on the Spring Data Mongo homepage. 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. Lastly, you can follow the Spring blog or the project team on Twitter (SpringData).

5. New & Noteworthy

5.1. What’s new in Spring Data MongoDB 1.9

  • The following annotations have been enabled to build own, composed annotations: @Document, @Id, @Field, @Indexed, @CompoundIndex, @GeoSpatialIndexed, @TextIndexed, @Query, @Meta.

  • Support for Projections in repository query methods.

  • Support for Query by Example.

  • Out-of-the-box support for java.util.Currency in object mapping.

  • Add support for the bulk operations introduced in MongoDB 2.6.

  • Upgrade to Querydsl 4.

  • Assert compatibility with MongoDB 3.0 and MongoDB Java Driver 3.2 (see: MongoDB 3.0 Support).

5.2. What’s new in Spring Data MongoDB 1.8

  • Criteria offers support for creating $geoIntersects.

  • Support SpEL expressions in @Query.

  • MongoMappingEvents expose the collection name they are issued for.

  • Improved support for <mongo:mongo-client credentials="…​" />.

  • Improved index creation failure error message.

5.3. What’s new in Spring Data MongoDB 1.7

  • Assert compatibility with MongoDB 3.0 and MongoDB Java Driver 3-beta3 (see: MongoDB 3.0 Support).

  • Support JSR-310 and ThreeTen back-port date/time types.

  • Allow Stream as query method return type (see: Query methods).

  • Added GeoJSON support in both domain types and queries (see: GeoJSON Support).

  • QueryDslPredicateExcecutor now supports findAll(OrderSpecifier<?>… orders).

  • Support calling JavaScript functions via Script Operations.

  • Improve support for CONTAINS keyword on collection like properties.

  • Support for $bit, $mul and $position operators to Update.

6. Dependencies

Due to 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 by relying on the Spring Data Release Train BOM we ship with the compatible versions defined. In a Maven project you’d declare this dependency in the <dependencyManagement /> section of your POM:

Example 1. Using the Spring Data release train BOM
<dependencyManagement>
  <dependencies>
    <dependency>
      <groupId>org.springframework.data</groupId>
      <artifactId>spring-data-releasetrain</artifactId>
      <version>${release-train}</version>
      <scope>import</scope>
      <type>pom</type>
    </dependency>
  </dependencies>
</dependencyManagement>

The current release train version is Hopper-SR5. The train names are ascending alphabetically and currently available ones are listed here. The version name follows the following pattern: ${name}-${release} where release can be one of the following:

  • BUILD-SNAPSHOT - current snapshots

  • M1, M2 etc. - milestones

  • RC1, RC2 etc. - release candidates

  • RELEASE - GA release

  • SR1, SR2 etc. - service releases

A working example of using the BOMs can be found in our Spring Data examples repository. If that’s in place declare the Spring Data modules you’d like to use without a version in the <dependencies /> block.

Example 2. Declaring a dependency to a Spring Data module
<dependencies>
  <dependency>
    <groupId>org.springframework.data</groupId>
    <artifactId>spring-data-jpa</artifactId>
  </dependency>
<dependencies>

6.1. Dependency management with Spring Boot

Spring Boot already selects a very recent version of Spring Data modules for you. In case you want to upgrade to a newer version nonetheless, simply configure the property spring-data-releasetrain.version to the train name and iteration you’d like to use.

6.2. Spring Framework

The current version of Spring Data modules require Spring Framework in version 4.2.8.RELEASE 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.

7. Working with Spring Data Repositories

The goal of 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. Adapt the XML namespace declaration and the types to be extended to the equivalents of the particular module that you are using. Namespace reference covers XML configuration which is supported across all Spring Data modules supporting 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, consult the chapter on that module of this document.

7.1. Core concepts

The central interface in Spring Data repository abstraction is Repository (probably not that much of a surprise). 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 provides sophisticated CRUD functionality for the entity class that is being managed.

Example 3. CrudRepository interface
public interface CrudRepository<T, ID extends Serializable>
    extends Repository<T, ID> {

    <S extends T> S save(S entity); (1)

    T findOne(ID primaryKey);       (2)

    Iterable<T> findAll();          (3)

    Long count();                   (4)

    void delete(T entity);          (5)

    boolean exists(ID primaryKey);  (6)

    // … more functionality omitted.
}
1 Saves the given entity.
2 Returns the entity identified by the given id.
3 Returns all entities.
4 Returns the number of entities.
5 Deletes the given entity.
6 Indicates whether an entity with the given id exists.
We also provide persistence technology-specific abstractions like e.g. JpaRepository or MongoRepository. Those interfaces extend CrudRepository and expose the capabilities of the underlying persistence technology in addition to the rather generic persistence technology-agnostic interfaces like e.g. CrudRepository.

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

Example 4. PagingAndSortingRepository
public interface PagingAndSortingRepository<T, ID extends Serializable>
  extends CrudRepository<T, ID> {

  Iterable<T> findAll(Sort sort);

  Page<T> findAll(Pageable pageable);
}

Accessing the second page of User by a page size of 20 you could simply do something like this:

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

In addition to query methods, query derivation for both count and delete queries, is available.

Example 5. Derived Count Query
public interface UserRepository extends CrudRepository<User, Long> {

  Long countByLastname(String lastname);
}
Example 6. Derived Delete Query
public interface UserRepository extends CrudRepository<User, Long> {

  Long deleteByLastname(String lastname);

  List<User> removeByLastname(String lastname);

}

7.2. Query methods

Standard CRUD functionality repositories usually have queries on the underlying datastore. With Spring Data, declaring those queries becomes a four-step process:

  1. Declare an interface extending Repository or one of its subinterfaces and type it to the domain class and ID type that it will handle.

    interface PersonRepository extends Repository<Person, Long> { … }
  2. Declare query methods on the interface.

    interface PersonRepository extends Repository<Person, Long> {
      List<Person> findByLastname(String lastname);
    }
  3. Set up Spring to create proxy instances for those interfaces. Either via JavaConfig:

    import org.springframework.data.jpa.repository.config.EnableJpaRepositories;
    
    @EnableJpaRepositories
    class Config {}
    <?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
         http://www.springframework.org/schema/beans/spring-beans.xsd
         http://www.springframework.org/schema/data/jpa
         http://www.springframework.org/schema/data/jpa/spring-jpa.xsd">
    
       <jpa:repositories base-package="com.acme.repositories"/>
    
    </beans>

    The JPA namespace is used in this example. If you are using the repository abstraction for any other store, you need to change this to the appropriate namespace declaration of your store module which should be exchanging jpa in favor of, for example, mongodb.

    Also, note that the JavaConfig variant doesn’t configure a package explictly as the package of the annotated class is used by default. To customize the package to scan use one of the basePackage… attribute of the data-store specific repository @Enable…-annotation.

  4. Get the repository instance injected and use it.

    public class SomeClient {
    
      @Autowired
      private PersonRepository repository;
    
      public void doSomething() {
        List<Person> persons = repository.findByLastname("Matthews");
      }
    }

The sections that follow explain each step in detail.

7.3. Defining repository interfaces

As a first step you 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.

7.3.1. Fine-tuning repository definition

Typically, your repository interface will extend 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, simply copy the ones you want to expose from CrudRepository into your domain repository.

This allows you to define your own abstractions on top of the provided Spring Data Repositories functionality.
Example 7. Selectively exposing CRUD methods
@NoRepositoryBean
interface MyBaseRepository<T, ID extends Serializable> extends Repository<T, ID> {

  T findOne(ID id);

  T save(T entity);
}

interface UserRepository extends MyBaseRepository<User, Long> {
  User findByEmailAddress(EmailAddress emailAddress);
}

In this first step you defined a common base interface for all your domain repositories and exposed findOne(…) as well as save(…).These methods will be routed into the base repository implementation of the store of your choice provided by Spring Data ,e.g. in the case if JPA SimpleJpaRepository, because they are matching the method signatures in CrudRepository. So the UserRepository will now be able to save users, and find single ones by id, as well as triggering a query to find Users by their email address.

Note, that the intermediate repository interface is annotated with @NoRepositoryBean. Make sure you add that annotation to all repository interfaces that Spring Data should not create instances for at runtime.

7.3.2. Using Repositories with multiple Spring Data modules

Using a unique Spring Data module in your application makes things simple hence, 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 case, it’s required for a repository definition to distinguish between persistence technologies. Spring Data enters strict repository configuration mode because it detects multiple repository factories on the class path. Strict configuration requires details on the repository or the domain class to decide about Spring Data module binding for a repository definition:

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

  2. If the domain class is annotated with the module-specific type annotation, then it’s a valid candidate for the particular Spring Data module. Spring Data modules accept either 3rd party annotations (such as JPA’s @Entity) or provide own annotations such as @Document for Spring Data MongoDB/Spring Data Elasticsearch.

Example 8. Repository definitions using Module-specific Interfaces
interface MyRepository extends JpaRepository<User, Long> { }

@NoRepositoryBean
interface MyBaseRepository<T, ID extends Serializable> 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.

Example 9. Repository definitions using generic Interfaces
interface AmbiguousRepository extends Repository<User, Long> {
 …
}

@NoRepositoryBean
interface MyBaseRepository<T, ID extends Serializable> 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 perfectly fine using a unique Spring Data module, multiple modules cannot distinguish to which particular Spring Data these repositories should be bound.

Example 10. Repository definitions using Domain Classes with Annotations
interface PersonRepository extends Repository<Person, Long> {
 …
}

@Entity
public class Person {
  …
}

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

@Document
public class User {
  …
}

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

Example 11. Repository definitions using Domain Classes with mixed Annotations
interface JpaPersonRepository extends Repository<Person, Long> {
 …
}

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

@Entity
@Document
public 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 identifying domain class annotations are used for strict repository configuration identify repository candidates for a particular Spring Data module. Using multiple persistence technology-specific annotations on the same domain type is possible to reuse domain types across multiple persistence technologies, but then Spring Data is no longer able to determine a unique module to bind the repository.

The last way to distinguish repositories is scoping repository base packages. Base packages define the starting points for scanning for repository interface definitions which implies to have 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.

Example 12. Annotation-driven configuration of base packages
@EnableJpaRepositories(basePackages = "com.acme.repositories.jpa")
@EnableMongoRepositories(basePackages = "com.acme.repositories.mongo")
interface Configuration { }

7.4. Defining query methods

The repository proxy has two ways to derive a store-specific query from the method name. It can derive the query from the method name directly, or by using a manually defined query. Available options depend on the actual store. However, there’s got to be a strategy that decides what actual query is created. Let’s have a look at the available options.

7.4.1. Query lookup strategies

The following strategies are available for the repository infrastructure to resolve the query. You can configure the strategy at the namespace through the query-lookup-strategy attribute in case of XML configuration or via the queryLookupStrategy attribute of the Enable${store}Repositories annotation in case of Java config. Some strategies may not be supported for particular datastores.

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

  • USE_DECLARED_QUERY tries to find a declared query and will throw an exception in case it can’t find one. The query can be defined by an annotation somewhere or declared by other means. Consult the documentation of the specific store to find available options for that store. If the repository infrastructure does not find a declared query for the method at bootstrap time, it fails.

  • CREATE_IF_NOT_FOUND (default) combines CREATE and USE_DECLARED_QUERY. It looks up a declared query first, and if no declared query is found, it creates a custom method name-based query. This is the default lookup strategy and thus will be used if you do not configure anything explicitly. It allows quick query definition by method names but also custom-tuning of these queries by introducing declared queries as needed.

7.4.2. Query creation

The query builder mechanism built into Spring Data repository infrastructure is useful for building constraining queries over entities of the repository. The mechanism strips the prefixes find…By, read…By, query…By, count…By, and get…By from the method and starts parsing the rest of it. The introducing clause can contain further expressions such as a Distinct to set a distinct flag on the query to be created. However, the first By acts as delimiter to indicate the start of the actual criteria. At a very basic level you can define conditions on entity properties and concatenate them with And and Or.

Example 13. Query creation from method names
public interface PersonRepository extends Repository<User, 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);
}

The actual result of parsing the method depends on the persistence store for which you create the query. However, there are some general things to notice.

  • The expressions are usually property traversals combined with operators that can be concatenated. You can combine property expressions with AND and OR. You also get support for operators such as Between, LessThan, GreaterThan, Like for the property expressions. The supported operators can vary by datastore, so consult the appropriate part of your reference documentation.

  • The method parser supports setting an IgnoreCase flag for individual properties (for example, findByLastnameIgnoreCase(…)) or for all properties of a type that support ignoring case (usually String instances, for example, findByLastnameAndFirstnameAllIgnoreCase(…)). Whether ignoring cases is supported may vary by store, so consult the relevant sections in the reference documentation for the store-specific query method.

  • You can apply static ordering by appending an OrderBy clause to the query method that references a property and by providing a sorting direction (Asc or Desc). To create a query method that supports dynamic sorting, see Special parameter handling.

7.4.3. 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. Assume a Person has an Address with a ZipCode. In that case a method name of

List<Person> findByAddressZipCode(ZipCode zipCode);

creates the property traversal x.address.zipCode. The resolution algorithm starts with 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 continue building the tree down from there, splitting the tail up in the way just described. If the first split does not match, the algorithm move 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 and essentially choose the wrong property and finally 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 end up like so:

List<Person> findByAddress_ZipCode(ZipCode zipCode);

As we treat underscore as a reserved character we strongly advise to follow standard Java naming conventions (i.e. not using underscores in property names but camel case instead).

7.4.4. Special parameter handling

To handle parameters in your query you simply define method parameters as already seen in the examples above. Besides that the infrastructure will recognize certain specific types like Pageable and Sort to apply pagination and sorting to your queries dynamically.

Example 14. Using Pageable, Slice and Sort in query methods
Page<User> findByLastname(String lastname, Pageable pageable);

Slice<User> findByLastname(String lastname, Pageable pageable);

List<User> findByLastname(String lastname, Sort sort);

List<User> findByLastname(String lastname, Pageable pageable);

The first method allows you to 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, Slice can be used as return instead. A Slice only knows about whether there’s a next Slice available which might be just sufficient when walking thought a larger result set.

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

To find out how many pages you get for a query entirely you have to trigger an additional count query. By default this query will be derived from the query you actually trigger.

7.4.5. Limiting query results

The results of query methods can be limited via the keywords first or top, which can be used interchangeably. An optional numeric value can be appended to top/first to specify the maximum result size to be returned. If the number is left out, a result size of 1 is assumed.

Example 15. 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. Also, for the queries limiting the result set to one instance, wrapping the result into an Optional is supported.

If pagination or slicing is applied to a limiting query pagination (and the calculation of the number of pages available) then it is applied within the limited result.

Note that limiting the results in combination with dynamic sorting via a Sort parameter allows to express query methods for the 'K' smallest as well as for the 'K' biggest elements.

7.4.6. Streaming query results

The results of query methods can be processed incrementally by using a Java 8 Stream<T> as return type. Instead of simply wrapping the query results in a Stream data store specific methods are used to perform the streaming.

Example 16. Stream the result of a query with Java 8 Stream<T>
@Query("select u from User u")
Stream<User> findAllByCustomQueryAndStream();

Stream<User> readAllByFirstnameNotNull();

@Query("select u from User u")
Stream<User> streamAllPaged(Pageable pageable);
A Stream potentially wraps underlying data store specific resources and must therefore be closed after usage. You can either manually close the Stream using the close() method or by using a Java 7 try-with-resources block.
Example 17. 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 Stream<T> as a return type.

7.4.7. Async query results

Repository queries can be executed asynchronously using Spring’s asynchronous method execution capability. This means the method will return immediately upon invocation and the actual query execution will occur in a task that has been submitted to a Spring TaskExecutor.

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

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

@Async
ListenableFuture<User> findOneByLastname(String lastname);    (3)
1 Use java.util.concurrent.Future as return type.
2 Use a Java 8 java.util.concurrent.CompletableFuture as return type.
3 Use a org.springframework.util.concurrent.ListenableFuture as return type.

7.5. Creating repository instances

In this section you create instances and bean definitions for the repository interfaces defined. One way to do so is using the Spring namespace that is shipped with each Spring Data module that supports the repository mechanism although we generally recommend to use the Java-Config style configuration.

7.5.1. XML configuration

Each Spring Data module includes a repositories element that allows you to simply define a base package that Spring scans for you.

Example 18. 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
    http://www.springframework.org/schema/beans/spring-beans.xsd
    http://www.springframework.org/schema/data/jpa
    http://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. 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 extending 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 bean instances get created for. To do this you use <include-filter /> and <exclude-filter /> elements inside <repositories />. The semantics are exactly equivalent to the elements in Spring’s context namespace. For details, see Spring reference documentation on these elements.

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

Example 19. Using exclude-filter element
<repositories base-package="com.acme.repositories">
  <context:exclude-filter type="regex" expression=".*SomeRepository" />
</repositories>

This example excludes all interfaces ending in SomeRepository from being instantiated.

7.5.2. JavaConfig

The repository infrastructure can also be triggered using a store-specific @Enable${store}Repositories annotation on a JavaConfig class. For an introduction into Java-based configuration of the Spring container, see the reference documentation.[1]

A sample configuration to enable Spring Data repositories looks something like this.

Example 20. Sample annotation based repository configuration
@Configuration
@EnableJpaRepositories("com.acme.repositories")
class ApplicationConfiguration {

  @Bean
  public EntityManagerFactory entityManagerFactory() {
    // …
  }
}
The sample uses the JPA-specific annotation, which you would change according to the store module you actually use. The same applies to the definition of the EntityManagerFactory bean. Consult the sections covering the store-specific configuration.

7.5.3. Standalone usage

You can also use the repository infrastructure outside of a Spring container, e.g. 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 a persistence technology-specific RepositoryFactory that you can use as follows.

Example 21. Standalone usage of repository factory
RepositoryFactorySupport factory = … // Instantiate factory here
UserRepository repository = factory.getRepository(UserRepository.class);

7.6. Custom implementations for Spring Data repositories

Often it is necessary to provide a custom implementation for a few repository methods. Spring Data repositories easily allow you to provide custom repository code and integrate it with generic CRUD abstraction and query method functionality.

7.6.1. Adding custom behavior to single repositories

To enrich a repository with custom functionality you first define an interface and an implementation for the custom functionality. Use the repository interface you provided to extend the custom interface.

Example 22. Interface for custom repository functionality
interface UserRepositoryCustom {
  public void someCustomMethod(User user);
}
Example 23. Implementation of custom repository functionality
class UserRepositoryImpl implements UserRepositoryCustom {

  public void someCustomMethod(User user) {
    // Your custom implementation
  }
}
The most important bit for the class to be found is the Impl postfix of the name on it compared to the core repository interface (see below).

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

Example 24. Changes to the your basic repository interface
interface UserRepository extends CrudRepository<User, Long>, UserRepositoryCustom {

  // Declare query methods here
}

Let your standard repository interface extend the custom one. Doing so combines the CRUD and custom functionality and makes it available to clients.

Configuration

If you use namespace configuration, the repository infrastructure tries to autodetect custom implementations by scanning for classes below the package we found a repository in. These classes need to follow the naming convention of appending the namespace element’s attribute repository-impl-postfix to the found repository interface name. This postfix defaults to Impl.

Example 25. Configuration example
<repositories base-package="com.acme.repository" />

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

The first configuration example will try to look up a class com.acme.repository.UserRepositoryImpl to act as custom repository implementation, whereas the second example will try to lookup com.acme.repository.UserRepositoryFooBar.

Manual wiring

The approach just shown works well if your custom implementation uses annotation-based configuration and autowiring only, as it will be treated as any other Spring bean. If your custom implementation bean needs special wiring, you simply declare the bean and name it after the conventions just described. The infrastructure will then refer to the manually defined bean definition by name instead of creating one itself.

Example 26. Manual wiring of custom implementations
<repositories base-package="com.acme.repository" />

<beans:bean id="userRepositoryImpl" class="…">
  <!-- further configuration -->
</beans:bean>

7.6.2. Adding custom behavior to all repositories

The preceding approach is not feasible when you want to add a single method to all your repository interfaces. To add custom behavior to all repositories, you first add an intermediate interface to declare the shared behavior.

Example 27. An interface declaring custom shared behavior
@NoRepositoryBean
public interface MyRepository<T, ID extends Serializable>
  extends PagingAndSortingRepository<T, ID> {

  void sharedCustomMethod(ID id);
}

Now your individual repository interfaces will extend this intermediate interface instead of the Repository interface to include the functionality declared. Next, create an implementation of the intermediate interface that extends the persistence technology-specific repository base class. This class will then act as a custom base class for the repository proxies.

Example 28. Custom repository base class
public class MyRepositoryImpl<T, ID extends Serializable>
  extends SimpleJpaRepository<T, ID> implements MyRepository<T, ID> {

  private final EntityManager entityManager;

  public MyRepositoryImpl(JpaEntityInformation entityInformation,
                          EntityManager entityManager) {
    super(entityInformation, entityManager);

    // Keep the EntityManager around to used from the newly introduced methods.
    this.entityManager = entityManager;
  }

  public void sharedCustomMethod(ID id) {
    // implementation goes here
  }
}
The class needs to have a constructor of the super class which the store-specific repository factory implementation is using. In case the repository base class has multiple constructors, override the one taking an EntityInformation plus a store specific infrastructure object (e.g. an EntityManager or a template class).

The default behavior of the Spring <repositories /> namespace is to provide an implementation for all interfaces that fall under the base-package. This means that if left in its current state, an implementation instance of MyRepository will be created by Spring. This is of course not desired as it is just supposed to act as an intermediary between Repository and the actual repository interfaces you want to define for each entity. To exclude an interface that extends Repository from being instantiated as a repository instance, you can either annotate it with @NoRepositoryBean (as seen above) or move it outside of the configured base-package.

The final step is to make the Spring Data infrastructure aware of the customized repository base class. In JavaConfig this is achieved by using the repositoryBaseClass attribute of the @Enable…Repositories annotation:

Example 29. Configuring a custom repository base class using JavaConfig
@Configuration
@EnableJpaRepositories(repositoryBaseClass = MyRepositoryImpl.class)
class ApplicationConfiguration { … }

A corresponding attribute is available in the XML namespace.

Example 30. Configuring a custom repository base class using XML
<repositories base-package="com.acme.repository"
     base-class="….MyRepositoryImpl" />

7.7. 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.

7.7.1. Querydsl Extension

Querydsl is a framework which enables the construction of statically typed SQL-like queries via its fluent API.

Several Spring Data modules offer integration with Querydsl via QueryDslPredicateExecutor.

Example 31. QueryDslPredicateExecutor interface
public interface QueryDslPredicateExecutor<T> {

    T findOne(Predicate predicate);             (1)

    Iterable<T> findAll(Predicate predicate);   (2)

    long count(Predicate predicate);            (3)

    boolean exists(Predicate predicate);        (4)

    // … more functionality omitted.
}
1 Finds and returns a single entity matching the Predicate.
2 Finds and returns all entities matching the Predicate.
3 Returns the number of entities matching the Predicate.
4 Returns if an entity that matches the Predicate exists.

To make use of Querydsl support simply extend QueryDslPredicateExecutor on your repository interface.

Example 32. Querydsl integration on repositories
interface UserRepository extends CrudRepository<User, Long>, QueryDslPredicateExecutor<User> {

}

The above enables to write typesafe queries using Querydsl Predicate s.

Predicate predicate = user.firstname.equalsIgnoreCase("dave")
	.and(user.lastname.startsWithIgnoreCase("mathews"));

userRepository.findAll(predicate);

7.7.2. Web support

This section contains the documentation for the Spring Data web support as it is implemented as of Spring Data Commons in the 1.6 range. As it the newly introduced support changes quite a lot of things we kept the documentation of the former behavior in Legacy web support.

Spring Data modules ships with a variety of web support if the module supports the repository programming model. The web related stuff requires Spring MVC JARs on the classpath, some of them even provide integration with Spring HATEOAS [2]. In general, the integration support is enabled by using the @EnableSpringDataWebSupport annotation in your JavaConfig configuration class.

Example 33. Enabling Spring Data web support
@Configuration
@EnableWebMvc
@EnableSpringDataWebSupport
class WebConfiguration { }

The @EnableSpringDataWebSupport annotation registers a few components we will discuss in a bit. It will also detect Spring HATEOAS on the classpath and register integration components for it as well if present.

Alternatively, if you are using XML configuration, register either SpringDataWebSupport or HateoasAwareSpringDataWebSupport as Spring beans:

Example 34. Enabling Spring Data web support in XML
<bean class="org.springframework.data.web.config.SpringDataWebConfiguration" />

<!-- If you're using Spring HATEOAS as well register this one *instead* of the former -->
<bean class="org.springframework.data.web.config.HateoasAwareSpringDataWebConfiguration" />
Basic web support

The configuration setup shown above will register a few basic components:

  • A DomainClassConverter to enable Spring MVC to resolve instances of repository managed domain classes from request parameters or path variables.

  • HandlerMethodArgumentResolver implementations to let Spring MVC resolve Pageable and Sort instances from request parameters.

DomainClassConverter

The DomainClassConverter allows you to use domain types in your Spring MVC controller method signatures directly, so that you don’t have to manually lookup the instances via the repository:

Example 35. A Spring MVC controller using domain types in method signatures
@Controller
@RequestMapping("/users")
public class UserController {

  @RequestMapping("/{id}")
  public String showUserForm(@PathVariable("id") User user, Model model) {

    model.addAttribute("user", user);
    return "userForm";
  }
}

As you can see 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 findOne(…) on the repository instance registered for the domain type.

Currently the repository has to implement CrudRepository to be eligible to be discovered for conversion.
HandlerMethodArgumentResolvers for Pageable and Sort

The configuration snippet above also registers a PageableHandlerMethodArgumentResolver as well as an instance of SortHandlerMethodArgumentResolver. The registration enables Pageable and Sort being valid controller method arguments

Example 36. Using Pageable as controller method argument
@Controller
@RequestMapping("/users")
public class UserController {

  @Autowired UserRepository repository;

  @RequestMapping
  public String showUsers(Model model, Pageable pageable) {

    model.addAttribute("users", repository.findAll(pageable));
    return "users";
  }
}

This method signature will cause Spring MVC try to derive a Pageable instance from the request parameters using the following default configuration:

Table 1. Request parameters evaluated for Pageable instances

page

Page you want to retrieve, 0 indexed and defaults to 0.

size

Size of the page you want to retrieve, defaults to 20.

sort

Properties that should be sorted by in the format property,property(,ASC|DESC). Default sort direction is ascending. Use multiple sort parameters if you want to switch directions, e.g. ?sort=firstname&sort=lastname,asc.

To customize this behavior extend either SpringDataWebConfiguration or the HATEOAS-enabled equivalent and override the pageableResolver() or sortResolver() methods and import your customized configuration file instead of using the @Enable-annotation.

In case 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}_. So for a method signature like this:

public String showUsers(Model model,
      @Qualifier("foo") Pageable first,
      @Qualifier("bar") Pageable second) { … }

you have to populate foo_page and bar_page etc.

The default Pageable handed into the method is equivalent to a new PageRequest(0, 20) but can be customized using the @PageableDefaults 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, the PagedResourcesAssembler.

Example 37. 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 above allows the PagedResourcesAssembler to be used as controller method argument. Calling toResources(…) on it will cause the following:

  • The content of the Page will become the content of the PagedResources instance.

  • The PagedResources will get a PageMetadata instance attached populated with information form the Page and the underlying PageRequest.

  • The PagedResources gets prev and next links attached depending on the page’s state. The links will point to the URI the method invoked is mapped to. The pagination parameters added to the method will match the setup of the PageableHandlerMethodArgumentResolver to make sure the links can be resolved later on.

Assume we have 30 Person instances in the database. You can now trigger a request GET http://localhost:8080/persons and you’ll see something similar to this:

{ "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
  }
}

You see that the assembler produced the correct URI and also picks up the default configuration present to resolve the parameters into a Pageable for an upcoming request. This means, if you change that configuration, the links will automatically adhere to the change. By default the assembler points to the controller method it was invoked in but that can be customized by handing in a custom Link to be used as base to build the pagination links to overloads of the PagedResourcesAssembler.toResource(…) method.

Querydsl web support

For those stores having QueryDSL integration it is possible to derive queries from the attributes contained in a Request query string.

This means that given the User object from previous samples a query string

?firstname=Dave&lastname=Matthews

can be resolved to

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

using the QuerydslPredicateArgumentResolver.

The feature will be automatically enabled along @EnableSpringDataWebSupport when Querydsl is found on the classpath.

Adding a @QuerydslPredicate to the method signature will provide a ready to use Predicate which can be executed via the QueryDslPredicateExecutor.

Type information is typically resolved from the methods return type. Since those information does not necessarily match the domain type it might be a good idea to use the root attribute of QuerydslPredicate.
@Controller
class UserController {

  @Autowired UserRepository repository;

  @RequestMapping(value = "/", method = RequestMethod.GET)
  String index(Model model, @QuerydslPredicate(root = User.class) Predicate predicate,    (1)
          Pageable pageable, @RequestParam MultiValueMap<String, String> parameters) {

    model.addAttribute("users", repository.findAll(predicate, pageable));

    return "index";
  }
}
1 Resolve query string arguments to matching Predicate for User.

The default binding is as follows:

  • Object on simple properties as eq.

  • Object on collection like properties as contains.

  • Collection on simple properties as in.

Those bindings can be customized via the bindings attribute of @QuerydslPredicate or by making use of Java 8 default methods adding the QuerydslBinderCustomizer to the repository interface.

interface UserRepository extends CrudRepository<User, String>,
                                 QueryDslPredicateExecutor<User>,                (1)
                                 QuerydslBinderCustomizer<QUser> {               (2)

  @Override
  default public void customize(QuerydslBindings bindings, QUser user) {

    bindings.bind(user.username).first((path, value) -> path.contains(value))    (3)
    bindings.bind(String.class)
      .first((StringPath path, String value) -> path.containsIgnoreCase(value)); (4)
    bindings.excluding(user.password);                                           (5)
  }
}
1 QueryDslPredicateExecutor provides access to specific finder methods for Predicate.
2 QuerydslBinderCustomizer defined on the repository interface will be automatically picked up and shortcuts @QuerydslPredicate(bindings=…​).
3 Define the binding for the username property to be a simple contains binding.
4 Define the default binding for String properties to be a case insensitive contains match.
5 Exclude the password property from Predicate resolution.

7.7.3. Repository populators

If you work with the Spring JDBC module, you probably are familiar with the support to populate a DataSource using 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 data.json with the following content:

Example 38. Data defined in JSON
[ { "_class" : "com.acme.Person",
 "firstname" : "Dave",
  "lastname" : "Matthews" },
  { "_class" : "com.acme.Person",
 "firstname" : "Carter",
  "lastname" : "Beauford" } ]

You can easily 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 , do the following:

Example 39. 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
    http://www.springframework.org/schema/beans/spring-beans.xsd
    http://www.springframework.org/schema/data/repository
    http://www.springframework.org/schema/data/repository/spring-repository.xsd">

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

</beans>

This declaration causes the data.json file to be read and deserialized via a Jackson ObjectMapper.

The type to which the JSON object will be unmarshalled to will be determined by inspecting the _class attribute of the JSON document. The infrastructure will eventually select the appropriate repository to handle the object just deserialized.

To rather use XML to define the data the repositories shall be populated with, you can use the unmarshaller-populator element. You configure it to use one of the XML marshaller options Spring OXM provides you with. See the Spring reference documentation for details.

Example 40. 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
    http://www.springframework.org/schema/beans/spring-beans.xsd
    http://www.springframework.org/schema/data/repository
    http://www.springframework.org/schema/data/repository/spring-repository.xsd
    http://www.springframework.org/schema/oxm
    http://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>

7.7.4. Legacy web support

Domain class web binding for Spring MVC

Given you are developing a Spring MVC web application you typically have to resolve domain class ids from URLs. By default your task is to transform that request parameter or URL part into the domain class to hand it to layers below then or execute business logic on the entities directly. This would look something like this:

@Controller
@RequestMapping("/users")
public class UserController {

  private final UserRepository userRepository;

  @Autowired
  public UserController(UserRepository userRepository) {
    Assert.notNull(repository, "Repository must not be null!");
    this.userRepository = userRepository;
  }

  @RequestMapping("/{id}")
  public String showUserForm(@PathVariable("id") Long id, Model model) {

    // Do null check for id
    User user = userRepository.findOne(id);
    // Do null check for user

    model.addAttribute("user", user);
    return "user";
  }
}

First you declare a repository dependency for each controller to look up the entity managed by the controller or repository respectively. Looking up the entity is boilerplate as well, as it’s always a findOne(…) call. Fortunately Spring provides means to register custom components that allow conversion between a String value to an arbitrary type.

PropertyEditors

For Spring versions before 3.0 simple Java PropertyEditors had to be used. To integrate with that, Spring Data offers a DomainClassPropertyEditorRegistrar, which looks up all Spring Data repositories registered in the ApplicationContext and registers a custom PropertyEditor for the managed domain class.

<bean class="….web.servlet.mvc.annotation.AnnotationMethodHandlerAdapter">
  <property name="webBindingInitializer">
    <bean class="….web.bind.support.ConfigurableWebBindingInitializer">
      <property name="propertyEditorRegistrars">
        <bean class="org.springframework.data.repository.support.DomainClassPropertyEditorRegistrar" />
      </property>
    </bean>
  </property>
</bean>

If you have configured Spring MVC as in the preceding example, you can configure your controller as follows, which reduces a lot of the clutter and boilerplate.

@Controller
@RequestMapping("/users")
public class UserController {

  @RequestMapping("/{id}")
  public String showUserForm(@PathVariable("id") User user, Model model) {

    model.addAttribute("user", user);
    return "userForm";
  }
}

Reference Documentation

8. Introduction

8.1. Document Structure

This part of the reference documentation explains the core functionality offered by Spring Data Document.

MongoDB support introduces the MongoDB module feature set.

MongoDB repositories introduces the repository support for MongoDB.

9. MongoDB support

The MongoDB support contains a wide range of features which are summarized below.

  • Spring configuration support using Java based @Configuration classes or an XML namespace for a Mongo driver instance and replica sets

  • MongoTemplate helper class that increases productivity performing common Mongo operations. Includes integrated object mapping between documents and POJOs.

  • Exception translation into Spring’s portable Data Access Exception hierarchy

  • Feature Rich Object Mapping integrated with Spring’s Conversion Service

  • Annotation based mapping metadata but extensible to support other metadata formats

  • Persistence and mapping lifecycle events

  • Java based Query, Criteria, and Update DSLs

  • Automatic implementation of Repository interfaces including support for custom finder methods.

  • QueryDSL integration to support type-safe queries.

  • Cross-store persistence - support for JPA Entities with fields transparently persisted/retrieved using MongoDB

  • Log4j log appender

  • GeoSpatial integration

For most tasks you will find yourself using MongoTemplate or the Repository support that both leverage the rich mapping functionality. MongoTemplate is the place to look for accessing functionality such as incrementing counters or ad-hoc CRUD operations. MongoTemplate also provides callback methods so that it is easy for you to get a hold of the low level API artifacts such as com.mongo.DB to communicate directly with MongoDB. The goal with naming conventions on various API artifacts is to copy those in the base MongoDB Java driver so you can easily map your existing knowledge onto the Spring APIs.

9.1. Getting Started

Spring MongoDB support requires MongoDB 2.6 or higher and Java SE 6 or higher. An easy way to bootstrap setting up a working environment is to create a Spring based project in STS.

First you need to set up a running Mongodb server. Refer to the Mongodb Quick Start guide for an explanation on how to startup a MongoDB instance. Once installed starting MongoDB is typically a matter of executing the following command: MONGO_HOME/bin/mongod

To create a Spring project in STS go to File → New → Spring Template Project → Simple Spring Utility Project → press Yes when prompted. Then enter a project and a package name such as org.spring.mongodb.example.

Then add the following to pom.xml dependencies section.

<dependencies>

  <!-- other dependency elements omitted -->

  <dependency>
    <groupId>org.springframework.data</groupId>
    <artifactId>spring-data-mongodb</artifactId>
    <version>{version}</version>
  </dependency>

</dependencies>

Also change the version of Spring in the pom.xml to be

<spring.framework.version>{springVersion}</spring.framework.version>

You will also need to add the location of the Spring Milestone repository for maven to your pom.xml which is at the same level of your <dependencies/> element

<repositories>
  <repository>
    <id>spring-milestone</id>
    <name>Spring Maven MILESTONE Repository</name>
    <url>http://repo.spring.io/libs-milestone</url>
  </repository>
</repositories>

The repository is also browseable here.

You may also want to set the logging level to DEBUG to see some additional information, edit the log4j.properties file to have

log4j.category.org.springframework.data.mongodb=DEBUG
log4j.appender.stdout.layout.ConversionPattern=%d{ABSOLUTE} %5p %40.40c:%4L - %m%n

Create a simple Person class to persist:

package org.spring.mongodb.example;

public class Person {

  private String id;
  private String name;
  private int age;

  public Person(String name, int age) {
    this.name = name;
    this.age = age;
  }

  public String getId() {
    return id;
  }
  public String getName() {
    return name;
  }
  public int getAge() {
    return age;
  }

  @Override
  public String toString() {
    return "Person [id=" + id + ", name=" + name + ", age=" + age + "]";
  }
}

And a main application to run

package org.spring.mongodb.example;

import static org.springframework.data.mongodb.core.query.Criteria.where;

import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.springframework.data.mongodb.core.MongoOperations;
import org.springframework.data.mongodb.core.MongoTemplate;
import org.springframework.data.mongodb.core.query.Query;

import com.mongodb.Mongo;

public class MongoApp {

  private static final Log log = LogFactory.getLog(MongoApp.class);

  public static void main(String[] args) throws Exception {

    MongoOperations mongoOps = new MongoTemplate(new Mongo(), "database");
    mongoOps.insert(new Person("Joe", 34));

    log.info(mongoOps.findOne(new Query(where("name").is("Joe")), Person.class));

    mongoOps.dropCollection("person");
  }
}

This will produce the following output

10:01:32,062 DEBUG apping.MongoPersistentEntityIndexCreator:  80 - Analyzing class class org.spring.example.Person for index information.
10:01:32,265 DEBUG ramework.data.mongodb.core.MongoTemplate: 631 - insert DBObject containing fields: [_class, age, name] in collection: Person
10:01:32,765 DEBUG ramework.data.mongodb.core.MongoTemplate:1243 - findOne using query: { "name" : "Joe"} in db.collection: database.Person
10:01:32,953  INFO      org.spring.mongodb.example.MongoApp:  25 - Person [id=4ddbba3c0be56b7e1b210166, name=Joe, age=34]
10:01:32,984 DEBUG ramework.data.mongodb.core.MongoTemplate: 375 - Dropped collection [database.person]

Even in this simple example, there are few things to take notice of

  • You can instantiate the central helper class of Spring Mongo, MongoTemplate, using the standard com.mongodb.Mongo object and the name of the database to use.

  • The mapper works against standard POJO objects without the need for any additional metadata (though you can optionally provide that information. See here.).

  • Conventions are used for handling the id field, converting it to be a ObjectId when stored in the database.

  • Mapping conventions can use field access. Notice the Person class has only getters.

  • If the constructor argument names match the field names of the stored document, they will be used to instantiate the object

9.2. Examples Repository

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

9.3. Connecting to MongoDB with Spring

One of the first tasks when using MongoDB and Spring is to create a com.mongodb.Mongo object using the IoC container. There are two main ways to do this, either using Java based bean metadata or XML based bean metadata. These are discussed in the following sections.

For those not familiar with how to configure the Spring container using Java based bean metadata instead of XML based metadata see the high level introduction in the reference docs here as well as the detailed documentation here.

9.3.1. Registering a Mongo instance using Java based metadata

An example of using Java based bean metadata to register an instance of a com.mongodb.Mongo is shown below

Example 41. Registering a com.mongodb.Mongo object using Java based bean metadata
@Configuration
public class AppConfig {

  /*
   * Use the standard Mongo driver API to create a com.mongodb.Mongo instance.
   */
   public @Bean Mongo mongo() throws UnknownHostException {
       return new Mongo("localhost");
   }
}

This approach allows you to use the standard com.mongodb.Mongo API that you may already be used to using but also pollutes the code with the UnknownHostException checked exception. The use of the checked exception is not desirable as Java based bean metadata uses methods as a means to set object dependencies, making the calling code cluttered.

An alternative is to register an instance of com.mongodb.Mongo instance with the container using Spring’s MongoClientFactoryBean. As compared to instantiating a com.mongodb.Mongo instance directly, the FactoryBean approach does not throw a checked exception and has the added advantage of also providing the container with an ExceptionTranslator implementation that translates MongoDB exceptions to exceptions in Spring’s portable DataAccessException hierarchy for data access classes annotated with the @Repository annotation. This hierarchy and use of @Repository is described in Spring’s DAO support features.

An example of a Java based bean metadata that supports exception translation on @Repository annotated classes is shown below:

Example 42. Registering a com.mongodb.Mongo object using Spring’s MongoClientFactoryBean and enabling Spring’s exception translation support
@Configuration
public class AppConfig {

    /*
     * Factory bean that creates the com.mongodb.Mongo instance
     */
     public @Bean MongoClientFactoryBean mongo() {
          MongoClientFactoryBean mongo = new MongoClientFactoryBean();
          mongo.setHost("localhost");
          return mongo;
     }
}

To access the com.mongodb.Mongo object created by the MongoClientFactoryBean in other @Configuration or your own classes, use a “private @Autowired Mongo mongo;” field.

9.3.2. Registering a Mongo instance using XML based metadata

While you can use Spring’s traditional <beans/> XML namespace to register an instance of com.mongodb.Mongo with the container, the XML can be quite verbose as it is general purpose. XML namespaces are a better alternative to configuring commonly used objects such as the Mongo instance. The mongo namespace allows you to create a Mongo instance server location, replica-sets, and options.

To use the Mongo namespace elements you will need to reference the Mongo schema:

Example 43. XML schema to configure MongoDB
<?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:context="http://www.springframework.org/schema/context"
          xmlns:mongo="http://www.springframework.org/schema/data/mongo"
          xsi:schemaLocation=
          "http://www.springframework.org/schema/context
          http://www.springframework.org/schema/context/spring-context-3.0.xsd
          *http://www.springframework.org/schema/data/mongo http://www.springframework.org/schema/data/mongo/spring-mongo-1.0.xsd*
          http://www.springframework.org/schema/beans
          http://www.springframework.org/schema/beans/spring-beans-3.0.xsd">

    <!-- Default bean name is 'mongo' -->
    *<mongo:mongo host="localhost" port="27017"/>*

</beans>

A more advanced configuration with MongoOptions is shown below (note these are not recommended values)

Example 44. XML schema to configure a com.mongodb.Mongo object with MongoOptions
<beans>

  <mongo:mongo host="localhost" port="27017">
    <mongo:options connections-per-host="8"
                   threads-allowed-to-block-for-connection-multiplier="4"
                   connect-timeout="1000"
                   max-wait-time="1500}"
                   auto-connect-retry="true"
                   socket-keep-alive="true"
                   socket-timeout="1500"
                   slave-ok="true"
                   write-number="1"
                   write-timeout="0"
                   write-fsync="true"/>
  </mongo:mongo/>

</beans>

A configuration using replica sets is shown below.

Example 45. XML schema to configure com.mongodb.Mongo object with Replica Sets
<mongo:mongo id="replicaSetMongo" replica-set="127.0.0.1:27017,localhost:27018"/>

9.3.3. The MongoDbFactory interface

While com.mongodb.Mongo is the entry point to the MongoDB driver API, connecting to a specific MongoDB database instance requires additional information such as the database name and an optional username and password. With that information you can obtain a com.mongodb.DB object and access all the functionality of a specific MongoDB database instance. Spring provides the org.springframework.data.mongodb.core.MongoDbFactory interface shown below to bootstrap connectivity to the database.

public interface MongoDbFactory {

  DB getDb() throws DataAccessException;

  DB getDb(String dbName) throws DataAccessException;
}

The following sections show how you can use the container with either Java or the XML based metadata to configure an instance of the MongoDbFactory interface. In turn, you can use the MongoDbFactory instance to configure MongoTemplate.

The class org.springframework.data.mongodb.core.SimpleMongoDbFactory provides implements the MongoDbFactory interface and is created with a standard com.mongodb.Mongo instance, the database name and an optional org.springframework.data.authentication.UserCredentials constructor argument.

Instead of using the IoC container to create an instance of MongoTemplate, you can just use them in standard Java code as shown below.

public class MongoApp {

  private static final Log log = LogFactory.getLog(MongoApp.class);

  public static void main(String[] args) throws Exception {

    MongoOperations mongoOps = new MongoTemplate(*new SimpleMongoDbFactory(new Mongo(), "database")*);

    mongoOps.insert(new Person("Joe", 34));

    log.info(mongoOps.findOne(new Query(where("name").is("Joe")), Person.class));

    mongoOps.dropCollection("person");
  }
}

The code in bold highlights the use of SimpleMongoDbFactory and is the only difference between the listing shown in the getting started section.

9.3.4. Registering a MongoDbFactory instance using Java based metadata

To register a MongoDbFactory instance with the container, you write code much like what was highlighted in the previous code listing. A simple example is shown below

@Configuration
public class MongoConfiguration {

  public @Bean MongoDbFactory mongoDbFactory() throws Exception {
    return new SimpleMongoDbFactory(new Mongo(), "database");
  }
}

To define the username and password create an instance of org.springframework.data.authentication.UserCredentials and pass it into the constructor as shown below. This listing also shows using MongoDbFactory register an instance of MongoTemplate with the container.

@Configuration
public class MongoConfiguration {

  public @Bean MongoDbFactory mongoDbFactory() throws Exception {
    UserCredentials userCredentials = new UserCredentials("joe", "secret");
    return new SimpleMongoDbFactory(new Mongo(), "database", userCredentials);
  }

  public @Bean MongoTemplate mongoTemplate() throws Exception {
    return new MongoTemplate(mongoDbFactory());
  }
}

9.3.5. Registering a MongoDbFactory instance using XML based metadata

The mongo namespace provides a convenient way to create a SimpleMongoDbFactory as compared to using the <beans/> namespace. Simple usage is shown below

<mongo:db-factory dbname="database">

In the above example a com.mongodb.Mongo instance is created using the default host and port number. The SimpleMongoDbFactory registered with the container is identified by the id 'mongoDbFactory' unless a value for the id attribute is specified.

You can also provide the host and port for the underlying com.mongodb.Mongo instance as shown below, in addition to username and password for the database.

<mongo:db-factory id="anotherMongoDbFactory"
                  host="localhost"
                  port="27017"
                  dbname="database"
                  username="joe"
                  password="secret"/>

If you need to configure additional options on the com.mongodb.Mongo instance that is used to create a SimpleMongoDbFactory you can refer to an existing bean using the mongo-ref attribute as shown below. To show another common usage pattern, this listing shows the use of a property placeholder to parametrise the configuration and creating MongoTemplate.

<context:property-placeholder location="classpath:/com/myapp/mongodb/config/mongo.properties"/>

<mongo:mongo host="${mongo.host}" port="${mongo.port}">
  <mongo:options
     connections-per-host="${mongo.connectionsPerHost}"
     threads-allowed-to-block-for-connection-multiplier="${mongo.threadsAllowedToBlockForConnectionMultiplier}"
     connect-timeout="${mongo.connectTimeout}"
     max-wait-time="${mongo.maxWaitTime}"
     auto-connect-retry="${mongo.autoConnectRetry}"
     socket-keep-alive="${mongo.socketKeepAlive}"
     socket-timeout="${mongo.socketTimeout}"
     slave-ok="${mongo.slaveOk}"
     write-number="1"
     write-timeout="0"
     write-fsync="true"/>
</mongo:mongo>

<mongo:db-factory dbname="database" mongo-ref="mongo"/>

<bean id="anotherMongoTemplate" class="org.springframework.data.mongodb.core.MongoTemplate">
  <constructor-arg name="mongoDbFactory" ref="mongoDbFactory"/>
</bean>

9.4. Introduction to MongoTemplate

The class MongoTemplate, located in the package org.springframework.data.mongodb.core, is the central class of the Spring’s MongoDB support providing a rich feature set to interact with the database. The template offers convenience operations to create, update, delete and query for MongoDB documents and provides a mapping between your domain objects and MongoDB documents.

Once configured, MongoTemplate is thread-safe and can be reused across multiple instances.

The mapping between MongoDB documents and domain classes is done by delegating to an implementation of the interface MongoConverter. Spring provides two implementations, SimpleMappingConverter and MongoMappingConverter, but you can also write your own converter. Please refer to the section on MongoConverters for more detailed information.

The MongoTemplate class implements the interface MongoOperations. In as much as possible, the methods on MongoOperations are named after methods available on the MongoDB driver Collection object to make the API familiar to existing MongoDB developers who are used to the driver API. For example, you will find methods such as "find", "findAndModify", "findOne", "insert", "remove", "save", "update" and "updateMulti". The design goal was to make it as easy as possible to transition between the use of the base MongoDB driver and MongoOperations. A major difference in between the two APIs is that MongoOperations can be passed domain objects instead of DBObject and there are fluent APIs for Query, Criteria, and Update operations instead of populating a DBObject to specify the parameters for those operations.

The preferred way to reference the operations on MongoTemplate instance is via its interface MongoOperations.

The default converter implementation used by MongoTemplate is MongoMappingConverter. While the MongoMappingConverter can make use of additional metadata to specify the mapping of objects to documents it is also capable of converting objects that contain no additional metadata by using some conventions for the mapping of IDs and collection names. These conventions as well as the use of mapping annotations is explained in the Mapping chapter.

In the M2 release SimpleMappingConverter, was the default and this class is now deprecated as its functionality has been subsumed by the MongoMappingConverter.

Another central feature of MongoTemplate is exception translation of exceptions thrown in the MongoDB Java driver into Spring’s portable Data Access Exception hierarchy. Refer to the section on exception translation for more information.

While there are many convenience methods on MongoTemplate to help you easily perform common tasks if you should need to access the MongoDB driver API directly to access functionality not explicitly exposed by the MongoTemplate you can use one of several Execute callback methods to access underlying driver APIs. The execute callbacks will give you a reference to either a com.mongodb.Collection or a com.mongodb.DB object. Please see the section mongo.executioncallback[Execution Callbacks] for more information.

Now let’s look at an example of how to work with the MongoTemplate in the context of the Spring container.

9.4.1. Instantiating MongoTemplate

You can use Java to create and register an instance of MongoTemplate as shown below.

Example 46. Registering a com.mongodb.Mongo object and enabling Spring’s exception translation support
@Configuration
public class AppConfig {

  public @Bean Mongo mongo() throws Exception {
      return new Mongo("localhost");
  }

  public @Bean MongoTemplate mongoTemplate() throws Exception {
      return new MongoTemplate(mongo(), "mydatabase");
  }
}

There are several overloaded constructors of MongoTemplate. These are

  • MongoTemplate(Mongo mongo, String databaseName) - takes the com.mongodb.Mongo object and the default database name to operate against.

  • MongoTemplate(Mongo mongo, String databaseName, UserCredentials userCredentials) - adds the username and password for authenticating with the database.

  • MongoTemplate(MongoDbFactory mongoDbFactory) - takes a MongoDbFactory object that encapsulated the com.mongodb.Mongo object, database name, and username and password.

  • MongoTemplate(MongoDbFactory mongoDbFactory, MongoConverter mongoConverter) - adds a MongoConverter to use for mapping.

You can also configure a MongoTemplate using Spring’s XML <beans/> schema.

<mongo:mongo host="localhost" port="27017"/>

<bean id="mongoTemplate" class="org.springframework.data.mongodb.core.MongoTemplate">
  <constructor-arg ref="mongo"/>
  <constructor-arg name="databaseName" value="geospatial"/>
</bean>

Other optional properties that you might like to set when creating a MongoTemplate are the default WriteResultCheckingPolicy, WriteConcern, and ReadPreference.

The preferred way to reference the operations on MongoTemplate instance is via its interface MongoOperations.

9.4.2. WriteResultChecking Policy

When in development it is very handy to either log or throw an exception if the com.mongodb.WriteResult returned from any MongoDB operation contains an error. It is quite common to forget to do this during development and then end up with an application that looks like it runs successfully but in fact the database was not modified according to your expectations. Set MongoTemplate’s property to an enum with the following values, LOG, EXCEPTION, or NONE to either log the error, throw and exception or do nothing. The default is to use a WriteResultChecking value of NONE.

9.4.3. WriteConcern

You can set the com.mongodb.WriteConcern property that the MongoTemplate will use for write operations if it has not yet been specified via the driver at a higher level such as com.mongodb.Mongo. If MongoTemplate’s WriteConcern property is not set it will default to the one set in the MongoDB driver’s DB or Collection setting.

9.4.4. WriteConcernResolver

For more advanced cases where you want to set different WriteConcern values on a per-operation basis (for remove, update, insert and save operations), a strategy interface called WriteConcernResolver can be configured on MongoTemplate. Since MongoTemplate is used to persist POJOs, the WriteConcernResolver lets you create a policy that can map a specific POJO class to a WriteConcern value. The WriteConcernResolver interface is shown below.

public interface WriteConcernResolver {
  WriteConcern resolve(MongoAction action);
}

The passed in argument, MongoAction, is what you use to determine the WriteConcern value to be used or to use the value of the Template itself as a default. MongoAction contains the collection name being written to, the java.lang.Class of the POJO, the converted DBObject, as well as the operation as an enumeration (MongoActionOperation: REMOVE, UPDATE, INSERT, INSERT_LIST, SAVE) and a few other pieces of contextual information. For example,

private class MyAppWriteConcernResolver implements WriteConcernResolver {

  public WriteConcern resolve(MongoAction action) {
    if (action.getEntityClass().getSimpleName().contains("Audit")) {
      return WriteConcern.NONE;
    } else if (action.getEntityClass().getSimpleName().contains("Metadata")) {
      return WriteConcern.JOURNAL_SAFE;
    }
    return action.getDefaultWriteConcern();
  }
}

9.5. Saving, Updating, and Removing Documents

MongoTemplate provides a simple way for you to save, update, and delete your domain objects and map those objects to documents stored in MongoDB.

Given a simple class such as Person

public class Person {

  private String id;
  private String name;
  private int age;

  public Person(String name, int age) {
    this.name = name;
    this.age = age;
  }

  public String getId() {
    return id;
  }
  public String getName() {
    return name;
  }
  public int getAge() {
    return age;
  }

  @Override
  public String toString() {
    return "Person [id=" + id + ", name=" + name + ", age=" + age + "]";
  }

}

You can save, update and delete the object as shown below.

MongoOperations is the interface that MongoTemplate implements.
package org.spring.example;

import static org.springframework.data.mongodb.core.query.Criteria.where;
import static org.springframework.data.mongodb.core.query.Update.update;
import static org.springframework.data.mongodb.core.query.Query.query;

import java.util.List;

import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.springframework.data.mongodb.core.MongoOperations;
import org.springframework.data.mongodb.core.MongoTemplate;
import org.springframework.data.mongodb.core.SimpleMongoDbFactory;

import com.mongodb.Mongo;

public class MongoApp {

  private static final Log log = LogFactory.getLog(MongoApp.class);

  public static void main(String[] args) throws Exception {

    MongoOperations mongoOps = new MongoTemplate(new SimpleMongoDbFactory(new Mongo(), "database"));

    Person p = new Person("Joe", 34);

    // Insert is used to initially store the object into the database.
    mongoOps.insert(p);
    log.info("Insert: " + p);

    // Find
    p = mongoOps.findById(p.getId(), Person.class);
    log.info("Found: " + p);

    // Update
    mongoOps.updateFirst(query(where("name").is("Joe")), update("age", 35), Person.class);
    p = mongoOps.findOne(query(where("name").is("Joe")), Person.class);
    log.info("Updated: " + p);

    // Delete
    mongoOps.remove(p);

    // Check that deletion worked
    List<Person> people =  mongoOps.findAll(Person.class);
    log.info("Number of people = : " + people.size());


    mongoOps.dropCollection(Person.class);
  }
}

This would produce the following log output (including debug messages from MongoTemplate itself)

DEBUG apping.MongoPersistentEntityIndexCreator:  80 - Analyzing class class org.spring.example.Person for index information.
DEBUG work.data.mongodb.core.MongoTemplate: 632 - insert DBObject containing fields: [_class, age, name] in collection: person
INFO               org.spring.example.MongoApp:  30 - Insert: Person [id=4ddc6e784ce5b1eba3ceaf5c, name=Joe, age=34]
DEBUG work.data.mongodb.core.MongoTemplate:1246 - findOne using query: { "_id" : { "$oid" : "4ddc6e784ce5b1eba3ceaf5c"}} in db.collection: database.person
INFO               org.spring.example.MongoApp:  34 - Found: Person [id=4ddc6e784ce5b1eba3ceaf5c, name=Joe, age=34]
DEBUG work.data.mongodb.core.MongoTemplate: 778 - calling update using query: { "name" : "Joe"} and update: { "$set" : { "age" : 35}} in collection: person
DEBUG work.data.mongodb.core.MongoTemplate:1246 - findOne using query: { "name" : "Joe"} in db.collection: database.person
INFO               org.spring.example.MongoApp:  39 - Updated: Person [id=4ddc6e784ce5b1eba3ceaf5c, name=Joe, age=35]
DEBUG work.data.mongodb.core.MongoTemplate: 823 - remove using query: { "id" : "4ddc6e784ce5b1eba3ceaf5c"} in collection: person
INFO               org.spring.example.MongoApp:  46 - Number of people = : 0
DEBUG work.data.mongodb.core.MongoTemplate: 376 - Dropped collection [database.person]

There was implicit conversion using the MongoConverter between a String and ObjectId as stored in the database and recognizing a convention of the property "Id" name.

This example is meant to show the use of save, update and remove operations on MongoTemplate and not to show complex mapping functionality

The query syntax used in the example is explained in more detail in the section Querying Documents.

9.5.1. How the _id field is handled in the mapping layer

MongoDB requires that you have an _id field for all documents. If you don’t provide one the driver will assign a ObjectId with a generated value. When using the MongoMappingConverter there are certain rules that govern how properties from the Java class is mapped to this _id field.

The following outlines what property will be mapped to the _id document field:

  • A property or field annotated with @Id (org.springframework.data.annotation.Id) will be mapped to the _id field.

  • A property or field without an annotation but named id will be mapped to the _id field.

The following outlines what type conversion, if any, will be done on the property mapped to the _id document field when using the MappingMongoConverter, the default for MongoTemplate.

  • An id property or field declared as a String in the Java class will be converted to and stored as an ObjectId if possible using a Spring Converter<String, ObjectId>. Valid conversion rules are delegated to the MongoDB Java driver. If it cannot be converted to an ObjectId, then the value will be stored as a string in the database.

  • An id property or field declared as BigInteger in the Java class will be converted to and stored as an ObjectId using a Spring Converter<BigInteger, ObjectId>.

If no field or property specified above is present in the Java class then an implicit _id file will be generated by the driver but not mapped to a property or field of the Java class.

When querying and updating MongoTemplate will use the converter to handle conversions of the Query and Update objects that correspond to the above rules for saving documents so field names and types used in your queries will be able to match what is in your domain classes.

9.5.2. Type mapping

As MongoDB collections can contain documents that represent instances of a variety of types. A great example here is if you store a hierarchy of classes or simply have a class with a property of type Object. In the latter case the values held inside that property have to be read in correctly when retrieving the object. Thus we need a mechanism to store type information alongside the actual document.

To achieve that the MappingMongoConverter uses a MongoTypeMapper abstraction with DefaultMongoTypeMapper as it’s main implementation. Its default behavior is storing the fully qualified classname under _class inside the document for the top-level document as well as for every value if it’s a complex type and a subtype of the property type declared.

Example 47. Type mapping
public class Sample {
  Contact value;
}

public abstract class Contact { … }

public class Person extends Contact { … }

Sample sample = new Sample();
sample.value = new Person();

mongoTemplate.save(sample);

{ "_class" : "com.acme.Sample",
  "value" : { "_class" : "com.acme.Person" }
}

As you can see we store the type information for the actual root class persistent as well as for the nested type as it is complex and a subtype of Contact. So if you’re now using mongoTemplate.findAll(Object.class, "sample") we are able to find out that the document stored shall be a Sample instance. We are also able to find out that the value property shall be a Person actually.

Customizing type mapping

In case you want to avoid writing the entire Java class name as type information but rather like to use some key you can use the @TypeAlias annotation at the entity class being persisted. If you need to customize the mapping even more have a look at the TypeInformationMapper interface. An instance of that interface can be configured at the DefaultMongoTypeMapper which can be configured in turn on MappingMongoConverter.

Example 48. Defining a TypeAlias for an Entity
@TypeAlias("pers")
class Person {

}

Note that the resulting document will contain "pers" as the value in the _class Field.

Configuring custom type mapping

The following example demonstrates how to configure a custom MongoTypeMapper in MappingMongoConverter.

Example 49. Configuring a custom MongoTypeMapper via Spring Java Config
class CustomMongoTypeMapper extends DefaultMongoTypeMapper {
  //implement custom type mapping here
}
@Configuration
class SampleMongoConfiguration extends AbstractMongoConfiguration {

  @Override
  protected String getDatabaseName() {
    return "database";
  }

  @Override
  public Mongo mongo() throws Exception {
    return new Mongo();
  }

  @Bean
  @Override
  public MappingMongoConverter mappingMongoConverter() throws Exception {
    MappingMongoConverter mmc = super.mappingMongoConverter();
    mmc.setTypeMapper(customTypeMapper());
    return mmc;
  }

  @Bean
  public MongoTypeMapper customTypeMapper() {
    return new CustomMongoTypeMapper();
  }
}

Note that we are extending the AbstractMongoConfiguration class and override the bean definition of the MappingMongoConverter where we configure our custom MongoTypeMapper.

Example 50. Configuring a custom MongoTypeMapper via XML
<mongo:mapping-converter type-mapper-ref="customMongoTypeMapper"/>

<bean name="customMongoTypeMapper" class="com.bubu.mongo.CustomMongoTypeMapper"/>

9.5.3. Methods for saving and inserting documents

There are several convenient methods on MongoTemplate for saving and inserting your objects. To have more fine-grained control over the conversion process you can register Spring converters with the MappingMongoConverter, for example Converter<Person, DBObject> and Converter<DBObject, Person>.

The difference between insert and save operations is that a save operation will perform an insert if the object is not already present.

The simple case of using the save operation is to save a POJO. In this case the collection name will be determined by name (not fully qualified) of the class. You may also call the save operation with a specific collection name. The collection to store the object can be overridden using mapping metadata.

When inserting or saving, if the Id property is not set, the assumption is that its value will be auto-generated by the database. As such, for auto-generation of an ObjectId to succeed the type of the Id property/field in your class must be either a String, ObjectId, or BigInteger.

Here is a basic example of using the save operation and retrieving its contents.

Example 51. Inserting and retrieving documents using the MongoTemplate
import static org.springframework.data.mongodb.core.query.Criteria.where;
import static org.springframework.data.mongodb.core.query.Criteria.query;
…

Person p = new Person("Bob", 33);
mongoTemplate.insert(p);

Person qp = mongoTemplate.findOne(query(where("age").is(33)), Person.class);

The insert/save operations available to you are listed below.

  • void save (Object objectToSave) Save the object to the default collection.

  • void save (Object objectToSave, String collectionName) Save the object to the specified collection.

A similar set of insert operations is listed below

  • void insert (Object objectToSave) Insert the object to the default collection.

  • void insert (Object objectToSave, String collectionName) Insert the object to the specified collection.

Which collection will my documents be saved into?

There are two ways to manage the collection name that is used for operating on the documents. The default collection name that is used is the class name changed to start with a lower-case letter. So a com.test.Person class would be stored in the "person" collection. You can customize this by providing a different collection name using the @Document annotation. You can also override the collection name by providing your own collection name as the last parameter for the selected MongoTemplate method calls.

Inserting or saving individual objects

The MongoDB driver supports inserting a collection of documents in one operation. The methods in the MongoOperations interface that support this functionality are listed below

  • insert inserts an object. If there is an existing document with the same id then an error is generated.

  • insertAll takes a Collection of objects as the first parameter. This method inspects each object and inserts it to the appropriate collection based on the rules specified above.

  • save saves the object overwriting any object that might exist with the same id.

Inserting several objects in a batch

The MongoDB driver supports inserting a collection of documents in one operation. The methods in the MongoOperations interface that support this functionality are listed below

  • insert methods that take a Collection as the first argument. This inserts a list of objects in a single batch write to the database.

9.5.4. Updating documents in a collection

For updates we can elect to update the first document found using MongoOperation 's method updateFirst or we can update all documents that were found to match the query using the method updateMulti. Here is an example of an update of all SAVINGS accounts where we are adding a one-time $50.00 bonus to the balance using the $inc operator.

Example 52. Updating documents using the MongoTemplate
import static org.springframework.data.mongodb.core.query.Criteria.where;
import static org.springframework.data.mongodb.core.query.Query;
import static org.springframework.data.mongodb.core.query.Update;

...

WriteResult wr = mongoTemplate.updateMulti(new Query(where("accounts.accountType").is(Account.Type.SAVINGS)),
  new Update().inc("accounts.$.balance", 50.00), Account.class);

In addition to the Query discussed above we provide the update definition using an Update object. The Update class has methods that match the update modifiers available for MongoDB.

As you can see most methods return the Update object to provide a fluent style for the API.

Methods for executing updates for documents
  • updateFirst Updates the first document that matches the query document criteria with the provided updated document.

  • updateMulti Updates all objects that match the query document criteria with the provided updated document.

Methods for the Update class

The Update class can be used with a little 'syntax sugar' as its methods are meant to be chained together and you can kick-start the creation of a new Update instance via the static method public static Update update(String key, Object value) and using static imports.

Here is a listing of methods on the Update class

  • Update addToSet (String key, Object value) ` Update using the `$addToSet update modifier

  • Update inc (String key, Number inc) Update using the $inc update modifier

  • Update pop (String key, Update.Position pos) Update using the $pop update modifier

  • Update pull (String key, Object value) Update using the $pull update modifier

  • Update pullAll (String key, Object[] values) Update using the $pullAll update modifier

  • Update push (String key, Object value) ` Update using the `$push update modifier

  • Update pushAll (String key, Object[] values) Update using the $pushAll update modifier

  • Update rename (String oldName, String newName) Update using the $rename update modifier

  • Update set (String key, Object value) Update using the $set update modifier

  • Update unset (String key) Update using the $unset update modifier

9.5.5. Upserting documents in a collection

Related to performing an updateFirst operations, you can also perform an upsert operation which will perform an insert if no document is found that matches the query. The document that is inserted is a combination of the query document and the update document. Here is an example

template.upsert(query(where("ssn").is(1111).and("firstName").is("Joe").and("Fraizer").is("Update")), update("address", addr), Person.class);

9.5.6. Finding and Upserting documents in a collection

The findAndModify(…) method on DBCollection can update a document and return either the old or newly updated document in a single operation. MongoTemplate provides a findAndModify method that takes Query and Update classes and converts from DBObject to your POJOs. Here are the methods

<T> T findAndModify(Query query, Update update, Class<T> entityClass);

<T> T findAndModify(Query query, Update update, Class<T> entityClass, String collectionName);

<T> T findAndModify(Query query, Update update, FindAndModifyOptions options, Class<T> entityClass);

<T> T findAndModify(Query query, Update update, FindAndModifyOptions options, Class<T> entityClass, String collectionName);

As an example usage, we will insert of few Person objects into the container and perform a simple findAndUpdate operation

mongoTemplate.insert(new Person("Tom", 21));
mongoTemplate.insert(new Person("Dick", 22));
mongoTemplate.insert(new Person("Harry", 23));

Query query = new Query(Criteria.where("firstName").is("Harry"));
Update update = new Update().inc("age", 1);
Person p = mongoTemplate.findAndModify(query, update, Person.class); // return's old person object

assertThat(p.getFirstName(), is("Harry"));
assertThat(p.getAge(), is(23));
p = mongoTemplate.findOne(query, Person.class);
assertThat(p.getAge(), is(24));

// Now return the newly updated document when updating
p = template.findAndModify(query, update, new FindAndModifyOptions().returnNew(true), Person.class);
assertThat(p.getAge(), is(25));

The FindAndModifyOptions lets you set the options of returnNew, upsert, and remove. An example extending off the previous code snippet is shown below

Query query2 = new Query(Criteria.where("firstName").is("Mary"));
p = mongoTemplate.findAndModify(query2, update, new FindAndModifyOptions().returnNew(true).upsert(true), Person.class);
assertThat(p.getFirstName(), is("Mary"));
assertThat(p.getAge(), is(1));

9.5.7. Methods for removing documents

You can use several overloaded methods to remove an object from the database.

  • remove Remove the given document based on one of the following: a specific object instance, a query document criteria combined with a class or a query document criteria combined with a specific collection name.

9.5.8. Optimistic locking

The @Version annotation provides a JPA similar semantic in the context of MongoDB and makes sure updates are only applied to documents with matching version. Therefore the actual value of the version property is added to the update query in a way that the update won’t have any effect if another operation altered the document in between. In that case an OptimisticLockingFailureException is thrown.

@Document
class Person {

  @Id String id;
  String firstname;
  String lastname;
  @Version Long version;
}

Person daenerys = template.insert(new Person("Daenerys"));                           (1)

Person tmp = teplate.findOne(query(where("id").is(daenerys.getId())), Person.class); (2)

daenerys.setLastname("Targaryen");
template.save(daenerys);                                                             (3)

template.save(tmp); // throws OptimisticLockingFailureException                      (4)
1 Intially insert document. version is set to 0.
2 Load the just inserted document version is still 0.
3 Update document with version = 0. Set the lastname and bump version to 1.
4 Try to update previously loaded document sill having version = 0 fails with OptimisticLockingFailureException as the current version is 1.
Using MongoDB driver version 3 requires to set the WriteConcern to ACKNOWLEDGED. Otherwise OptimisticLockingFailureException can be silently swallowed.

9.6. Querying Documents

You can express your queries using the Query and Criteria classes which have method names that mirror the native MongoDB operator names such as lt, lte, is, and others. The Query and Criteria classes follow a fluent API style so that you can easily chain together multiple method criteria and queries while having easy to understand the code. Static imports in Java are used to help remove the need to see the 'new' keyword for creating Query and Criteria instances so as to improve readability. If you like to create Query instances from a plain JSON String use BasicQuery.

Example 53. Creating a Query instance from a plain JSON String
BasicQuery query = new BasicQuery("{ age : { $lt : 50 }, accounts.balance : { $gt : 1000.00 }}");
List<Person> result = mongoTemplate.find(query, Person.class);

GeoSpatial queries are also supported and are described more in the section GeoSpatial Queries.

Map-Reduce operations are also supported and are described more in the section Map-Reduce.

9.6.1. Querying documents in a collection

We saw how to retrieve a single document using the findOne and findById methods on MongoTemplate in previous sections which return a single domain object. We can also query for a collection of documents to be returned as a list of domain objects. Assuming that we have a number of Person objects with name and age stored as documents in a collection and that each person has an embedded account document with a balance. We can now run a query using the following code.

Example 54. Querying for documents using the MongoTemplate
import static org.springframework.data.mongodb.core.query.Criteria.where;
import static org.springframework.data.mongodb.core.query.Query.query;

…

List<Person> result = mongoTemplate.find(query(where("age").lt(50)
  .and("accounts.balance").gt(1000.00d)), Person.class);

All find methods take a Query object as a parameter. This object defines the criteria and options used to perform the query. The criteria is specified using a Criteria object that has a static factory method named where used to instantiate a new Criteria object. We recommend using a static import for org.springframework.data.mongodb.core.query.Criteria.where and Query.query to make the query more readable.

This query should return a list of Person objects that meet the specified criteria. The Criteria class has the following methods that correspond to the operators provided in MongoDB.

As you can see most methods return the Criteria object to provide a fluent style for the API.

Methods for the Criteria class
  • Criteria all (Object o) Creates a criterion using the $all operator

  • Criteria and (String key) Adds a chained Criteria with the specified key to the current Criteria and returns the newly created one

  • Criteria andOperator (Criteria…​ criteria) Creates an and query using the $and operator for all of the provided criteria (requires MongoDB 2.0 or later)

  • Criteria elemMatch (Criteria c) Creates a criterion using the $elemMatch operator

  • Criteria exists (boolean b) Creates a criterion using the $exists operator

  • Criteria gt (Object o) Creates a criterion using the $gt operator

  • Criteria gte (Object o) Creates a criterion using the $gte operator

  • Criteria in (Object…​ o) Creates a criterion using the $in operator for a varargs argument.

  • Criteria in (Collection<?> collection) Creates a criterion using the $in operator using a collection

  • Criteria is (Object o) Creates a criterion using the $is operator

  • Criteria lt (Object o) Creates a criterion using the $lt operator

  • Criteria lte (Object o) Creates a criterion using the $lte operator

  • Criteria mod (Number value, Number remainder) Creates a criterion using the $mod operator

  • Criteria ne (Object o) Creates a criterion using the $ne operator

  • Criteria nin (Object…​ o) Creates a criterion using the $nin operator

  • Criteria norOperator (Criteria…​ criteria) Creates an nor query using the $nor operator for all of the provided criteria

  • Criteria not () Creates a criterion using the $not meta operator which affects the clause directly following

  • Criteria orOperator (Criteria…​ criteria) Creates an or query using the $or operator for all of the provided criteria

  • Criteria regex (String re) Creates a criterion using a $regex

  • Criteria size (int s) Creates a criterion using the $size operator

  • Criteria type (int t) Creates a criterion using the $type operator

There are also methods on the Criteria class for geospatial queries. Here is a listing but look at the section on GeoSpatial Queries to see them in action.

  • Criteria within (Circle circle) Creates a geospatial criterion using $geoWithin $center operators.

  • Criteria within (Box box) Creates a geospatial criterion using a $geoWithin $box operation.

  • Criteria withinSphere (Circle circle) Creates a geospatial criterion using $geoWithin $center operators.

  • Criteria near (Point point) Creates a geospatial criterion using a $near operation

  • Criteria nearSphere (Point point) Creates a geospatial criterion using $nearSphere$center operations. This is only available for MongoDB 1.7 and higher.

  • Criteria minDistance (double minDistance) Creates a geospatial criterion using the $minDistance operation, for use with $near.

  • Criteria maxDistance (double maxDistance) Creates a geospatial criterion using the $maxDistance operation, for use with $near.

The Query class has some additional methods used to provide options for the query.

Methods for the Query class
  • Query addCriteria (Criteria criteria) used to add additional criteria to the query

  • Field fields () used to define fields to be included in the query results

  • Query limit (int limit) used to limit the size of the returned results to the provided limit (used for paging)

  • Query skip (int skip) used to skip the provided number of documents in the results (used for paging)

  • Query with (Sort sort) used to provide sort definition for the results

9.6.2. Methods for querying for documents

The query methods need to specify the target type T that will be returned and they are also overloaded with an explicit collection name for queries that should operate on a collection other than the one indicated by the return type.

  • findAll Query for a list of objects of type T from the collection.

  • findOne Map the results of an ad-hoc query on the collection to a single instance of an object of the specified type.

  • findById Return an object of the given id and target class.

  • find Map the results of an ad-hoc query on the collection to a List of the specified type.

  • findAndRemove Map the results of an ad-hoc query on the collection to a single instance of an object of the specified type. The first document that matches the query is returned and also removed from the collection in the database.

9.6.3. GeoSpatial Queries

MongoDB supports GeoSpatial queries through the use of operators such as $near, $within, geoWithin and $nearSphere. Methods specific to geospatial queries are available on the Criteria class. There are also a few shape classes, Box, Circle, and Point that are used in conjunction with geospatial related Criteria methods.

To understand how to perform GeoSpatial queries we will use the following Venue class taken from the integration tests which relies on using the rich MappingMongoConverter.

@Document(collection="newyork")
public class Venue {

  @Id
  private String id;
  private String name;
  private double[] location;

  @PersistenceConstructor
  Venue(String name, double[] location) {
    super();
    this.name = name;
    this.location = location;
  }

  public Venue(String name, double x, double y) {
    super();
    this.name = name;
    this.location = new double[] { x, y };
  }

  public String getName() {
    return name;
  }

  public double[] getLocation() {
    return location;
  }

  @Override
  public String toString() {
    return "Venue [id=" + id + ", name=" + name + ", location="
        + Arrays.toString(location) + "]";
  }
}

To find locations within a Circle, the following query can be used.

Circle circle = new Circle(-73.99171, 40.738868, 0.01);
List<Venue> venues =
    template.find(new Query(Criteria.where("location").within(circle)), Venue.class);

To find venues within a Circle using spherical coordinates the following query can be used

Circle circle = new Circle(-73.99171, 40.738868, 0.003712240453784);
List<Venue> venues =
    template.find(new Query(Criteria.where("location").withinSphere(circle)), Venue.class);

To find venues within a Box the following query can be used

//lower-left then upper-right
Box box = new Box(new Point(-73.99756, 40.73083), new Point(-73.988135, 40.741404));
List<Venue> venues =
    template.find(new Query(Criteria.where("location").within(box)), Venue.class);

To find venues near a Point, the following queries can be used

Point point = new Point(-73.99171, 40.738868);
List<Venue> venues =
    template.find(new Query(Criteria.where("location").near(point).maxDistance(0.01)), Venue.class);
Point point = new Point(-73.99171, 40.738868);
List<Venue> venues =
    template.find(new Query(Criteria.where("location").near(point).minDistance(0.01).maxDistance(100)), Venue.class);

To find venues near a Point using spherical coordinates the following query can be used

Point point = new Point(-73.99171, 40.738868);
List<Venue> venues =
    template.find(new Query(
        Criteria.where("location").nearSphere(point).maxDistance(0.003712240453784)),
        Venue.class);
Geo near queries

MongoDB supports querying the database for geo locations and calculation the distance from a given origin at the very same time. With geo-near queries it’s possible to express queries like: "find all restaurants in the surrounding 10 miles". To do so MongoOperations provides geoNear(…) methods taking a NearQuery as argument as well as the already familiar entity type and collection

Point location = new Point(-73.99171, 40.738868);
NearQuery query = NearQuery.near(location).maxDistance(new Distance(10, Metrics.MILES));

GeoResults<Restaurant> = operations.geoNear(query, Restaurant.class);

As you can see we use the NearQuery builder API to set up a query to return all Restaurant instances surrounding the given Point by 10 miles maximum. The Metrics enum used here actually implements an interface so that other metrics could be plugged into a distance as well. A Metric is backed by a multiplier to transform the distance value of the given metric into native distances. The sample shown here would consider the 10 to be miles. Using one of the pre-built in metrics (miles and kilometers) will automatically trigger the spherical flag to be set on the query. If you want to avoid that, simply hand in plain double values into maxDistance(…). For more information see the JavaDoc of NearQuery and Distance.

The geo near operations return a GeoResults wrapper object that encapsulates GeoResult instances. The wrapping GeoResults allows accessing the average distance of all results. A single GeoResult object simply carries the entity found plus its distance from the origin.

9.6.4. GeoJSON Support

MongoDB supports GeoJSON and simple (legacy) coordinate pairs for geospatial data. Those formats can both be used for storing as well as querying data.

Please refer to the MongoDB manual on GeoJSON support to learn about requirements and restrictions.
GeoJSON types in domain classes

Usage of GeoJSON types in domain classes is straight forward. The org.springframework.data.mongodb.core.geo package contains types like GeoJsonPoint, GeoJsonPolygon and others. Those are extensions to the existing org.springframework.data.geo types.

public class Store {

	String id;

	/**
	 * location is stored in GeoJSON format.
	 * {
	 *   "type" : "Point",
	 *   "coordinates" : [ x, y ]
	 * }
	 */
	GeoJsonPoint location;
}
GeoJSON types in repository query methods

Using GeoJSON types as repository query parameters forces usage of the $geometry operator when creating the query.

public interface StoreRepository extends CrudRepository<Store, String> {

	List<Store> findByLocationWithin(Polygon polygon);  (1)

}

/*
 * {
 *   "location": {
 *     "$geoWithin": {
 *       "$geometry": {
 *         "type": "Polygon",
 *         "coordinates": [
 *           [
 *             [-73.992514,40.758934],
 *             [-73.961138,40.760348],
 *             [-73.991658,40.730006],
 *             [-73.992514,40.758934]
 *           ]
 *         ]
 *       }
 *     }
 *   }
 * }
 */
repo.findByLocationWithin(                              (2)
  new GeoJsonPolygon(
    new Point(-73.992514, 40.758934),
    new Point(-73.961138, 40.760348),
    new Point(-73.991658, 40.730006),
    new Point(-73.992514, 40.758934)));                 (3)

/*
 * {
 *   "location" : {
 *     "$geoWithin" : {
 *        "$polygon" : [ [-73.992514,40.758934] , [-73.961138,40.760348] , [-73.991658,40.730006] ]
 *     }
 *   }
 * }
 */
repo.findByLocationWithin(                              (4)
  new Polygon(
    new Point(-73.992514, 40.758934),
    new Point(-73.961138, 40.760348),
    new Point(-73.991658, 40.730006));
1 Repository method definition using the commons type allows calling it with both GeoJSON and legacy format.
2 Use GeoJSON type the make use of $geometry operator.
3 Plase note that GeoJSON polygons need the define a closed ring.
4 Use legacy format $polygon operator.

9.6.5. Full Text Queries

Since MongoDB 2.6 full text queries can be executed using the $text operator. Methods and operations specific for full text queries are available in TextQuery and TextCriteria. When doing full text search please refer to the MongoDB reference for its behavior and limitations.

Before we are actually able to use full text search we have to ensure to set up the search index correctly. Please refer to section Text Index for creating index structures.

db.foo.createIndex(
{
  title : "text",
  content : "text"
},
{
  weights : {
              title : 3
            }
}
)

A query searching for coffee cake, sorted by relevance according to the weights can be defined and executed as:

Query query = TextQuery.searching(new TextCriteria().matchingAny("coffee", "cake")).sortByScore();
List<Document> page = template.find(query, Document.class);

Exclusion of search terms can directly be done by prefixing the term with - or using notMatching

// search for 'coffee' and not 'cake'
TextQuery.searching(new TextCriteria().matching("coffee").matching("-cake"));
TextQuery.searching(new TextCriteria().matching("coffee").notMatching("cake"));

As TextCriteria.matching takes the provided term as is. Therefore phrases can be defined by putting them between double quotes (eg. \"coffee cake\") or using TextCriteria.phrase.

// search for phrase 'coffee cake'
TextQuery.searching(new TextCriteria().matching("\"coffee cake\""));
TextQuery.searching(new TextCriteria().phrase("coffee cake"));

9.7. Query by Example

9.7.1. Introduction

This chapter will give you an introduction to Query by Example and explain how to use Examples.

Query by Example (QBE) is a user-friendly querying technique with a simple interface. It allows dynamic query creation and does not require to write queries containing field names. In fact, Query by Example does not require to write queries using store-specific query languages at all.

9.7.2. Usage

The Query by Example API consists of three parts:

  • Probe: That is the actual example of a domain object with populated fields.

  • ExampleMatcher: The ExampleMatcher carries details on how to match particular fields. It can be reused across multiple Examples.

  • Example: An Example consists of the probe and the ExampleMatcher. It is used to create the query.

Query by Example is suited for several use-cases but also comes with limitations:

When to use

  • Querying your data store with a set of static or dynamic constraints

  • Frequent refactoring of the domain objects without worrying about breaking existing queries

  • Works independently from the underlying data store API

Limitations

  • Query predicates are combined using the AND keyword

  • No support for nested/grouped property constraints like firstname = ?0 or (firstname = ?1 and lastname = ?2)

  • Only supports starts/contains/ends/regex matching for strings and exact matching for other property types

Before getting started with Query by Example, you need to have a domain object. To get started, simply create an interface for your repository:

Example 55. Sample Person object
public class Person {

  @Id
  private String id;
  private String firstname;
  private String lastname;
  private Address address;

  // … getters and setters omitted
}

This is a simple domain object. You can use it to create an Example. By default, fields having null values are ignored, and strings are matched using the store specific defaults. Examples can be built by either using the of factory method or by using ExampleMatcher. Example is immutable.

Example 56. Simple Example
Person person = new Person();                         (1)
person.setFirstname("Dave");                          (2)

Example<Person> example = Example.of(person);         (3)
1 Create a new instance of the domain object
2 Set the properties to query
3 Create the Example

Examples are ideally be executed with repositories. To do so, let your repository interface extend QueryByExampleExecutor<T>. Here’s an excerpt from the QueryByExampleExecutor interface:

Example 57. The QueryByExampleExecutor
public interface QueryByExampleExecutor<T> {

  <S extends T> S findOne(Example<S> example);

  <S extends T> Iterable<S> findAll(Example<S> example);

  // … more functionality omitted.
}

You can read more about Query by Example Execution below.

9.7.3. Example matchers

Examples are not limited to default settings. You can specify own defaults for string matching, null handling and property-specific settings using the ExampleMatcher.

Example 58. Example matcher with customized matching
Person person = new Person();                          (1)
person.setFirstname("Dave");                           (2)

ExampleMatcher matcher = ExampleMatcher.matching()     (3)
  .withIgnorePaths("lastname")                         (4)
  .withIncludeNullValues()                             (5)
  .withStringMatcherEnding();                          (6)

Example<Person> example = Example.of(person, matcher); (7)
1 Create a new instance of the domain object.
2 Set properties.
3 Create an ExampleMatcher which is usable at this stage even without further configuration.
4 Construct a new ExampleMatcher to ignore the property path lastname.
5 Construct a new ExampleMatcher to ignore the property path lastname and to include null values.
6 Construct a new ExampleMatcher to ignore the property path lastname, to include null values, and use perform suffix string matching.
7 Create a new Example based on the domain object and the configured ExampleMatcher.

You can specify behavior for individual properties (e.g. "firstname" and "lastname", "address.city" for nested properties). You can tune it with matching options and case sensitivity.

Example 59. Configuring matcher options
ExampleMatcher matcher = ExampleMatcher.matching()
  .withMatcher("firstname", endsWith())
  .withMatcher("lastname", startsWith().ignoreCase());
}

Another style to configure matcher options is by using Java 8 lambdas. This approach is a callback that asks the implementor to modify the matcher. It’s not required to return the matcher because configuration options are held within the matcher instance.

Example 60. Configuring matcher options with lambdas
ExampleMatcher matcher = ExampleMatcher.matching()
  .withMatcher("firstname", match -> match.endsWith())
  .withMatcher("firstname", match -> match.startsWith());
}

Queries created by Example use a merged view of the configuration. Default matching settings can be set at ExampleMatcher level while individual settings can be applied to particular property paths. Settings that are set on ExampleMatcher are inherited by property path settings unless they are defined explicitly. Settings on a property patch have higher precedence than default settings.

Table 2. Scope of ExampleMatcher settings
Setting Scope

Null-handling

ExampleMatcher

String matching

ExampleMatcher and property path

Ignoring properties

Property path

Case sensitivity

ExampleMatcher and property path

Value transformation

Property path

9.7.4. Executing an example

Example 61. Query by Example using a Repository
public interface PersonRepository extends QueryByExampleExecutor<Person> {

}

public class PersonService {

  @Autowired PersonRepository personRepository;

  public List<Person> findPeople(Person probe) {
    return personRepository.findAll(Example.of(probe));
  }
}

An Example containing an untyped ExampleSpec uses the Repository type and its collection name. Typed ExampleSpec use their type as result type and the collection name from the Repository.

When including null values in the ExampleSpec Spring Data Mongo uses embedded document matching instead of dot notation property matching. This forces exact document matching for all property values and the property order in the embedded document.

Spring Data MongoDB provides support for the following matching options:

Table 3. StringMatcher options
Matching Logical result

DEFAULT (case-sensitive)

{"firstname" : firstname}

DEFAULT (case-insensitive)

{"firstname" : { $regex: firstname, $options: 'i'}}

EXACT (case-sensitive)

{"firstname" : { $regex: /^firstname$/}}

EXACT (case-insensitive)

{"firstname" : { $regex: /^firstname$/, $options: 'i'}}

STARTING (case-sensitive)

{"firstname" : { $regex: /^firstname/}}

STARTING (case-insensitive)

{"firstname" : { $regex: /^firstname/, $options: 'i'}}

ENDING (case-sensitive)

{"firstname" : { $regex: /firstname$/}}

ENDING (case-insensitive)

{"firstname" : { $regex: /firstname$/, $options: 'i'}}

CONTAINING (case-sensitive)

{"firstname" : { $regex: /.*firstname.*/}}

CONTAINING (case-insensitive)

{"firstname" : { $regex: /.*firstname.*/, $options: 'i'}}

REGEX (case-sensitive)

{"firstname" : { $regex: /firstname/}}

REGEX (case-insensitive)

{"firstname" : { $regex: /firstname/, $options: 'i'}}

9.8. Map-Reduce Operations

You can query MongoDB using Map-Reduce which is useful for batch processing, data aggregation, and for when the query language doesn’t fulfill your needs.

Spring provides integration with MongoDB’s map reduce by providing methods on MongoOperations to simplify the creation and execution of Map-Reduce operations. It can convert the results of a Map-Reduce operation to a POJO also integrates with Spring’s Resource abstraction abstraction. This will let you place your JavaScript files on the file system, classpath, http server or any other Spring Resource implementation and then reference the JavaScript resources via an easy URI style syntax, e.g. 'classpath:reduce.js;. Externalizing JavaScript code in files is often preferable to embedding them as Java strings in your code. Note that you can still pass JavaScript code as Java strings if you prefer.

9.8.1. Example Usage

To understand how to perform Map-Reduce operations an example from the book 'MongoDB - The definitive guide' is used. In this example we will create three documents that have the values [a,b], [b,c], and [c,d] respectfully. The values in each document are associated with the key 'x' as shown below. For this example assume these documents are in the collection named "jmr1".

{ "_id" : ObjectId("4e5ff893c0277826074ec533"), "x" : [ "a", "b" ] }
{ "_id" : ObjectId("4e5ff893c0277826074ec534"), "x" : [ "b", "c" ] }
{ "_id" : ObjectId("4e5ff893c0277826074ec535"), "x" : [ "c", "d" ] }

A map function that will count the occurrence of each letter in the array for each document is shown below

function () {
    for (var i = 0; i < this.x.length; i++) {
        emit(this.x[i], 1);
    }
}

The reduce function that will sum up the occurrence of each letter across all the documents is shown below

function (key, values) {
    var sum = 0;
    for (var i = 0; i < values.length; i++)
        sum += values[i];
    return sum;
}

Executing this will result in a collection as shown below.

{ "_id" : "a", "value" : 1 }
{ "_id" : "b", "value" : 2 }
{ "_id" : "c", "value" : 2 }
{ "_id" : "d", "value" : 1 }

Assuming that the map and reduce functions are located in map.js and reduce.js and bundled in your jar so they are available on the classpath, you can execute a map-reduce operation and obtain the results as shown below

MapReduceResults<ValueObject> results = mongoOperations.mapReduce("jmr1", "classpath:map.js", "classpath:reduce.js", ValueObject.class);
for (ValueObject valueObject : results) {
  System.out.println(valueObject);
}

The output of the above code is

ValueObject [id=a, value=1.0]
ValueObject [id=b, value=2.0]
ValueObject [id=c, value=2.0]
ValueObject [id=d, value=1.0]

The MapReduceResults class implements Iterable and provides access to the raw output, as well as timing and count statistics. The ValueObject class is simply

public class ValueObject {

  private String id;
  private float value;

  public String getId() {
    return id;
  }

  public float getValue() {
    return value;
  }

  public void setValue(float value) {
    this.value = value;
  }

  @Override
  public String toString() {
    return "ValueObject [id=" + id + ", value=" + value + "]";
  }
}

By default the output type of INLINE is used so you don’t have to specify an output collection. To specify additional map-reduce options use an overloaded method that takes an additional MapReduceOptions argument. The class MapReduceOptions has a fluent API so adding additional options can be done in a very compact syntax. Here an example that sets the output collection to "jmr1_out". Note that setting only the output collection assumes a default output type of REPLACE.

MapReduceResults<ValueObject> results = mongoOperations.mapReduce("jmr1", "classpath:map.js", "classpath:reduce.js",
                                                                     new MapReduceOptions().outputCollection("jmr1_out"), ValueObject.class);

There is also a static import import static org.springframework.data.mongodb.core.mapreduce.MapReduceOptions.options; that can be used to make the syntax slightly more compact

MapReduceResults<ValueObject> results = mongoOperations.mapReduce("jmr1", "classpath:map.js", "classpath:reduce.js",
                                                                     options().outputCollection("jmr1_out"), ValueObject.class);

You can also specify a query to reduce the set of data that will be used to feed into the map-reduce operation. This will remove the document that contains [a,b] from consideration for map-reduce operations.

Query query = new Query(where("x").ne(new String[] { "a", "b" }));
MapReduceResults<ValueObject> results = mongoOperations.mapReduce(query, "jmr1", "classpath:map.js", "classpath:reduce.js",
                                                                     options().outputCollection("jmr1_out"), ValueObject.class);

Note that you can specify additional limit and sort values as well on the query but not skip values.

9.9. Script Operations

MongoDB allows executing JavaScript functions on the server by either directly sending the script or calling a stored one. ScriptOperations can be accessed via MongoTemplate and provides basic abstraction for JavaScript usage.

9.9.1. Example Usage

ScriptOperations scriptOps = template.scriptOps();

ExecutableMongoScript echoScript = new ExecutableMongoScript("function(x) { return x; }");
scriptOps.execute(echoScript, "directly execute script");     (1)

scriptOps.register(new NamedMongoScript("echo", echoScript)); (2)
scriptOps.call("echo", "execute script via name");            (3)
1 Execute the script directly without storing the function on server side.
2 Store the script using 'echo' as its name. The given name identifies the script and allows calling it later.
3 Execute the script with name 'echo' using the provided parameters.

9.10. Group Operations

As an alternative to using Map-Reduce to perform data aggregation, you can use the group operation which feels similar to using SQL’s group by query style, so it may feel more approachable vs. using Map-Reduce. Using the group operations does have some limitations, for example it is not supported in a shared environment and it returns the full result set in a single BSON object, so the result should be small, less than 10,000 keys.

Spring provides integration with MongoDB’s group operation by providing methods on MongoOperations to simplify the creation and execution of group operations. It can convert the results of the group operation to a POJO and also integrates with Spring’s Resource abstraction abstraction. This will let you place your JavaScript files on the file system, classpath, http server or any other Spring Resource implementation and then reference the JavaScript resources via an easy URI style syntax, e.g. 'classpath:reduce.js;. Externalizing JavaScript code in files if often preferable to embedding them as Java strings in your code. Note that you can still pass JavaScript code as Java strings if you prefer.

9.10.1. Example Usage

In order to understand how group operations work the following example is used, which is somewhat artificial. For a more realistic example consult the book 'MongoDB - The definitive guide'. A collection named group_test_collection created with the following rows.

{ "_id" : ObjectId("4ec1d25d41421e2015da64f1"), "x" : 1 }
{ "_id" : ObjectId("4ec1d25d41421e2015da64f2"), "x" : 1 }
{ "_id" : ObjectId("4ec1d25d41421e2015da64f3"), "x" : 2 }
{ "_id" : ObjectId("4ec1d25d41421e2015da64f4"), "x" : 3 }
{ "_id" : ObjectId("4ec1d25d41421e2015da64f5"), "x" : 3 }
{ "_id" : ObjectId("4ec1d25d41421e2015da64f6"), "x" : 3 }

We would like to group by the only field in each row, the x field and aggregate the number of times each specific value of x occurs. To do this we need to create an initial document that contains our count variable and also a reduce function which will increment it each time it is encountered. The Java code to execute the group operation is shown below

GroupByResults<XObject> results = mongoTemplate.group("group_test_collection",
                                                      GroupBy.key("x").initialDocument("{ count: 0 }").reduceFunction("function(doc, prev) { prev.count += 1 }"),
                                                      XObject.class);

The first argument is the name of the collection to run the group operation over, the second is a fluent API that specifies properties of the group operation via a GroupBy class. In this example we are using just the intialDocument and reduceFunction methods. You can also specify a key-function, as well as a finalizer as part of the fluent API. If you have multiple keys to group by, you can pass in a comma separated list of keys.

The raw results of the group operation is a JSON document that looks like this

{
  "retval" : [ { "x" : 1.0 , "count" : 2.0} ,
               { "x" : 2.0 , "count" : 1.0} ,
               { "x" : 3.0 , "count" : 3.0} ] ,
  "count" : 6.0 ,
  "keys" : 3 ,
  "ok" : 1.0
}

The document under the "retval" field is mapped onto the third argument in the group method, in this case XObject which is shown below.

public class XObject {

  private float x;

  private float count;


  public float getX() {
    return x;
  }

  public void setX(float x) {
    this.x = x;
  }

  public float getCount() {
    return count;
  }

  public void setCount(float count) {
    this.count = count;
  }

  @Override
  public String toString() {
    return "XObject [x=" + x + " count = " + count + "]";
  }
}

You can also obtain the raw result as a DbObject by calling the method getRawResults on the GroupByResults class.

There is an additional method overload of the group method on MongoOperations which lets you specify a Criteria object for selecting a subset of the rows. An example which uses a Criteria object, with some syntax sugar using static imports, as well as referencing a key-function and reduce function javascript files via a Spring Resource string is shown below.

import static org.springframework.data.mongodb.core.mapreduce.GroupBy.keyFunction;
import static org.springframework.data.mongodb.core.query.Criteria.where;

GroupByResults<XObject> results = mongoTemplate.group(where("x").gt(0),
                                        "group_test_collection",
                                        keyFunction("classpath:keyFunction.js").initialDocument("{ count: 0 }").reduceFunction("classpath:groupReduce.js"), XObject.class);

9.11. Aggregation Framework Support

Spring Data MongoDB provides support for the Aggregation Framework introduced to MongoDB in version 2.2.

The MongoDB Documentation describes the Aggregation Framework as follows:

For further information see the full reference documentation of the aggregation framework and other data aggregation tools for MongoDB.

9.11.1. Basic Concepts

The Aggregation Framework support in Spring Data MongoDB is based on the following key abstractions Aggregation, AggregationOperation and AggregationResults.

  • Aggregation

    An Aggregation represents a MongoDB aggregate operation and holds the description of the aggregation pipeline instructions. Aggregations are created by invoking the appropriate newAggregation(…) static factory Method of the Aggregation class which takes the list of AggregateOperation as a parameter next to the optional input class.

    The actual aggregate operation is executed by the aggregate method of the MongoTemplate which also takes the desired output class as parameter.

  • AggregationOperation

    An AggregationOperation represents a MongoDB aggregation pipeline operation and describes the processing that should be performed in this aggregation step. Although one could manually create an AggregationOperation the recommended way to construct an AggregateOperation is to use the static factory methods provided by the Aggregate class.

  • AggregationResults

    AggregationResults is the container for the result of an aggregate operation. It provides access to the raw aggregation result in the form of an DBObject, to the mapped objects and information which performed the aggregation.

    The canonical example for using the Spring Data MongoDB support for the MongoDB Aggregation Framework looks as follows:

import static org.springframework.data.mongodb.core.aggregation.Aggregation.*;

Aggregation agg = newAggregation(
    pipelineOP1(),
    pipelineOP2(),
    pipelineOPn()
);

AggregationResults<OutputType> results = mongoTemplate.aggregate(agg, "INPUT_COLLECTION_NAME", OutputType.class);
List<OutputType> mappedResult = results.getMappedResults();

Note that if you provide an input class as the first parameter to the newAggregation method the MongoTemplate will derive the name of the input collection from this class. Otherwise if you don’t not specify an input class you must provide the name of the input collection explicitly. If an input-class and an input-collection is provided the latter takes precedence.

9.11.2. Supported Aggregation Operations

The MongoDB Aggregation Framework provides the following types of Aggregation Operations:

  • Pipeline Aggregation Operators

  • Group Aggregation Operators

  • Boolean Aggregation Operators

  • Comparison Aggregation Operators

  • Arithmetic Aggregation Operators

  • String Aggregation Operators

  • Date Aggregation Operators

  • Conditional Aggregation Operators

  • Lookup Aggregation Operators

At the time of this writing we provide support for the following Aggregation Operations in Spring Data MongoDB.

Table 4. Aggregation Operations currently supported by Spring Data MongoDB

Pipeline Aggregation Operators

project, skip, limit, lookup, unwind, group, sort, geoNear

Group Aggregation Operators

addToSet, first, last, max, min, avg, push, sum, (*count)

Arithmetic Aggregation Operators

add (*via plus), subtract (*via minus), multiply, divide, mod

Comparison Aggregation Operators

eq (*via: is), gt, gte, lt, lte, ne

Note that the aggregation operations not listed here are currently not supported by Spring Data MongoDB. Comparison aggregation operators are expressed as Criteria expressions.

*) The operation is mapped or added by Spring Data MongoDB.

9.11.3. Projection Expressions

Projection expressions are used to define the fields that are the outcome of a particular aggregation step. Projection expressions can be defined via the project method of the Aggregate class either by passing a list of String 's or an aggregation framework Fields object. The projection can be extended with additional fields through a fluent API via the and(String) method and aliased via the as(String) method. Note that one can also define fields with aliases via the static factory method Fields.field of the aggregation framework that can then be used to construct a new Fields instance.

Example 62. Projection expression examples
project("name", "netPrice") // will generate {$project: {name: 1, netPrice: 1}}
project().and("foo").as("bar") // will generate {$project: {bar: $foo}}
project("a","b").and("foo").as("bar") // will generate {$project: {a: 1, b: 1, bar: $foo}}

Note that more examples for project operations can be found in the AggregationTests class.

Note that further details regarding the projection expressions can be found in the corresponding section of the MongoDB Aggregation Framework reference documentation.

Spring Expression Support in Projection Expressions

As of Version 1.4.0 we support the use of SpEL expression in projection expressions via the andExpression method of the ProjectionOperation class. This allows you to define the desired expression as a SpEL expression which is translated into a corresponding MongoDB projection expression part on query execution. This makes it much easier to express complex calculations.

Complex calculations with SpEL expressions

The following SpEL expression:

1 + (q + 1) / (q - 1)

will be translated into the following projection expression part:

{ "$add" : [ 1, {
    "$divide" : [ {
        "$add":["$q", 1]}, {
        "$subtract":[ "$q", 1]}
    ]
}]}

Have a look at an example in more context in Aggregation Framework Example 5 and Aggregation Framework Example 6. You can find more usage examples for supported SpEL expression constructs in SpelExpressionTransformerUnitTests.

Aggregation Framework Examples

The following examples demonstrate the usage patterns for the MongoDB Aggregation Framework with Spring Data MongoDB.

Aggregation Framework Example 1

In this introductory example we want to aggregate a list of tags to get the occurrence count of a particular tag from a MongoDB collection called "tags" sorted by the occurrence count in descending order. This example demonstrates the usage of grouping, sorting, projections (selection) and unwinding (result splitting).

class TagCount {
 String tag;
 int n;
}
import static org.springframework.data.mongodb.core.aggregation.Aggregation.*;

Aggregation agg = newAggregation(
    project("tags"),
    unwind("tags"),
    group("tags").count().as("n"),
    project("n").and("tag").previousOperation(),
    sort(DESC, "n")
);

AggregationResults<TagCount> results = mongoTemplate.aggregate(agg, "tags", TagCount.class);
List<TagCount> tagCount = results.getMappedResults();
  • In order to do this we first create a new aggregation via the newAggregation static factory method to which we pass a list of aggregation operations. These aggregate operations define the aggregation pipeline of our Aggregation.

  • As a second step we select the "tags" field (which is an array of strings) from the input collection with the project operation.

  • In a third step we use the unwind operation to generate a new document for each tag within the "tags" array.

  • In the forth step we use the group operation to define a group for each "tags"-value for which we aggregate the occurrence count via the count aggregation operator and collect the result in a new field called "n".

  • As a fifth step we select the field "n" and create an alias for the id-field generated from the previous group operation (hence the call to previousOperation()) with the name "tag".

  • As the sixth step we sort the resulting list of tags by their occurrence count in descending order via the sort operation.

  • Finally we call the aggregate Method on the MongoTemplate in order to let MongoDB perform the actual aggregation operation with the created Aggregation as an argument.

Note that the input collection is explicitly specified as the "tags" parameter to the aggregate Method. If the name of the input collection is not specified explicitly, it is derived from the input-class passed as first parameter to the newAggreation Method.

Aggregation Framework Example 2

This example is based on the Largest and Smallest Cities by State example from the MongoDB Aggregation Framework documentation. We added additional sorting to produce stable results with different MongoDB versions. Here we want to return the smallest and largest cities by population for each state, using the aggregation framework. This example demonstrates the usage of grouping, sorting and projections (selection).

class ZipInfo {
   String id;
   String city;
   String state;
   @Field("pop") int population;
   @Field("loc") double[] location;
}

class City {
   String name;
   int population;
}

class ZipInfoStats {
   String id;
   String state;
   City biggestCity;
   City smallestCity;
}
import static org.springframework.data.mongodb.core.aggregation.Aggregation.*;

TypedAggregation<ZipInfo> aggregation = newAggregation(ZipInfo.class,
    group("state", "city")
       .sum("population").as("pop"),
    sort(ASC, "pop", "state", "city"),
    group("state")
       .last("city").as("biggestCity")
       .last("pop").as("biggestPop")
       .first("city").as("smallestCity")
       .first("pop").as("smallestPop"),
    project()
       .and("state").previousOperation()
       .and("biggestCity")
          .nested(bind("name", "biggestCity").and("population", "biggestPop"))
       .and("smallestCity")
          .nested(bind("name", "smallestCity").and("population", "smallestPop")),
    sort(ASC, "state")
);

AggregationResults<ZipInfoStats> result = mongoTemplate.aggregate(aggregation, ZipInfoStats.class);
ZipInfoStats firstZipInfoStats = result.getMappedResults().get(0);
  • The class ZipInfo maps the structure of the given input-collection. The class ZipInfoStats defines the structure in the desired output format.

  • As a first step we use the group operation to define a group from the input-collection. The grouping criteria is the combination of the fields "state" and "city" which forms the id structure of the group. We aggregate the value of the "population" property from the grouped elements with by using the sum operator saving the result in the field "pop".

  • In a second step we use the sort operation to sort the intermediate-result by the fields "pop", "state" and "city" in ascending order, such that the smallest city is at the top and the biggest city is at the bottom of the result. Note that the sorting on "state" and "city" is implicitly performed against the group id fields which Spring Data MongoDB took care of.

  • In the third step we use a group operation again to group the intermediate result by "state". Note that "state" again implicitly references an group-id field. We select the name and the population count of the biggest and smallest city with calls to the last(…) and first(…​) operator respectively via the project operation.

  • As the forth step we select the "state" field from the previous group operation. Note that "state" again implicitly references an group-id field. As we do not want an implicitly generated id to appear, we exclude the id from the previous operation via and(previousOperation()).exclude(). As we want to populate the nested City structures in our output-class accordingly we have to emit appropriate sub-documents with the nested method.

  • Finally as the fifth step we sort the resulting list of StateStats by their state name in ascending order via the sort operation.

Note that we derive the name of the input-collection from the ZipInfo-class passed as first parameter to the newAggregation-Method.

Aggregation Framework Example 3

This example is based on the States with Populations Over 10 Million example from the MongoDB Aggregation Framework documentation. We added additional sorting to produce stable results with different MongoDB versions. Here we want to return all states with a population greater than 10 million, using the aggregation framework. This example demonstrates the usage of grouping, sorting and matching (filtering).

class StateStats {
   @Id String id;
   String state;
   @Field("totalPop") int totalPopulation;
}
import static org.springframework.data.mongodb.core.aggregation.Aggregation.*;

TypedAggregation<ZipInfo> agg = newAggregation(ZipInfo.class,
    group("state").sum("population").as("totalPop"),
    sort(ASC, previousOperation(), "totalPop"),
    match(where("totalPop").gte(10 * 1000 * 1000))
);

AggregationResults<StateStats> result = mongoTemplate.aggregate(agg, StateStats.class);
List<StateStats> stateStatsList = result.getMappedResults();
  • As a first step we group the input collection by the "state" field and calculate the sum of the "population" field and store the result in the new field "totalPop".

  • In the second step we sort the intermediate result by the id-reference of the previous group operation in addition to the "totalPop" field in ascending order.

  • Finally in the third step we filter the intermediate result by using a match operation which accepts a Criteria query as an argument.

Note that we derive the name of the input-collection from the ZipInfo-class passed as first parameter to the newAggregation-Method.

Aggregation Framework Example 4

This example demonstrates the use of simple arithmetic operations in the projection operation.

class Product {
    String id;
    String name;
    double netPrice;
    int spaceUnits;
}
import static org.springframework.data.mongodb.core.aggregation.Aggregation.*;

TypedAggregation<Product> agg = newAggregation(Product.class,
    project("name", "netPrice")
        .and("netPrice").plus(1).as("netPricePlus1")
        .and("netPrice").minus(1).as("netPriceMinus1")
        .and("netPrice").multiply(1.19).as("grossPrice")
        .and("netPrice").divide(2).as("netPriceDiv2")
        .and("spaceUnits").mod(2).as("spaceUnitsMod2")
);

AggregationResults<DBObject> result = mongoTemplate.aggregate(agg, DBObject.class);
List<DBObject> resultList = result.getMappedResults();

Note that we derive the name of the input-collection from the Product-class passed as first parameter to the newAggregation-Method.

Aggregation Framework Example 5

This example demonstrates the use of simple arithmetic operations derived from SpEL Expressions in the projection operation.

class Product {
    String id;
    String name;
    double netPrice;
    int spaceUnits;
}
import static org.springframework.data.mongodb.core.aggregation.Aggregation.*;

TypedAggregation<Product> agg = newAggregation(Product.class,
    project("name", "netPrice")
        .andExpression("netPrice + 1").as("netPricePlus1")
        .andExpression("netPrice - 1").as("netPriceMinus1")
        .andExpression("netPrice / 2").as("netPriceDiv2")
        .andExpression("netPrice * 1.19").as("grossPrice")
        .andExpression("spaceUnits % 2").as("spaceUnitsMod2")
        .andExpression("(netPrice * 0.8  + 1.2) * 1.19").as("grossPriceIncludingDiscountAndCharge")

);

AggregationResults<DBObject> result = mongoTemplate.aggregate(agg, DBObject.class);
List<DBObject> resultList = result.getMappedResults();
Aggregation Framework Example 6

This example demonstrates the use of complex arithmetic operations derived from SpEL Expressions in the projection operation.

Note: The additional parameters passed to the addExpression Method can be referenced via indexer expressions according to their position. In this example we reference the parameter which is the first parameter of the parameters array via [0]. External parameter expressions are replaced with their respective values when the SpEL expression is transformed into a MongoDB aggregation framework expression.

class Product {
    String id;
    String name;
    double netPrice;
    int spaceUnits;
}
import static org.springframework.data.mongodb.core.aggregation.Aggregation.*;

double shippingCosts = 1.2;

TypedAggregation<Product> agg = newAggregation(Product.class,
    project("name", "netPrice")
        .andExpression("(netPrice * (1-discountRate)  + [0]) * (1+taxRate)", shippingCosts).as("salesPrice")
);

AggregationResults<DBObject> result = mongoTemplate.aggregate(agg, DBObject.class);
List<DBObject> resultList = result.getMappedResults();

Note that we can also refer to other fields of the document within the SpEL expression.

9.12. Overriding default mapping with custom converters

In order to have more fine-grained control over the mapping process you can register Spring converters with the MongoConverter implementations such as the MappingMongoConverter.

The MappingMongoConverter checks to see if there are any Spring converters that can handle a specific class before attempting to map the object itself. To 'hijack' the normal mapping strategies of the MappingMongoConverter, perhaps for increased performance or other custom mapping needs, you first need to create an implementation of the Spring Converter interface and then register it with the MappingConverter.

For more information on the Spring type conversion service see the reference docs here.

9.12.1. Saving using a registered Spring Converter

An example implementation of the Converter that converts from a Person object to a com.mongodb.DBObject is shown below

import org.springframework.core.convert.converter.Converter;

import com.mongodb.BasicDBObject;
import com.mongodb.DBObject;

public class PersonWriteConverter implements Converter<Person, DBObject> {

  public DBObject convert(Person source) {
    DBObject dbo = new BasicDBObject();
    dbo.put("_id", source.getId());
    dbo.put("name", source.getFirstName());
    dbo.put("age", source.getAge());
    return dbo;
  }
}

9.12.2. Reading using a Spring Converter

An example implementation of a Converter that converts from a DBObject to a Person object is shown below.

public class PersonReadConverter implements Converter<DBObject, Person> {

  public Person convert(DBObject source) {
    Person p = new Person((ObjectId) source.get("_id"), (String) source.get("name"));
    p.setAge((Integer) source.get("age"));
    return p;
  }
}

9.12.3. Registering Spring Converters with the MongoConverter

The Mongo Spring namespace provides a convenience way to register Spring Converter s with the MappingMongoConverter. The configuration snippet below shows how to manually register converter beans as well as configuring the wrapping MappingMongoConverter into a MongoTemplate.

<mongo:db-factory dbname="database"/>

<mongo:mapping-converter>
  <mongo:custom-converters>
    <mongo:converter ref="readConverter"/>
    <mongo:converter>
      <bean class="org.springframework.data.mongodb.test.PersonWriteConverter"/>
    </mongo:converter>
  </mongo:custom-converters>
</mongo:mapping-converter>

<bean id="readConverter" class="org.springframework.data.mongodb.test.PersonReadConverter"/>

<bean id="mongoTemplate" class="org.springframework.data.mongodb.core.MongoTemplate">
  <constructor-arg name="mongoDbFactory" ref="mongoDbFactory"/>
  <constructor-arg name="mongoConverter" ref="mappingConverter"/>
</bean>

You can also use the base-package attribute of the custom-converters element to enable classpath scanning for all Converter and GenericConverter implementations below the given package.

<mongo:mapping-converter>
  <mongo:custom-converters base-package="com.acme.**.converters" />
</mongo:mapping-converter>

9.12.4. 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 MongoDB can handle natively we will register the converter instance as reading or writing one. Have a look at the following samples:

// Write converter as only the target type is one Mongo can handle natively
class MyConverter implements Converter<Person, String> { … }

// Read converter as only the source type is one Mongo can handle natively
class MyConverter implements Converter<String, Person> { … }

In case you write a Converter whose source and target type are native Mongo types there’s no way for us to determine whether we should consider it as reading or writing converter. Registering the converter instance as both might lead to unwanted results then. E.g. 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 be generally able to force the infrastructure to register a converter for one way only we provide @ReadingConverter as well as @WritingConverter to be used in the converter implementation.

9.13. Index and Collection management

MongoTemplate provides a few methods for managing indexes and collections. These are collected into a helper interface called IndexOperations. You access these operations by calling the method indexOps and pass in either the collection name or the java.lang.Class of your entity (the collection name will be derived from the .class either by name or via annotation metadata).

The IndexOperations interface is shown below

public interface IndexOperations {

  void ensureIndex(IndexDefinition indexDefinition);

  void dropIndex(String name);

  void dropAllIndexes();

  void resetIndexCache();

  List<IndexInfo> getIndexInfo();
}

9.13.1. Methods for creating an Index

We can create an index on a collection to improve query performance.

Creating an index using the MongoTemplate
mongoTemplate.indexOps(Person.class).ensureIndex(new Index().on("name",Order.ASCENDING));
  • ensureIndex Ensure that an index for the provided IndexDefinition exists for the collection.

You can create standard, geospatial and text indexes using the classes IndexDefinition, GeoSpatialIndex and TextIndexDefinition. For example, given the Venue class defined in a previous section, you would declare a geospatial query as shown below.

mongoTemplate.indexOps(Venue.class).ensureIndex(new GeospatialIndex("location"));

9.13.2. Accessing index information

The IndexOperations interface has the method getIndexInfo that returns a list of IndexInfo objects. This contains all the indexes defined on the collection. Here is an example that defines an index on the Person class that has age property.

template.indexOps(Person.class).ensureIndex(new Index().on("age", Order.DESCENDING).unique(Duplicates.DROP));

List<IndexInfo> indexInfoList = template.indexOps(Person.class).getIndexInfo();

// Contains
// [IndexInfo [fieldSpec={_id=ASCENDING}, name=_id_, unique=false, dropDuplicates=false, sparse=false],
//  IndexInfo [fieldSpec={age=DESCENDING}, name=age_-1, unique=true, dropDuplicates=true, sparse=false]]

9.13.3. Methods for working with a Collection

It’s time to look at some code examples showing how to use the MongoTemplate. First we look at creating our first collection.

Example 63. Working with collections using the MongoTemplate
DBCollection collection = null;
if (!mongoTemplate.getCollectionNames().contains("MyNewCollection")) {
    collection = mongoTemplate.createCollection("MyNewCollection");
}

mongoTemplate.dropCollection("MyNewCollection");
  • getCollectionNames Returns a set of collection names.

  • collectionExists Check to see if a collection with a given name exists.

  • createCollection Create an uncapped collection

  • dropCollection Drop the collection

  • getCollection Get a collection by name, creating it if it doesn’t exist.

9.14. Executing Commands

You can also get at the MongoDB driver’s DB.command( ) method using the executeCommand(…) methods on MongoTemplate. These will also perform exception translation into Spring’s DataAccessException hierarchy.

9.14.1. Methods for executing commands

  • CommandResult executeCommand (DBObject command) Execute a MongoDB command.

  • CommandResult executeCommand (String jsonCommand) Execute the a MongoDB command expressed as a JSON string.

9.15. Lifecycle Events

Built into the MongoDB mapping framework are several org.springframework.context.ApplicationEvent events that your application can respond to by registering special beans in the ApplicationContext. By being based off Spring’s ApplicationContext event infrastructure this enables other products, such as Spring Integration, to easily receive these events as they are a well known eventing mechanism in Spring based applications.

To intercept an object before it goes through the conversion process (which turns your domain object into a com.mongodb.DBObject), you’d register a subclass of AbstractMongoEventListener that overrides the onBeforeConvert method. When the event is dispatched, your listener will be called and passed the domain object before it goes into the converter.

public class BeforeConvertListener extends AbstractMongoEventListener<Person> {
  @Override
  public void onBeforeConvert(BeforeConvertEvent<Person> event) {
    ... does some auditing manipulation, set timestamps, whatever ...
  }
}

To intercept an object before it goes into the database, you’d register a subclass of org.springframework.data.mongodb.core.mapping.event.AbstractMongoEventListener that overrides the onBeforeSave method. When the event is dispatched, your listener will be called and passed the domain object and the converted com.mongodb.DBObject.

public class BeforeSaveListener extends AbstractMongoEventListener<Person> {
  @Override
  public void onBeforeSave(BeforeSaveEvent<Person> event) {
    … change values, delete them, whatever …
  }
}

Simply declaring these beans in your Spring ApplicationContext will cause them to be invoked whenever the event is dispatched.

The list of callback methods that are present in AbstractMappingEventListener are

  • onBeforeConvert - called in MongoTemplate insert, insertList and save operations before the object is converted to a DBObject using a MongoConveter.

  • onBeforeSave - called in MongoTemplate insert, insertList and save operations before inserting/saving the DBObject in the database.

  • onAfterSave - called in MongoTemplate insert, insertList and save operations after inserting/saving the DBObject in the database.

  • onAfterLoad - called in MongoTemplate find, findAndRemove, findOne and getCollection methods after the DBObject is retrieved from the database.

  • onAfterConvert - called in MongoTemplate find, findAndRemove, findOne and getCollection methods after the DBObject retrieved from the database was converted to a POJO.

9.16. Exception Translation

The Spring framework provides exception translation for a wide variety of database and mapping technologies. This has traditionally been for JDBC and JPA. The Spring support for MongoDB extends this feature to the MongoDB Database by providing an implementation of the org.springframework.dao.support.PersistenceExceptionTranslator interface.

The motivation behind mapping to Spring’s consistent data access exception hierarchy is that you are then able to write portable and descriptive exception handling code without resorting to coding against MongoDB error codes. All of Spring’s data access exceptions are inherited from the root DataAccessException class so you can be sure that you will be able to catch all database related exception within a single try-catch block. Note, that not all exceptions thrown by the MongoDB driver inherit from the MongoException class. The inner exception and message are preserved so no information is lost.

Some of the mappings performed by the MongoExceptionTranslator are: com.mongodb.Network to DataAccessResourceFailureException and MongoException error codes 1003, 12001, 12010, 12011, 12012 to InvalidDataAccessApiUsageException. Look into the implementation for more details on the mapping.

9.17. Execution callbacks

One common design feature of all Spring template classes is that all functionality is routed into one of the templates execute callback methods. This helps ensure that exceptions and any resource management that maybe required are performed consistency. While this was of much greater need in the case of JDBC and JMS than with MongoDB, it still offers a single spot for exception translation and logging to occur. As such, using these execute callback is the preferred way to access the MongoDB driver’s DB and DBCollection objects to perform uncommon operations that were not exposed as methods on MongoTemplate.

Here is a list of execute callback methods.

  • <T> T execute (Class<?> entityClass, CollectionCallback<T> action) Executes the given CollectionCallback for the entity collection of the specified class.

  • <T> T execute (String collectionName, CollectionCallback<T> action) Executes the given CollectionCallback on the collection of the given name.

  • <T> T execute (DbCallback<T> action) Spring Data MongoDB provides support for the Aggregation Framework introduced to MongoDB in version 2.2. Executes a DbCallback translating any exceptions as necessary.

  • <T> T execute (String collectionName, DbCallback<T> action) Executes a DbCallback on the collection of the given name translating any exceptions as necessary.

  • <T> T executeInSession (DbCallback<T> action) Executes the given DbCallback within the same connection to the database so as to ensure consistency in a write heavy environment where you may read the data that you wrote.

Here is an example that uses the CollectionCallback to return information about an index

boolean hasIndex = template.execute("geolocation", new CollectionCallbackBoolean>() {
  public Boolean doInCollection(Venue.class, DBCollection collection) throws MongoException, DataAccessException {
    List<DBObject> indexes = collection.getIndexInfo();
    for (DBObject dbo : indexes) {
      if ("location_2d".equals(dbo.get("name"))) {
        return true;
      }
    }
    return false;
  }
});

9.18. GridFS support

MongoDB supports storing binary files inside it’s filesystem GridFS. Spring Data MongoDB provides a GridFsOperations interface as well as the according implementation GridFsTemplate to easily interact with the filesystem. You can setup a GridFsTemplate instance by handing it a MongoDbFactory as well as a MongoConverter:

Example 64. JavaConfig setup for a GridFsTemplate
class GridFsConfiguration extends AbstractMongoConfiguration {

  // … further configuration omitted

  @Bean
  public GridFsTemplate gridFsTemplate() {
    return new GridFsTemplate(mongoDbFactory(), mappingMongoConverter());
  }
}

An according XML configuration looks like this:

Example 65. XML configuration for a GridFsTemplate
<?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:mongo="http://www.springframework.org/schema/data/mongo"
  xsi:schemaLocation="http://www.springframework.org/schema/data/mongo
                      http://www.springframework.org/schema/data/mongo/spring-mongo.xsd
                      http://www.springframework.org/schema/beans
                      http://www.springframework.org/schema/beans/spring-beans.xsd">

  <mongo:db-factory id="mongoDbFactory" dbname="database" />
  <mongo:mapping-converter id="converter" />

  <bean class="org.springframework.data.mongodb.gridfs.GridFsTemplate">
    <constructor-arg ref="mongoDbFactory" />
    <constructor-arg ref="converter" />
  </bean>

</beans>

The template can now be injected and used to perform storage and retrieval operations.

Example 66. Using GridFsTemplate to store files
class GridFsClient {

  @Autowired
  GridFsOperations operations;

  @Test
  public void storeFileToGridFs {

    FileMetadata metadata = new FileMetadata();
    // populate metadata
    Resource file = … // lookup File or Resource

    operations.store(file.getInputStream(), "filename.txt", metadata);
  }
}

The store(…) operations take an InputStream, a filename and optionally metadata information about the file to store. The metadata can be an arbitrary object which will be marshaled by the MongoConverter configured with the GridFsTemplate. Alternatively you can also provide a DBObject as well.

Reading files from the filesystem can either be achieved through the find(…) or getResources(…) methods. Let’s have a look at the find(…) methods first. You can either find a single file matching a Query or multiple ones. To easily define file queries we provide the GridFsCriteria helper class. It provides static factory methods to encapsulate default metadata fields (e.g. whereFilename(), whereContentType()) or the custom one through whereMetaData().

Example 67. Using GridFsTemplate to query for files
class GridFsClient {

  @Autowired
  GridFsOperations operations;

  @Test
  public void findFilesInGridFs {
    List<GridFSDBFile> result = operations.find(query(whereFilename().is("filename.txt")))
  }
}
Currently MongoDB does not support defining sort criteria when retrieving files from GridFS. Thus any sort criteria defined on the Query instance handed into the find(…) method will be disregarded.

The other option to read files from the GridFs is using the methods introduced by the ResourcePatternResolver interface. They allow handing an Ant path into the method ar thus retrieve files matching the given pattern.

Example 68. Using GridFsTemplate to read files
class GridFsClient {

  @Autowired
  GridFsOperations operations;

  @Test
  public void readFilesFromGridFs {
    GridFsResources[] txtFiles = operations.getResources("*.txt");
  }
}

GridFsOperations extending ResourcePatternResolver allows the GridFsTemplate e.g. to be plugged into an ApplicationContext to read Spring Config files from a MongoDB.

10. MongoDB repositories

10.1. Introduction

This chapter will point out the specialties for repository support for MongoDB. This builds on the core repository support explained in Working with Spring Data Repositories. So make sure you’ve got a sound understanding of the basic concepts explained there.

10.2. Usage

To access domain entities stored in a MongoDB you can leverage our sophisticated repository support that eases implementing those quite significantly. To do so, simply create an interface for your repository:

Example 69. Sample Person entity
public class Person {

  @Id
  private String id;
  private String firstname;
  private String lastname;
  private Address address;

  // … getters and setters omitted
}

We have a quite simple domain object here. Note that it has a property named id of type ObjectId. The default serialization mechanism used in MongoTemplate (which is backing the repository support) regards properties named id as document id. Currently we support String, ObjectId and BigInteger as id-types.

Example 70. Basic repository interface to persist Person entities
public interface PersonRepository extends PagingAndSortingRepository<Person, Long> {

  // additional custom finder methods go here
}

Right now this interface simply serves typing purposes but we will add additional methods to it later. In your Spring configuration simply add

Example 71. General MongoDB repository Spring configuration
<?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:mongo="http://www.springframework.org/schema/data/mongo"
  xsi:schemaLocation="http://www.springframework.org/schema/beans
    http://www.springframework.org/schema/beans/spring-beans-3.0.xsd
    http://www.springframework.org/schema/data/mongo
    http://www.springframework.org/schema/data/mongo/spring-mongo-1.0.xsd">

  <mongo:mongo id="mongo" />

  <bean id="mongoTemplate" class="org.springframework.data.mongodb.core.MongoTemplate">
    <constructor-arg ref="mongo" />
    <constructor-arg value="databaseName" />
  </bean>

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

</beans>

This namespace element will cause the base packages to be scanned for interfaces extending MongoRepository and create Spring beans for each of them found. By default the repositories will get a MongoTemplate Spring bean wired that is called mongoTemplate, so you only need to configure mongo-template-ref explicitly if you deviate from this convention.

If you’d rather like to go with JavaConfig use the @EnableMongoRepositories annotation. The annotation carries the very same attributes like the namespace element. If no base package is configured the infrastructure will scan the package of the annotated configuration class.

Example 72. JavaConfig for repositories
@Configuration
@EnableMongoRepositories
class ApplicationConfig extends AbstractMongoConfiguration {

  @Override
  protected String getDatabaseName() {
    return "e-store";
  }

  @Override
  public Mongo mongo() throws Exception {
    return new Mongo();
  }

  @Override
  protected String getMappingBasePackage() {
    return "com.oreilly.springdata.mongodb"
  }
}

As our domain repository extends PagingAndSortingRepository it provides you with CRUD operations as well as methods for paginated and sorted access to the entities. Working with the repository instance is just a matter of dependency injecting it into a client. So accessing the second page of Person s at a page size of 10 would simply look something like this:

Example 73. Paging access to Person entities
@RunWith(SpringJUnit4ClassRunner.class)
@ContextConfiguration
public class PersonRepositoryTests {

    @Autowired PersonRepository repository;

    @Test
    public void readsFirstPageCorrectly() {

      Page<Person> persons = repository.findAll(new PageRequest(0, 10));
      assertThat(persons.isFirstPage(), is(true));
    }
}

The sample creates an application context with Spring’s unit test support which will perform annotation based dependency injection into test cases. Inside the test method we simply use the repository to query the datastore. We hand the repository a PageRequest instance that requests the first page of persons at a page size of 10.

10.3. Query methods

Most of the data access operations you usually trigger on a repository result a query being executed against the MongoDB databases. Defining such a query is just a matter of declaring a method on the repository interface

Example 74. PersonRepository with query methods
public interface PersonRepository extends PagingAndSortingRepository<Person, String> {

    List<Person> findByLastname(String lastname);                      (1)

    Page<Person> findByFirstname(String firstname, Pageable pageable); (2)

    Person findByShippingAddresses(Address address);                   (3)

    Stream<Person> findAllBy();                                        (4)
}
1 The method shows a query for all people with the given lastname. The query will be derived parsing the method name for constraints which can be concatenated with And and Or. Thus the method name will result in a query expression of {"lastname" : lastname}.
2 Applies pagination to a query. Just equip your method signature with a Pageable parameter and let the method return a Page instance and we will automatically page the query accordingly.
3 Shows that you can query based on properties which are not a primitive type.
4 Uses a Java 8 Stream which reads and converts individual elements while iterating the stream.
Note that for version 1.0 we currently don’t support referring to parameters that are mapped as DBRef in the domain class.
Table 5. Supported keywords for query methods
Keyword Sample Logical result

After

findByBirthdateAfter(Date date)

{"birthdate" : {"$gt" : date}}

GreaterThan

findByAgeGreaterThan(int age)

{"age" : {"$gt" : age}}

GreaterThanEqual

findByAgeGreaterThanEqual(int age)

{"age" : {"$gte" : age}}

Before

findByBirthdateBefore(Date date)

{"birthdate" : {"$lt" : date}}

LessThan

findByAgeLessThan(int age)

{"age" : {"$lt" : age}}

LessThanEqual

findByAgeLessThanEqual(int age)

{"age" : {"$lte" : age}}

Between

findByAgeBetween(int from, int to)

{"age" : {"$gt" : from, "$lt" : to}}

In

findByAgeIn(Collection ages)

{"age" : {"$in" : [ages…​]}}

NotIn

findByAgeNotIn(Collection ages)

{"age" : {"$nin" : [ages…​]}}

IsNotNull, NotNull

findByFirstnameNotNull()

{"firstname" : {"$ne" : null}}

IsNull, Null

findByFirstnameNull()

{"firstname" : null}

Like, StartingWith, EndingWith

findByFirstnameLike(String name)

{"firstname" : name} ( name as regex)

Containing on String

findByFirstnameContaining(String name)

{"firstname" : name} (name as regex)

NotContaining on String

findByFirstnameNotContaining(String name)

{"firstname" : { "$not" : name}} (name as regex)

Containing on Collection

findByAddressesContaining(Address address)

{"addresses" : { "$in" : address}}

NotContaining on Collection

findByAddressesNotContaining(Address address)

{"addresses" : { "$not" : { "$in" : address}}}

Regex

findByFirstnameRegex(String firstname)

{"firstname" : {"$regex" : firstname }}

(No keyword)

findByFirstname(String name)

{"firstname" : name}

Not

findByFirstnameNot(String name)

{"firstname" : {"$ne" : name}}

Near

findByLocationNear(Point point)

{"location" : {"$near" : [x,y]}}

Near

findByLocationNear(Point point, Distance max)

{"location" : {"$near" : [x,y], "$maxDistance" : max}}

Near

findByLocationNear(Point point, Distance min, Distance max)

{"location" : {"$near" : [x,y], "$minDistance" : min, "$maxDistance" : max}}

Within

findByLocationWithin(Circle circle)

{"location" : {"$geoWithin" : {"$center" : [ [x, y], distance]}}}

Within

findByLocationWithin(Box box)

{"location" : {"$geoWithin" : {"$box" : [ [x1, y1], x2, y2]}}}

IsTrue, True

findByActiveIsTrue()

{"active" : true}

IsFalse, False

findByActiveIsFalse()

{"active" : false}

Exists

findByLocationExists(boolean exists)

{"location" : {"$exists" : exists }}

10.3.1. Repository delete queries

The above keywords can be used in conjunction with delete…By or remove…By to create queries deleting matching documents.

Example 75. Delete…By Query
public interface PersonRepository extends MongoRepository<Person, String> {

  List <Person> deleteByLastname(String lastname);

  Long deletePersonByLastname(String lastname);
}

Using return type List will retrieve and return all matching documents before actually deleting them. A numeric return type directly removes the matching documents returning the total number of documents removed.

10.3.2. Geo-spatial repository queries

As you’ve just seen there are a few keywords triggering geo-spatial operations within a MongoDB query. The Near keyword allows some further modification. Let’s have a look at some examples:

Example 76. Advanced Near queries
public interface PersonRepository extends MongoRepository<Person, String>

  // { 'location' : { '$near' : [point.x, point.y], '$maxDistance' : distance}}
  List<Person> findByLocationNear(Point location, Distance distance);
}

Adding a Distance parameter to the query method allows restricting results to those within the given distance. If the Distance was set up containing a Metric we will transparently use $nearSphere instead of $code.

Example 77. Using Distance with Metrics
Point point = new Point(43.7, 48.8);
Distance distance = new Distance(200, Metrics.KILOMETERS);
… = repository.findByLocationNear(point, distance);
// {'location' : {'$nearSphere' : [43.7, 48.8], '$maxDistance' : 0.03135711885774796}}

As you can see using a Distance equipped with a Metric causes $nearSphere clause to be added instead of a plain $near. Beyond that the actual distance gets calculated according to the Metrics used.

Using @GeoSpatialIndexed(type = GeoSpatialIndexType.GEO_2DSPHERE) on the target property forces usage of $nearSphere operator.
Geo-near queries
public interface PersonRepository extends MongoRepository<Person, String>

  // {'geoNear' : 'location', 'near' : [x, y] }
  GeoResults<Person> findByLocationNear(Point location);

  // No metric: {'geoNear' : 'person', 'near' : [x, y], maxDistance : distance }
  // Metric: {'geoNear' : 'person', 'near' : [x, y], 'maxDistance' : distance,
  //          'distanceMultiplier' : metric.multiplier, 'spherical' : true }
  GeoResults<Person> findByLocationNear(Point location, Distance distance);

  // Metric: {'geoNear' : 'person', 'near' : [x, y], 'minDistance' : min,
  //          'maxDistance' : max, 'distanceMultiplier' : metric.multiplier,
  //          'spherical' : true }
  GeoResults<Person> findByLocationNear(Point location, Distance min, Distance max);

  // {'geoNear' : 'location', 'near' : [x, y] }
  GeoResults<Person> findByLocationNear(Point location);
}

10.3.3. MongoDB JSON based query methods and field restriction

By adding the annotation org.springframework.data.mongodb.repository.Query repository finder methods you can specify a MongoDB JSON query string to use instead of having the query derived from the method name. For example

public interface PersonRepository extends MongoRepository<Person, String>

  @Query("{ 'firstname' : ?0 }")
  List<Person> findByThePersonsFirstname(String firstname);

}

The placeholder ?0 lets you substitute the value from the method arguments into the JSON query string.

You can also use the filter property to restrict the set of properties that will be mapped into the Java object. For example,

public interface PersonRepository extends MongoRepository<Person, String>

  @Query(value="{ 'firstname' : ?0 }", fields="{ 'firstname' : 1, 'lastname' : 1}")
  List<Person> findByThePersonsFirstname(String firstname);

}

This will return only the firstname, lastname and Id properties of the Person objects. The age property, a java.lang.Integer, will not be set and its value will therefore be null.

10.3.4. Type-safe Query methods

MongoDB repository support integrates with the QueryDSL project which provides a means to perform type-safe queries in Java. To quote from the project description, "Instead of writing queries as inline strings or externalizing them into XML files they are constructed via a fluent API." It provides the following features

  • Code completion in IDE (all properties, methods and operations can be expanded in your favorite Java IDE)

  • Almost no syntactically invalid queries allowed (type-safe on all levels)

  • Domain types and properties can be referenced safely (no Strings involved!)

  • Adopts better to refactoring changes in domain types

  • Incremental query definition is easier

Please refer to the QueryDSL documentation which describes how to bootstrap your environment for APT based code generation using Maven or Ant.

Using QueryDSL you will be able to write queries as shown below

QPerson person = new QPerson("person");
List<Person> result = repository.findAll(person.address.zipCode.eq("C0123"));

Page<Person> page = repository.findAll(person.lastname.contains("a"),
                                       new PageRequest(0, 2, Direction.ASC, "lastname"));

QPerson is a class that is generated (via the Java annotation post processing tool) which is a Predicate that allows you to write type safe queries. Notice that there are no strings in the query other than the value "C0123".

You can use the generated Predicate class via the interface QueryDslPredicateExecutor which is shown below

public interface QueryDslPredicateExecutor<T> {

  T findOne(Predicate predicate);

  List<T> findAll(Predicate predicate);

  List<T> findAll(Predicate predicate, OrderSpecifier<?>... orders);

  Page<T> findAll(Predicate predicate, Pageable pageable);

  Long count(Predicate predicate);
}

To use this in your repository implementation, simply inherit from it in addition to other repository interfaces. This is shown below

public interface PersonRepository extends MongoRepository<Person, String>, QueryDslPredicateExecutor<Person> {

   // additional finder methods go here
}

We think you will find this an extremely powerful tool for writing MongoDB queries.

10.3.5. Full-text search queries

MongoDBs full text search feature is very store specific and therefore can rather be found on MongoRepository than on the more general CrudRepository. What we need is a document with a full-text index defined for (Please see section Text Indexes for creating).

Additional methods on MongoRepository take TextCriteria as input parameter. In addition to those explicit methods, it is also possible to add a TextCriteria derived repository method. The criteria will be added as an additional AND criteria. Once the entity contains a @TextScore annotated property the documents full-text score will be retrieved. Furthermore the @TextScore annotated property will also make it possible to sort by the documents score.

@Document
class FullTextDocument {

  @Id String id;
  @TextIndexed String title;
  @TextIndexed String content;
  @TextScore Float score;
}

interface FullTextRepository extends Repository<FullTextDocument, String> {

  // Execute a full-text search and define sorting dynamically
  List<FullTextDocument> findAllBy(TextCriteria criteria, Sort sort);

  // Paginate over a full-text search result
  Page<FullTextDocument> findAllBy(TextCriteria criteria, Pageable pageable);

  // Combine a derived query with a full-text search
  List<FullTextDocument> findByTitleOrderByScoreDesc(String title, TextCriteria criteria);
}


Sort sort = new Sort("score");
TextCriteria criteria = TextCriteria.forDefaultLanguage().matchingAny("spring", "data");
List<FullTextDocument> result = repository.findAllBy(criteria, sort);

criteria = TextCriteria.forDefaultLanguage().matching("film");
Page<FullTextDocument> page = repository.findAllBy(criteria, new PageRequest(1, 1, sort));
List<FullTextDocument> result = repository.findByTitleOrderByScoreDesc("mongodb", criteria);

10.3.6. Projections

Spring Data Repositories usually return the domain model when using query methods. However, sometimes, you may need to alter the view of that model for various reasons. In this section, you will learn how to define projections to serve up simplified and reduced views of resources.

Look at the following domain model:

@Entity
public class Person {

  @Id @GeneratedValue
  private Long id;
  private String firstName, lastName;

  @OneToOne
  private Address address;
  …
}

@Entity
public class Address {

  @Id @GeneratedValue
  private Long id;
  private String street, state, country;

  …
}

This Person has several attributes:

  • id is the primary key

  • firstName and lastName are data attributes

  • address is a link to another domain object

Now assume we create a corresponding repository as follows:

interface PersonRepository extends CrudRepository<Person, Long> {

  Person findPersonByFirstName(String firstName);
}

Spring Data will return the domain object including all of its attributes. There are two options just to retrieve the address attribute. One option is to define a repository for Address objects like this:

interface AddressRepository extends CrudRepository<Address, Long> {}

In this situation, using PersonRepository will still return the whole Person object. Using AddressRepository will return just the Address.

However, what if you do not want to expose address details at all? You can offer the consumer of your repository service an alternative by defining one or more projections.

Example 78. Simple Projection
interface NoAddresses {  (1)

  String getFirstName(); (2)

  String getLastName();  (3)
}

This projection has the following details:

1 A plain Java interface making it declarative.
2 Export the firstName.
3 Export the lastName.

The NoAddresses projection only has getters for firstName and lastName meaning that it will not serve up any address information. The query method definition returns in this case NoAdresses instead of Person.

interface PersonRepository extends CrudRepository<Person, Long> {

  NoAddresses findByFirstName(String firstName);
}

Projections declare a contract between the underlying type and the method signatures related to the exposed properties. Hence it is required to name getter methods according to the property name of the underlying type. If the underlying property is named firstName, then the getter method must be named getFirstName otherwise Spring Data is not able to look up the source property. This type of projection is also called closed projection. Closed projections expose a subset of properties hence they can be used to optimize the query in a way to reduce the selected fields from the data store. The other type is, as you might imagine, an open projection.

Remodelling data

So far, you have seen how projections can be used to reduce the information that is presented to the user. Projections can be used to adjust the exposed data model. You can add virtual properties to your projection. Look at the following projection interface:

Example 79. Renaming a property
interface RenamedProperty {    (1)

  String getFirstName();       (2)

  @Value("#{target.lastName}")
  String getName();            (3)
}

This projection has the following details:

1 A plain Java interface making it declarative.
2 Export the firstName.
3 Export the name property. Since this property is virtual it requires @Value("#{target.lastName}") to specify the property source.

The backing domain model does not have this property so we need to tell Spring Data from where this property is obtained. Virtual properties are the place where @Value comes into play. The name getter is annotated with @Value to use SpEL expressions pointing to the backing property lastName. You may have noticed lastName is prefixed with target which is the variable name pointing to the backing object. Using @Value on methods allows defining where and how the value is obtained.

Some applications require the full name of a person. Concatenating strings with String.format("%s %s", person.getFirstName(), person.getLastName()) would be one possibility but this piece of code needs to be called in every place the full name is required. Virtual properties on projections leverage the need for repeating that code all over.

interface FullNameAndCountry {

  @Value("#{target.firstName} #{target.lastName}")
  String getFullName();

  @Value("#{target.address.country}")
  String getCountry();
}

In fact, @Value gives full access to the target object and its nested properties. SpEL expressions are extremly powerful as the definition is always applied to the projection method. Let’s take SpEL expressions in projections to the next level.

Imagine you had the following domain model definition:

@Entity
public class User {

  @Id @GeneratedValue
  private Long id;
  private String name;

  private String password;
  …
}
This example may seem a bit contrived, but it is possible with a richer domain model and many projections, to accidentally leak such details. Since Spring Data cannot discern the sensitivity of such data, it is up to the developers to avoid such situations. Storing a password as plain-text is discouraged. You really should not do this. For this example, you could also replace password with anything else that is secret.

In some cases, you might keep the password as secret as possible and not expose it more than it should be. The solution is to create a projection using @Value together with a SpEL expression.

interface PasswordProjection {
  @Value("#{(target.password == null || target.password.empty) ? null : '******'}")
  String getPassword();
}

The expression checks whether the password is null or empty and returns null in this case, otherwise six asterisks to indicate a password was set.

10.4. Miscellaneous

10.4.1. CDI Integration

Instances of the repository interfaces are usually created by a container, which Spring is the most natural choice when working with Spring Data. As of version 1.3.0 Spring Data MongoDB ships with a custom CDI extension that allows using the repository abstraction in CDI environments. The extension is part of the JAR so all you need to do to activate it is dropping the Spring Data MongoDB JAR into your classpath. You can now set up the infrastructure by implementing a CDI Producer for the MongoTemplate:

class MongoTemplateProducer {

    @Produces
    @ApplicationScoped
    public MongoOperations createMongoTemplate() throws UnknownHostException, MongoException {

        MongoDbFactory factory = new SimpleMongoDbFactory(new Mongo(), "database");
        return new MongoTemplate(factory);
    }
}

The Spring Data MongoDB CDI extension will pick up the MongoTemplate available as CDI bean and create a proxy for a Spring Data repository whenever a bean of a repository type is requested by the container. Thus obtaining an instance of a Spring Data repository is a matter of declaring an @Inject-ed property:

class RepositoryClient {

  @Inject
  PersonRepository repository;

  public void businessMethod() {
    List<Person> people = repository.findAll();
  }
}

11. Auditing

11.1. Basics

Spring Data provides sophisticated support to transparently keep track of who created or changed an entity and the point in time this 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.

11.1.1. Annotation based auditing metadata

We provide @CreatedBy, @LastModifiedBy to capture the user who created or modified the entity as well as @CreatedDate and @LastModifiedDate to capture the point in time this happened.

Example 80. An audited entity
class Customer {

  @CreatedBy
  private User user;

  @CreatedDate
  private DateTime createdDate;

  // … further properties omitted
}

As you can see, the annotations can be applied selectively, depending on which information you’d like to capture. For the annotations capturing the points in time can be used on properties of type JodaTimes DateTime, legacy Java Date and Calendar, JDK8 date/time types as well as long/Long.

11.1.2. Interface-based auditing metadata

In case you don’t 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’s also a convenience base class AbstractAuditable which you can extend to avoid the need to manually implement the interface methods. Be aware that this 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.

11.1.3. 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 of what type the properties annotated with @CreatedBy or @LastModifiedBy have to be.

Here’s an example implementation of the interface using Spring Security’s Authentication object:

Example 81. Implementation of AuditorAware based on Spring Security
class SpringSecurityAuditorAware implements AuditorAware<User> {

  public User getCurrentAuditor() {

    Authentication authentication = SecurityContextHolder.getContext().getAuthentication();

    if (authentication == null || !authentication.isAuthenticated()) {
      return null;
    }

    return ((MyUserDetails) authentication.getPrincipal()).getUser();
  }
}

The implementation is accessing the Authentication object provided by Spring Security and looks up the custom UserDetails instance from it that you have created in your UserDetailsService implementation. We’re assuming here that you are exposing the domain user through that UserDetails implementation but you could also look it up from anywhere based on the Authentication found.

11.2. General auditing configuration

Activating auditing functionality is just a matter of adding the Spring Data Mongo auditing namespace element to your configuration:

Example 82. Activating auditing using XML configuration
<mongo:auditing mapping-context-ref="customMappingContext" auditor-aware-ref="yourAuditorAwareImpl"/>

Since Spring Data MongoDB 1.4 auditing can be enabled by annotating a configuration class with the @EnableMongoAuditing annotation.

Example 83. Activating auditing using JavaConfig
@Configuration
@EnableMongoAuditing
class Config {

  @Bean
  public AuditorAware<AuditableUser> myAuditorProvider() {
      return new AuditorAwareImpl();
  }
}

If you expose a bean of type AuditorAware to the ApplicationContext, the auditing infrastructure will pick it up automatically and use 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 @EnableJpaAuditing.

12. Mapping

Rich mapping support is provided by the MongoMappingConverter. MongoMappingConverter has a rich metadata model that provides a full feature set of functionality to map domain objects to MongoDB documents.The mapping metadata model is populated using annotations on your domain objects. However, the infrastructure is not limited to using annotations as the only source of metadata information. The MongoMappingConverter also allows you to map objects to documents without providing any additional metadata, by following a set of conventions.

In this section we will describe the features of the MongoMappingConverter. How to use conventions for mapping objects to documents and how to override those conventions with annotation based mapping metadata.

SimpleMongoConverter has been deprecated in Spring Data MongoDB M3 as all of its functionality has been subsumed into MappingMongoConverter.

12.1. Convention based Mapping

MongoMappingConverter has a few conventions for mapping objects to documents when no additional mapping metadata is provided. The conventions are:

  • The short Java class name is mapped to the collection name in the following manner. The class com.bigbank.SavingsAccount maps to savingsAccount collection name.

  • All nested objects are stored as nested objects in the document and not as DBRefs

  • The converter will use any Spring Converters registered with it to override the default mapping of object properties to document field/values.

  • The fields of an object are used to convert to and from fields in the document. Public JavaBean properties are not used.

  • You can have a single non-zero argument constructor whose constructor argument names match top level field names of document, that constructor will be used. Otherwise the zero arg constructor will be used. if there is more than one non-zero argument constructor an exception will be thrown.

12.1.1. How the _id field is handled in the mapping layer

MongoDB requires that you have an _id field for all documents. If you don’t provide one the driver will assign a ObjectId with a generated value. The "_id" field can be of any type the, other than arrays, so long as it is unique. The driver naturally supports all primitive types and Dates. When using the MongoMappingConverter there are certain rules that govern how properties from the Java class is mapped to this _id field.

The following outlines what field will be mapped to the _id document field:

  • A field annotated with @Id (org.springframework.data.annotation.Id) will be mapped to the _id field.

  • A field without an annotation but named id will be mapped to the _id field.

  • The default field name for identifiers is _id and can be customized via the @Field annotation.

Table 6. Examples for the translation of _id field definitions
Field definition Resulting Id-Fieldname in MongoDB

String id

_id

@Field String id

_id

@Field("x") String id

x

@Id String x

_id

@Field("x") @Id String x

_id

The following outlines what type conversion, if any, will be done on the property mapped to the _id document field.

  • If a field named id is declared as a String or BigInteger in the Java class it will be converted to and stored as an ObjectId if possible. ObjectId as a field type is also valid. If you specify a value for id in your application, the conversion to an ObjectId is detected to the MongoDBdriver. If the specified id value cannot be converted to an ObjectId, then the value will be stored as is in the document’s _id field.

  • If a field named id id field is not declared as a String, BigInteger, or ObjectID in the Java class then you should assign it a value in your application so it can be stored 'as-is' in the document’s _id field.

  • If no field named id is present in the Java class then an implicit _id file will be generated by the driver but not mapped to a property or field of the Java class.

When querying and updating MongoTemplate will use the converter to handle conversions of the Query and Update objects that correspond to the above rules for saving documents so field names and types used in your queries will be able to match what is in your domain classes.

12.2. Data mapping and type conversion

This section explain how types are mapped to a MongoDB representation and vice versa. Spring Data MongoDB supports all types that can be represented as BSON, MongoDB’s internal document format. In addition to these types, Spring Data MongoDB provides a set of built-in converters to map additional types. You can provide your own converters to adjust type conversion, see Overriding Mapping with explicit Converters for further details.

Table 7. Type
Type Type conversion Sample

String

native

{"firstname" : "Dave"}

double, Double, float, Float

native

{"weight" : 42.5}

int, Integer, short, Short

native
32-bit integer

{"height" : 42}

long, Long

native
64-bit integer

{"height" : 42}

Date, Timestamp

native

{"date" : ISODate("2019-11-12T23:00:00.809Z")}

byte[]

native

{"bin" : { "$binary" : "AQIDBA==", "$type" : "00" }}

java.util.UUID (Legacy UUID)

native

{"uuid" : { "$binary" : "MEaf1CFQ6lSphaa3b9AtlA==", "$type" : "03" }}

Date

native

{"date" : ISODate("2019-11-12T23:00:00.809Z")}

ObjectId

native

{"_id" : ObjectId("5707a2690364aba3136ab870")}

Array, List, BasicDBList

native

{"cookies" : [ … ]}

boolean, Boolean

native

{"active" : true}

null

native

{"value" : null}

DBObject

native

{"value" : { … }}

AtomicInteger
calling get() before the actual conversion

converter
32-bit integer

{"value" : "741" }

AtomicLong
calling get() before the actual conversion

converter
64-bit integer

{"value" : "741" }

BigInteger

converter
String

{"value" : "741" }

BigDecimal

converter
String

{"value" : "741.99" }

URL

converter

{"website" : "http://projects.spring.io/spring-data-mongodb/" }

Locale

converter

{"locale : "en_US" }

char, Character

converter

{"char" : "a" }

NamedMongoScript

converter
Code

{"_id" : "script name", value: (some javascript code)}

java.util.Currency

converter

{"currencyCode" : "EUR"}

LocalDate
(Joda, Java 8, JSR310-BackPort)

converter

{"date" : ISODate("2019-11-12T00:00:00.000Z")}

LocalDateTime, LocalTime, Instant
(Joda, Java 8, JSR310-BackPort)

converter

{"date" : ISODate("2019-11-12T23:00:00.809Z")}

DateTime (Joda)

converter

{"date" : ISODate("2019-11-12T23:00:00.809Z")}

DateMidnight (Joda)

converter

{"date" : ISODate("2019-11-12T00:00:00.000Z")}

ZoneId (Java 8, JSR310-BackPort)

converter

{"zoneId" : "ECT - Europe/Paris"}

Box

converter

{"box" : { "first" : { "x" : 1.0 , "y" : 2.0} , "second" : { "x" : 3.0 , "y" : 4.0}}

Polygon

converter

{"polygon" : { "points" : [ { "x" : 1.0 , "y" : 2.0} , { "x" : 3.0 , "y" : 4.0} , { "x" : 4.0 , "y" : 5.0}]}}

Circle

converter

{"circle" : { "center" : { "x" : 1.0 , "y" : 2.0} , "radius" : 3.0 , "metric" : "NEUTRAL"}}

Point

converter

{"point" : { "x" : 1.0 , "y" : 2.0}}

GeoJsonPoint

converter

{"point" : { "type" : "Point" , "coordinates" : [3.0 , 4.0] }}

GeoJsonMultiPoint

converter

{"geoJsonLineString" : {"type":"MultiPoint", "coordinates": [ [ 0 , 0 ], [ 0 , 1 ], [ 1 , 1 ] ] }}

Sphere

converter

{"sphere" : { "center" : { "x" : 1.0 , "y" : 2.0} , "radius" : 3.0 , "metric" : "NEUTRAL"}}

GeoJsonPolygon

converter

{"polygon" : { "type" : "Polygon", "coordinates" : [[ [ 0 , 0 ], [ 3 , 6 ], [ 6 , 1 ], [ 0 , 0 ] ]] }}

GeoJsonMultiPolygon

converter

{"geoJsonMultiPolygon" : { "type" : "MultiPolygon", "coordinates" : [ [ [ [ -73.958 , 40.8003 ] , [ -73.9498 , 40.7968 ] ] ], [ [ [ -73.973 , 40.7648 ] , [ -73.9588 , 40.8003 ] ] ] ] }}

GeoJsonLineString

converter

{ "geoJsonLineString" : { "type" : "LineString", "coordinates" : [ [ 40 , 5 ], [ 41 , 6 ] ] }}

GeoJsonMultiLineString

converter

{"geoJsonLineString" : { "type" : "MultiLineString", coordinates: [ [ [ -73.97162 , 40.78205 ], [ -73.96374 , 40.77715 ] ], [ [ -73.97880 , 40.77247 ], [ -73.97036 , 40.76811 ] ] ] }}

12.3. Mapping Configuration

Unless explicitly configured, an instance of MongoMappingConverter is created by default when creating a MongoTemplate. You can create your own instance of the MappingMongoConverter so as to tell it where to scan the classpath at startup your domain classes in order to extract metadata and construct indexes. Also, by creating your own instance you can register Spring converters to use for mapping specific classes to and from the database.

You can configure the MongoMappingConverter as well as com.mongodb.Mongo and MongoTemplate either using Java or XML based metadata. Here is an example using Spring’s Java based configuration

Example 84. @Configuration class to configure MongoDB mapping support
@Configuration
public class GeoSpatialAppConfig extends AbstractMongoConfiguration {

  @Bean
  public Mongo mongo() throws Exception {
    return new Mongo("localhost");
  }

  @Override
  public String getDatabaseName() {
    return "database";
  }

  @Override
  public String getMappingBasePackage() {
    return "com.bigbank.domain";
  }

  // the following are optional


  @Bean
  @Override
  public CustomConversions customConversions() throws Exception {
    List<Converter<?, ?>> converterList = new ArrayList<Converter<?, ?>>();
    converterList.add(new org.springframework.data.mongodb.test.PersonReadConverter());
    converterList.add(new org.springframework.data.mongodb.test.PersonWriteConverter());
    return new CustomConversions(converterList);
  }

  @Bean
  public LoggingEventListener<MongoMappingEvent> mappingEventsListener() {
    return new LoggingEventListener<MongoMappingEvent>();
  }
}

AbstractMongoConfiguration requires you to implement methods that define a com.mongodb.Mongo as well as provide a database name. AbstractMongoConfiguration also has a method you can override named getMappingBasePackage(…) which tells the converter where to scan for classes annotated with the @Document annotation.

You can add additional converters to the converter by overriding the method afterMappingMongoConverterCreation. Also shown in the above example is a LoggingEventListener which logs MongoMappingEvent s that are posted onto Spring’s ApplicationContextEvent infrastructure.

AbstractMongoConfiguration will create a MongoTemplate instance and registered with the container under the name mongoTemplate.

You can also override the method UserCredentials getUserCredentials() to provide the username and password information to connect to the database.

Spring’s MongoDB namespace enables you to easily enable mapping functionality in XML

Example 85. XML schema to configure MongoDB mapping support
<?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:context="http://www.springframework.org/schema/context"
  xmlns:mongo="http://www.springframework.org/schema/data/mongo"
  xsi:schemaLocation="http://www.springframework.org/schema/context http://www.springframework.org/schema/context/spring-context-3.0.xsd
    http://www.springframework.org/schema/data/mongo http://www.springframework.org/schema/data/mongo/spring-mongo-1.0.xsd
    http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans-3.0.xsd">

  <!-- Default bean name is 'mongo' -->
  <mongo:mongo host="localhost" port="27017"/>

  <mongo:db-factory dbname="database" mongo-ref="mongo"/>

  <!-- by default look for a Mongo object named 'mongo' - default name used for the converter is 'mappingConverter' -->
  <mongo:mapping-converter base-package="com.bigbank.domain">
    <mongo:custom-converters>
      <mongo:converter ref="readConverter"/>
      <mongo:converter>
        <bean class="org.springframework.data.mongodb.test.PersonWriteConverter"/>
      </mongo:converter>
    </mongo:custom-converters>
  </mongo:mapping-converter>

  <bean id="readConverter" class="org.springframework.data.mongodb.test.PersonReadConverter"/>

  <!-- set the mapping converter to be used by the MongoTemplate -->
  <bean id="mongoTemplate" class="org.springframework.data.mongodb.core.MongoTemplate">
    <constructor-arg name="mongoDbFactory" ref="mongoDbFactory"/>
    <constructor-arg name="mongoConverter" ref="mappingConverter"/>
  </bean>

  <bean class="org.springframework.data.mongodb.core.mapping.event.LoggingEventListener"/>

</beans>

The base-package property tells it where to scan for classes annotated with the @org.springframework.data.mongodb.core.mapping.Document annotation.

12.4. Metadata based Mapping

To take full advantage of the object mapping functionality inside the Spring Data/MongoDB support, you should annotate your mapped objects with the @Document annotation. Although it is not necessary for the mapping framework to have this annotation (your POJOs will be mapped correctly, even without any annotations), it allows the classpath scanner to find and pre-process your domain objects to extract the necessary metadata. If you don’t use this annotation, your application will take a slight performance hit the first time you store a domain object because the mapping framework needs to build up its internal metadata model so it knows about the properties of your domain object and how to persist them.

Example 86. Example domain object
package com.mycompany.domain;

@Document
public class Person {

  @Id
  private ObjectId id;

  @Indexed
  private Integer ssn;

  private String firstName;

  @Indexed
  private String lastName;
}
The @Id annotation tells the mapper which property you want to use for the MongoDB _id property and the @Indexed annotation tells the mapping framework to call createIndex(…) on that property of your document, making searches faster.
Automatic index creation is only done for types annotated with @Document.

12.4.1. Mapping annotation overview

The MappingMongoConverter can use metadata to drive the mapping of objects to documents. An overview of the annotations is provided below

  • @Id - applied at the field level to mark the field used for identiy purpose.

  • @Document - applied at the class level to indicate this class is a candidate for mapping to the database. You can specify the name of the collection where the database will be stored.

  • @DBRef - applied at the field to indicate it is to be stored using a com.mongodb.DBRef.

  • @Indexed - applied at the field level to describe how to index the field.

  • @CompoundIndex - applied at the type level to declare Compound Indexes

  • @GeoSpatialIndexed - applied at the field level to describe how to geoindex the field.

  • @TextIndexed - applied at the field level to mark the field to be included in the text index.

  • @Language - applied at the field level to set the language override property for text index.

  • @Transient - by default all private fields are mapped to the document, this annotation excludes the field where it is applied from being stored in the database

  • @PersistenceConstructor - marks a given constructor - even a package protected one - to use when instantiating the object from the database. Constructor arguments are mapped by name to the key values in the retrieved DBObject.

  • @Value - this annotation is part of the Spring Framework . Within the mapping framework it can be applied to constructor arguments. This lets you use a Spring Expression Language statement to transform a key’s value retrieved in the database before it is used to construct a domain object. In order to reference a property of a given document one has to use expressions like: @Value("#root.myProperty") where root refers to the root of the given document.

  • @Field - applied at the field level and described the name of the field as it will be represented in the MongoDB BSON document thus allowing the name to be different than the fieldname of the class.

  • @Version - applied at field level is used for optimistic locking and checked for modification on save operations. The initial value is zero which is bumped automatically on every update.

The mapping metadata infrastructure is defined in a seperate spring-data-commons project that is technology agnostic. Specific subclasses are using in the MongoDB support to support annotation based metadata. Other strategies are also possible to put in place if there is demand.

Here is an example of a more complex mapping.

@Document
@CompoundIndexes({
    @CompoundIndex(name = "age_idx", def = "{'lastName': 1, 'age': -1}")
})
public class Person<T extends Address> {

  @Id
  private String id;

  @Indexed(unique = true)
  private Integer ssn;

  @Field("fName")
  private String firstName;

  @Indexed
  private String lastName;

  private Integer age;

  @Transient
  private Integer accountTotal;

  @DBRef
  private List<Account> accounts;

  private T address;


  public Person(Integer ssn) {
    this.ssn = ssn;
  }

  @PersistenceConstructor
  public Person(Integer ssn, String firstName, String lastName, Integer age, T address) {
    this.ssn = ssn;
    this.firstName = firstName;
    this.lastName = lastName;
    this.age = age;
    this.address = address;
  }

  public String getId() {
    return id;
  }

  // no setter for Id.  (getter is only exposed for some unit testing)

  public Integer getSsn() {
    return ssn;
  }

// other getters/setters omitted

12.4.2. Customized Object Construction

The mapping subsystem allows the customization of the object construction by annotating a constructor with the @PersistenceConstructor annotation. The values to be used for the constructor parameters are resolved in the following way:

  • If a parameter is annotated with the @Value annotation, the given expression is evaluated and the result is used as the parameter value.

  • If the Java type has a property whose name matches the given field of the input document, then it’s property information is used to select the appropriate constructor parameter to pass the input field value to. This works only if the parameter name information is present in the java .class files which can be achieved by compiling the source with debug information or using the new -parameters command-line switch for javac in Java 8.

  • Otherwise a MappingException will be thrown indicating that the given constructor parameter could not be bound.

class OrderItem {

  private @Id String id;
  private int quantity;
  private double unitPrice;

  OrderItem(String id, @Value("#root.qty ?: 0") int quantity, double unitPrice) {
    this.id = id;
    this.quantity = quantity;
    this.unitPrice = unitPrice;
  }

  // getters/setters ommitted
}

DBObject input = new BasicDBObject("id", "4711");
input.put("unitPrice", 2.5);
input.put("qty",5);
OrderItem item = converter.read(OrderItem.class, input);
The SpEL expression in the @Value annotation of the quantity parameter falls back to the value 0 if the given property path cannot be resolved.

Additional examples for using the @PersistenceConstructor annotation can be found in the MappingMongoConverterUnitTests test suite.

12.4.3. Compound Indexes

Compound indexes are also supported. They are defined at the class level, rather than on individual properties.

Compound indexes are very important to improve the performance of queries that involve criteria on multiple fields

Here’s an example that creates a compound index of lastName in ascending order and age in descending order:

Example 87. Example Compound Index Usage
package com.mycompany.domain;

@Document
@CompoundIndexes({
    @CompoundIndex(name = "age_idx", def = "{'lastName': 1, 'age': -1}")
})
public class Person {

  @Id
  private ObjectId id;
  private Integer age;
  private String firstName;
  private String lastName;

}

12.4.4. Text Indexes

The text index feature is disabled by default for mongodb v.2.4.

Creating a text index allows accumulating several fields into a searchable full text index. It is only possible to have one text index per collection so all fields marked with @TextIndexed are combined into this index. Properties can be weighted to influence document score for ranking results. The default language for the text index is english, to change the default language set @Document(language="spanish") to any language you want. Using a property called language or @Language allows to define a language override on a per document base.

Example 88. Example Text Index Usage
@Document(language = "spanish")
class SomeEntity {

    @TextIndexed String foo;

    @Language String lang;

    Nested nested;
}

class Nested {

    @TextIndexed(weight=5) String bar;
    String roo;
}

12.4.5. Using DBRefs

The mapping framework doesn’t have to store child objects embedded within the document. You can also store them separately and use a DBRef to refer to that document. When the object is loaded from MongoDB, those references will be eagerly resolved and you will get back a mapped object that looks the same as if it had been stored embedded within your master document.

Here’s an example of using a DBRef to refer to a specific document that exists independently of the object in which it is referenced (both classes are shown in-line for brevity’s sake):

@Document
public class Account {

  @Id
  private ObjectId id;
  private Float total;
}

@Document
public class Person {

  @Id
  private ObjectId id;
  @Indexed
  private Integer ssn;
  @DBRef
  private List<Account> accounts;
}

There’s no need to use something like @OneToMany because the mapping framework sees that you want a one-to-many relationship because there is a List of objects. When the object is stored in MongoDB, there will be a list of DBRefs rather than the Account objects themselves.

The mapping framework does not handle cascading saves. If you change an Account object that is referenced by a Person object, you must save the Account object separately. Calling save on the Person object will not automatically save the Account objects in the property accounts.

12.4.6. Mapping Framework Events

Events are fired throughout the lifecycle of the mapping process. This is described in the Lifecycle Events section.

Simply declaring these beans in your Spring ApplicationContext will cause them to be invoked whenever the event is dispatched.

12.4.7. Overriding Mapping with explicit Converters

When storing and querying your objects it is convenient to have a MongoConverter instance handle the mapping of all Java types to DBObjects. However, sometimes you may want the MongoConverter s do most of the work but allow you to selectively handle the conversion for a particular type or to optimize performance.

To selectively handle the conversion yourself, register one or more one or more org.springframework.core.convert.converter.Converter instances with the MongoConverter.

Spring 3.0 introduced a core.convert package that provides a general type conversion system. This is described in detail in the Spring reference documentation section entitled Spring Type Conversion.

The method customConversions in AbstractMongoConfiguration can be used to configure Converters. The examples here at the beginning of this chapter show how to perform the configuration using Java and XML.

Below is an example of a Spring Converter implementation that converts from a DBObject to a Person POJO.

@ReadingConverter
 public class PersonReadConverter implements Converter<DBObject, Person> {

  public Person convert(DBObject source) {
    Person p = new Person((ObjectId) source.get("_id"), (String) source.get("name"));
    p.setAge((Integer) source.get("age"));
    return p;
  }
}

Here is an example that converts from a Person to a DBObject.

@WritingConverter
public class PersonWriteConverter implements Converter<Person, DBObject> {

  public DBObject convert(Person source) {
    DBObject dbo = new BasicDBObject();
    dbo.put("_id", source.getId());
    dbo.put("name", source.getFirstName());
    dbo.put("age", source.getAge());
    return dbo;
  }
}

13. Cross Store support

Sometimes you need to store data in multiple data stores and these data stores can be of different types. One might be relational while the other a document store. For this use case we have created a separate module in the MongoDB support that handles what we call cross-store support. The current implementation is based on JPA as the driver for the relational database and we allow select fields in the Entities to be stored in a Mongo database. In addition to allowing you to store your data in two stores we also coordinate persistence operations for the non-transactional MongoDB store with the transaction life-cycle for the relational database.

13.1. Cross Store Configuration

Assuming that you have a working JPA application and would like to add some cross-store persistence for MongoDB. What do you have to add to your configuration?

First of all you need to add a dependency on the module. Using Maven this is done by adding a dependency to your pom:

Example 89. Example Maven pom.xml with spring-data-mongodb-cross-store dependency
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
  <modelVersion>4.0.0</modelVersion>

  ...

    <!-- Spring Data -->
    <dependency>
      <groupId>org.springframework.data</groupId>
      <artifactId>spring-data-mongodb-cross-store</artifactId>
      <version>${spring.data.mongo.version}</version>
    </dependency>

  ...

</project>

Once this is done we need to enable AspectJ for the project. The cross-store support is implemented using AspectJ aspects so by enabling compile time AspectJ support the cross-store features will become available to your project. In Maven you would add an additional plugin to the <build> section of the pom:

Example 90. Example Maven pom.xml with AspectJ plugin enabled
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
  <modelVersion>4.0.0</modelVersion>

  ...

  <build>
    <plugins>

      …

      <plugin>
        <groupId>org.codehaus.mojo</groupId>
        <artifactId>aspectj-maven-plugin</artifactId>
        <version>1.0</version>
        <dependencies>
          <!-- NB: You must use Maven 2.0.9 or above or these are ignored (see MNG-2972) -->
          <dependency>
            <groupId>org.aspectj</groupId>
            <artifactId>aspectjrt</artifactId>
            <version>${aspectj.version}</version>
          </dependency>
          <dependency>
            <groupId>org.aspectj</groupId>
            <artifactId>aspectjtools</artifactId>
            <version>${aspectj.version}</version>
          </dependency>
        </dependencies>
        <executions>
          <execution>
            <goals>
              <goal>compile</goal>
              <goal>test-compile</goal>
            </goals>
          </execution>
        </executions>
        <configuration>
          <outxml>true</outxml>
          <aspectLibraries>
            <aspectLibrary>
              <groupId>org.springframework</groupId>
              <artifactId>spring-aspects</artifactId>
            </aspectLibrary>
            <aspectLibrary>
              <groupId>org.springframework.data</groupId>
              <artifactId>spring-data-mongodb-cross-store</artifactId>
            </aspectLibrary>
          </aspectLibraries>
          <source>1.6</source>
          <target>1.6</target>
        </configuration>
      </plugin>

      ...

    </plugins>
  </build>

...

</project>

Finally, you need to configure your project to use MongoDB and also configure the aspects that are used. The following XML snippet should be added to your application context:

Example 91. Example application context with MongoDB and cross-store aspect support
<?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:jdbc="http://www.springframework.org/schema/jdbc"
  xmlns:jpa="http://www.springframework.org/schema/data/jpa"
  xmlns:mongo="http://www.springframework.org/schema/data/mongo"
  xsi:schemaLocation="http://www.springframework.org/schema/data/mongo
    http://www.springframework.org/schema/data/mongo/spring-mongo.xsd
    http://www.springframework.org/schema/jdbc
    http://www.springframework.org/schema/jdbc/spring-jdbc-3.0.xsd
    http://www.springframework.org/schema/beans
    http://www.springframework.org/schema/beans/spring-beans-3.0.xsd
    http://www.springframework.org/schema/data/jpa
    http://www.springframework.org/schema/data/jpa/spring-jpa-1.0.xsd">

  ...

  <!--  Mongo config -->
  <mongo:mongo host="localhost" port="27017"/>

  <bean id="mongoTemplate" class="org.springframework.data.mongodb.core.MongoTemplate">
    <constructor-arg name="mongo" ref="mongo"/>
    <constructor-arg name="databaseName" value="test"/>
    <constructor-arg name="defaultCollectionName" value="cross-store"/>
  </bean>

  <bean class="org.springframework.data.mongodb.core.MongoExceptionTranslator"/>

  <!--  Mongo cross-store aspect config -->
  <bean class="org.springframework.data.persistence.document.mongo.MongoDocumentBacking"
        factory-method="aspectOf">
    <property name="changeSetPersister" ref="mongoChangeSetPersister"/>
  </bean>
  <bean id="mongoChangeSetPersister"
      class="org.springframework.data.persistence.document.mongo.MongoChangeSetPersister">
    <property name="mongoTemplate" ref="mongoTemplate"/>
    <property name="entityManagerFactory" ref="entityManagerFactory"/>
  </bean>

  ...

</beans>

13.2. Writing the Cross Store Application

We are assuming that you have a working JPA application so we will only cover the additional steps needed to persist part of your Entity in your Mongo database. First you need to identify the field you want persisted. It should be a domain class and follow the general rules for the Mongo mapping support covered in previous chapters. The field you want persisted in MongoDB should be annotated using the @RelatedDocument annotation. That is really all you need to do!. The cross-store aspects take care of the rest. This includes marking the field with @Transient so it won’t be persisted using JPA, keeping track of any changes made to the field value and writing them to the database on successful transaction completion, loading the document from MongoDB the first time the value is used in your application. Here is an example of a simple Entity that has a field annotated with @RelatedEntity.

Example 92. Example of Entity with @RelatedDocument
@Entity
public class Customer {

  @Id
  @GeneratedValue(strategy = GenerationType.IDENTITY)
  private Long id;

  private String firstName;

  private String lastName;

  @RelatedDocument
  private SurveyInfo surveyInfo;

  // getters and setters omitted
}
Example 93. Example of domain class to be stored as document
public class SurveyInfo {

  private Map<String, String> questionsAndAnswers;

  public SurveyInfo() {
    this.questionsAndAnswers = new HashMap<String, String>();
  }

  public SurveyInfo(Map<String, String> questionsAndAnswers) {
    this.questionsAndAnswers = questionsAndAnswers;
  }

  public Map<String, String> getQuestionsAndAnswers() {
    return questionsAndAnswers;
  }

  public void setQuestionsAndAnswers(Map<String, String> questionsAndAnswers) {
    this.questionsAndAnswers = questionsAndAnswers;
  }

  public SurveyInfo addQuestionAndAnswer(String question, String answer) {
    this.questionsAndAnswers.put(question, answer);
    return this;
  }
}

Once the SurveyInfo has been set on the Customer object above the MongoTemplate that was configured above is used to save the SurveyInfo along with some metadata about the JPA Entity is stored in a MongoDB collection named after the fully qualified name of the JPA Entity class. The following code:

Example 94. Example of code using the JPA Entity configured for cross-store persistence
Customer customer = new Customer();
customer.setFirstName("Sven");
customer.setLastName("Olafsen");
SurveyInfo surveyInfo = new SurveyInfo()
  .addQuestionAndAnswer("age", "22")
  .addQuestionAndAnswer("married", "Yes")
  .addQuestionAndAnswer("citizenship", "Norwegian");
customer.setSurveyInfo(surveyInfo);
customerRepository.save(customer);

Executing the code above results in the following JSON document stored in MongoDB.

Example 95. Example of JSON document stored in MongoDB
{ "_id" : ObjectId( "4d9e8b6e3c55287f87d4b79e" ),
  "_entity_id" : 1,
  "_entity_class" : "org.springframework.data.mongodb.examples.custsvc.domain.Customer",
  "_entity_field_name" : "surveyInfo",
  "questionsAndAnswers" : { "married" : "Yes",
    "age" : "22",
    "citizenship" : "Norwegian" },
  "_entity_field_class" : "org.springframework.data.mongodb.examples.custsvc.domain.SurveyInfo" }

14. Logging support

An appender for Log4j is provided in the maven module "spring-data-mongodb-log4j". Note, there is no dependency on other Spring Mongo modules, only the MongoDB driver.

14.1. MongoDB Log4j Configuration

Here is an example configuration

log4j.rootCategory=INFO, stdout

log4j.appender.stdout=org.springframework.data.document.mongodb.log4j.MongoLog4jAppender
log4j.appender.stdout.layout=org.apache.log4j.PatternLayout
log4j.appender.stdout.layout.ConversionPattern=%d %p [%c] - <%m>%n
log4j.appender.stdout.host = localhost
log4j.appender.stdout.port = 27017
log4j.appender.stdout.database = logs
log4j.appender.stdout.collectionPattern = %X{year}%X{month}
log4j.appender.stdout.applicationId = my.application
log4j.appender.stdout.warnOrHigherWriteConcern = FSYNC_SAFE

log4j.category.org.apache.activemq=ERROR
log4j.category.org.springframework.batch=DEBUG
log4j.category.org.springframework.data.document.mongodb=DEBUG
log4j.category.org.springframework.transaction=INFO

The important configuration to look at aside from host and port is the database and collectionPattern. The variables year, month, day and hour are available for you to use in forming a collection name. This is to support the common convention of grouping log information in a collection that corresponds to a specific time period, for example a collection per day.

There is also an applicationId which is put into the stored message. The document stored from logging as the following keys: level, name, applicationId, timestamp, properties, traceback, and message.

15. JMX support

The JMX support for MongoDB exposes the results of executing the 'serverStatus' command on the admin database for a single MongoDB server instance. It also exposes an administrative MBean, MongoAdmin which will let you perform administrative operations such as drop or create a database. The JMX features build upon the JMX feature set available in the Spring Framework. See here for more details.

15.1. MongoDB JMX Configuration

Spring’s Mongo namespace enables you to easily enable JMX functionality

Example 96. XML schema to configure MongoDB
<?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:context="http://www.springframework.org/schema/context"
  xmlns:mongo="http://www.springframework.org/schema/data/mongo"
  xsi:schemaLocation="
    http://www.springframework.org/schema/context
    http://www.springframework.org/schema/context/spring-context-3.0.xsd
    http://www.springframework.org/schema/data/mongo
    http://www.springframework.org/schema/data/mongo/spring-mongo-1.0.xsd
    http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans-3.0.xsd">

    <!-- Default bean name is 'mongo' -->
    <mongo:mongo host="localhost" port="27017"/>

    <!-- by default look for a Mongo object named 'mongo' -->
    <mongo:jmx/>

    <context:mbean-export/>

    <!-- To translate any MongoExceptions thrown in @Repository annotated classes -->
    <context:annotation-config/>

    <bean id="registry" class="org.springframework.remoting.rmi.RmiRegistryFactoryBean" p:port="1099" />

    <!-- Expose JMX over RMI -->
    <bean id="serverConnector" class="org.springframework.jmx.support.ConnectorServerFactoryBean"
        depends-on="registry"
        p:objectName="connector:name=rmi"
        p:serviceUrl="service:jmx:rmi://localhost/jndi/rmi://localhost:1099/myconnector" />

</beans>

This will expose several MBeans

  • AssertMetrics

  • BackgroundFlushingMetrics

  • BtreeIndexCounters

  • ConnectionMetrics

  • GlobalLoclMetrics

  • MemoryMetrics

  • OperationCounters

  • ServerInfo

  • MongoAdmin

This is shown below in a screenshot from JConsole

jconsole

16. MongoDB 3.0 Support

Spring Data MongoDB allows usage of both MongoDB Java driver generations 2 and 3 when connecting to a MongoDB 2.6/3.0 server running MMap.v1 or a MongoDB server 3.0 using MMap.v1 or the WiredTiger storage engine.

Please refer to the driver and database specific documentation for major differences between those.
Operations that are no longer valid using a 3.x MongoDB Java driver have been deprecated within Spring Data and will be removed in a subsequent release.

16.1. Using Spring Data MongoDB with MongoDB 3.0

16.1.1. Configuration Options

Some of the configuration options have been changed / removed for the mongo-java-driver. The following options will be ignored using the generation 3 driver:

  • autoConnectRetry

  • maxAutoConnectRetryTime

  • slaveOk

Generally it is recommended to use the <mongo:mongo-client …​ /> and <mongo:client-options …​ /> elements instead of <mongo:mongo …​ /> when doing XML based configuration, since those elements will only provide you with attributes valid for the 3 generation java driver.

<?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:mongo="http://www.springframework.org/schema/data/mongo"
	xsi:schemaLocation="http://www.springframework.org/schema/data/mongo http://www.springframework.org/schema/data/mongo/spring-mongo.xsd
		http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans.xsd">

  <mongo:mongo-client host="127.0.0.1" port="27017">
    <mongo:client-options write-concern="NORMAL" />
  </mongo:mongo-client>

</beans>

16.1.2. WriteConcern and WriteConcernChecking

The WriteConcern.NONE, which had been used as default by Spring Data MongoDB, was removed in 3.0. Therefore in a MongoDB 3 environment the WriteConcern will be defaulted to WriteConcern.UNACKNOWLEGED. In case WriteResultChecking.EXCEPTION is enabled the WriteConcern will be altered to WriteConcern.ACKNOWLEDGED for write operations, as otherwise errors during execution would not be throw correctly, since simply not raised by the driver.

16.1.3. Authentication

MongoDB Server generation 3 changed the authentication model when connecting to the DB. Therefore some of the configuration options available for authentication are no longer valid. Please use the MongoClient specific options for setting credentials via MongoCredential to provide authentication data.

@Configuration
public class ApplicationContextEventTestsAppConfig extends AbstractMongoConfiguration {

  @Override
  public String getDatabaseName() {
    return "database";
  }

  @Override
  @Bean
  public Mongo mongo() throws Exception {
    return new MongoClient(singletonList(new ServerAddress("127.0.0.1", 27017)),
      singletonList(MongoCredential.createCredential("name", "db", "pwd".toCharArray())));
  }
}

In order to use authentication with XML configuration use the credentials attribue on <mongo-client>.

<?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:mongo="http://www.springframework.org/schema/data/mongo"
	xsi:schemaLocation="http://www.springframework.org/schema/data/mongo http://www.springframework.org/schema/data/mongo/spring-mongo.xsd
		http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans.xsd">

  <mongo:mongo-client credentials="user:[email protected]" />

</beans>

16.1.4. Other things to be aware of

This section covers additional things to keep in mind when using the 3.0 driver.

  • IndexOperations.resetIndexCache() is no longer supported.

  • Any MapReduceOptions.extraOption is silently ignored.

  • WriteResult does not longer hold error informations but throws an Exception.

  • MongoOperations.executeInSession(…) no longer calls requestStart / requestDone.

  • Index name generation has become a driver internal operations, still we use the 2.x schema to generate names.

  • Some Exception messages differ between the generation 2 and 3 servers as well as between MMap.v1 and WiredTiger storage engine.

Appendix

Appendix A: Namespace reference

The <repositories /> element

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.[3]

Table 8. Attributes
Name Description

base-package

Defines the package to be used to be scanned for repository interfaces extending *Repository (actual interface is determined by specific Spring Data module) in auto detection mode. All packages below the configured package will be scanned, too. Wildcards are allowed.

repository-impl-postfix

Defines the postfix to autodetect custom repository implementations. Classes whose names end with the configured postfix will be considered as candidates. Defaults to Impl.

query-lookup-strategy

Determines the strategy to be used to create finder queries. See Query lookup strategies for details. Defaults to create-if-not-found.

named-queries-location

Defines the location to look for a Properties file containing externally defined queries.

consider-nested-repositories

Controls whether nested repository interface definitions should be considered. Defaults to false.

Appendix B: Populators namespace reference

The <populator /> element

The <populator /> element allows to populate the a data store via the Spring Data repository infrastructure.[4]

Table 9. Attributes
Name Description

locations

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

Appendix C: Repository query keywords

Supported query keywords

The following table lists the 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 listed here might not be supported in a particular store.

Table 10. Query keywords
Logical keyword Keyword expressions

AND

And

OR

Or

AFTER

After, IsAfter

BEFORE

Before, IsBefore

CONTAINING

Containing, IsContaining, Contains

BETWEEN

Between, IsBetween

ENDING_WITH

EndingWith, IsEndingWith, EndsWith

EXISTS

Exists

FALSE

False, IsFalse

GREATER_THAN

GreaterThan, IsGreaterThan

GREATER_THAN_EQUALS

GreaterThanEqual, IsGreaterThanEqual

IN

In, IsIn

IS

Is, Equals, (or no keyword)

IS_NOT_NULL

NotNull, IsNotNull

IS_NULL

Null, IsNull

LESS_THAN

LessThan, IsLessThan

LESS_THAN_EQUAL

LessThanEqual, IsLessThanEqual

LIKE

Like, IsLike

NEAR

Near, IsNear

NOT

Not, IsNot

NOT_IN

NotIn, IsNotIn

NOT_LIKE

NotLike, IsNotLike

REGEX

Regex, MatchesRegex, Matches

STARTING_WITH

StartingWith, IsStartingWith, StartsWith

TRUE

True, IsTrue

WITHIN

Within, IsWithin

Appendix D: 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 listed here might not be supported in a particular store.

Geospatial types like (GeoResult, GeoResults, GeoPage) are only available for data stores that support geospatial queries.
Table 11. Query return types
Return type Description

void

Denotes no return value.

Primitives

Java primitives.

Wrapper types

Java wrapper types.

T

An unique entity. Expects the query method to return one result at most. In case no result is found null is returned. More than one result will trigger an IncorrectResultSizeDataAccessException.

Iterator<T>

An Iterator.

Collection<T>

A Collection.

List<T>

A List.

Optional<T>

A Java 8 or Guava Optional. Expects the query method to return one result at most. In case no result is found Optional.empty()/Optional.absent() is returned. More than one result will trigger an IncorrectResultSizeDataAccessException.

Stream<T>

A Java 8 Stream.

Future<T>

A Future. Expects method to be annotated with @Async and requires Spring’s asynchronous method execution capability enabled.

CompletableFuture<T>

A Java 8 CompletableFuture. Expects method to be annotated with @Async and requires Spring’s asynchronous method execution capability enabled.

ListenableFuture

A org.springframework.util.concurrent.ListenableFuture. Expects method to be annotated with @Async and requires Spring’s asynchronous method execution capability enabled.

Slice

A sized chunk of data with information whether there is more data available. Requires a Pageable method parameter.

Page<T>

A Slice with additional information, e.g. the total number of results. Requires a Pageable method parameter.

GeoResult<T>

A result entry with additional information, e.g. distance to a reference location.

GeoResults<T>

A list of GeoResult<T> with additional information, e.g. average distance to a reference location.

GeoPage<T>

A Page with GeoResult<T>, e.g. average distance to a reference location.


1. JavaConfig in the Spring reference documentation
2. Spring HATEOAS - https://github.com/SpringSource/spring-hateoas
3. see XML configuration
4. see XML configuration