Spring Data MongoDB - Reference Documentation

Authors

Mark Pollack, Thomas Risberg, Oliver Gierke, Costin Leau, Jon Brisbin, Thomas Darimont

1.4.0.BUILD-SNAPSHOT

Copies of this document may be made for your own use and for distribution to others, provided that you do not charge any fee for such copies and further provided that each copy contains this Copyright Notice, whether distributed in print or electronically.


Table of Contents

Preface
I. Introduction
1. Why Spring Data - Document?
2. Requirements
3. Additional Help Resources
3.1. Support
3.1.1. Community Forum
3.1.2. Professional Support
3.2. Following Development
4. Working with Spring Data Repositories
4.1. Core concepts
4.2. Query methods
4.2.1. Defining repository interfaces
Fine-tuning repository definition
4.2.2. Defining query methods
Query lookup strategies
Query creation
Property expressions
Special parameter handling
4.2.3. Creating repository instances
XML configuration
JavaConfig
Standalone usage
4.3. Custom implementations for Spring Data repositories
4.3.1. Adding custom behavior to single repositories
4.3.2. Adding custom behavior to all repositories
4.4. Spring Data extensions
4.4.1. Web support
Basic web support
Hypermedia support for Pageables
4.4.2. Repository populators
4.4.3. Legacy web support
Domain class web binding for Spring MVC
Web pagination
II. Reference Documentation
5. MongoDB support
5.1. Getting Started
5.2. Examples Repository
5.3. Connecting to MongoDB with Spring
5.3.1. Registering a Mongo instance using Java based metadata
5.3.2. Registering a Mongo instance using XML based metadata
5.3.3. The MongoDbFactory interface
5.3.4. Registering a MongoDbFactory instance using Java based metadata
5.3.5. Registering a MongoDbFactory instance using XML based metadata
5.4. Introduction to MongoTemplate
5.4. . Instantiating MongoTemplate
WriteResultChecking Policy
WriteConcern
WriteConcernResolver
5.5. Saving, Updating, and Removing Documents
5.5.1. How the '_id' field is handled in the mapping layer
5.5.2. Type mapping
5.5.3. Methods for saving and inserting documents
Which collection will my documents be saved into?
Inserting or saving individual objects
Inserting several objects in a batch
5.5.4. Updating documents in a collection
Methods for executing updates for documents
Methods for the Update class
5.5.5. Upserting documents in a collection
5.5.6. Finding and Upserting documents in a collection
5.5.7. Methods for removing documents
5.6. Querying Documents
5.6.1. Querying documents in a collection
Methods for the Criteria class
Methods for the Query class
5.6.2. Methods for querying for documents
5.6.3. GeoSpatial Queries
Geo near queries
5.7. Map-Reduce Operations
5.7.1. Example Usage
5.8. Group Operations
5.8.1. Example Usage
5.9. Aggregation Framework Support
5.9.1. Basic Concepts
5.9.2. Supported Aggregation Operations
5.9.3. Projection Expressions
Spring Expresison Support in Projection Expressions
5.9.4. Aggregation Framework Examples
5.10. Overriding default mapping with custom converters
5.10.1. Saving using a registered Spring Converter
5.10.2. Reading using a Spring Converter
5.10.3. Registering Spring Converters with the MongoConverter
5.10.4. Converter disambiguation
5.11. Index and Collection managment
5.11.1. Methods for creating an Index
5.11.2. Accessing index information
5.11.3. Methods for working with a Collection
5.12. Executing Commands
5.12.1. Methods for executing commands
5.13. Lifecycle Events
5.14. Exception Translation
5.15. Execution callbacks
5.16. GridFS support
6. MongoDB repositories
6.1. Introduction
6.2. Usage
6.3. Query methods
6.3.1. Geo-spatial repository queries
6.3.2. MongoDB JSON based query methods and field restriction
6.3.3. Type-safe Query methods
6.4. Miscellaneous
6.4.1. CDI Integration
7. Mapping
7.1. Convention based Mapping
7.1.1. How the '_id' field is handled in the mapping layer
7.2. Mapping Configuration
7.3. Metadata based Mapping
7.3.1. Mapping annotation overview
7.3.2. Customized Object Construction
7.3.3. Compound Indexes
7.3.4. Using DBRefs
7.3.5. Mapping Framework Events
7.3.6. Overriding Mapping with explicit Converters
8. Cross Store support
8.1. Cross Store Configuration
8.2. Writing the Cross Store Application
9. Logging support
9.1. MongoDB Log4j Configuration
10. JMX support
10.1. MongoDB JMX Configuration
III. Appendix
A. Namespace reference
A.1. The <repositories /> element
B. Repository query keywords
B.1. Supported query keywords

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.

Part I. Introduction

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

1. Why Spring Data - Document?

The Spring Framework is the leading full-stack Java/JEE application framework. It provides a lightweight container and a non-invasive programming model enabled by the use of dependency injection, AOP, and portable service abstractions.

NoSQL storages provide an alternative to classical RDBMS for horizontal scalability and speed. In terms of implementation, Document stores represent one of the most popular types of stores in the NoSQL space. The document database supported by Spring Data are MongoDB and CouchDB, though just MongoDB integration has been released to date.

The goal of the Spring Data Document (or DATADOC) framework is to provide an extension to the Spring programming model that supports writing applications that use Document databases. The Spring framework has always promoted a POJO programming model with a strong emphasis on portability and productivity. These values are caried over into Spring Data Document.

Notable features that are used in Spring Data Document from the Spring framework are the Features that particular, features from the Spring framework that are used are the Conversion Service, JMX Exporters, portable Data Access Exception hierarchy, Spring Expression Language, and Java based IoC container configuration. The programming model follows the familiar Spring 'template' style, so if you are familar with Spring template classes such as JdbcTemplate, JmsTemplate, RestTemplate, you will feel right at home. For example, MongoTemplate removes much of the boilerplate code you would have to write when using the MongoDB driver to save POJOs as well as a rich java based query interface to retrieve POJOs. The programming model also offers a new Repository approach in which the Spring container will provide an implementation of a Repository based soley off an interface definition which can also include custom finder methods.

2. Requirements

Spring Data Document 1.x binaries requires JDK level 6.0 and above, and Spring Framework 3.0.x and above.

In terms of document stores, MongoDB preferably version 1.6.5 or later or CouchDB 1.0.1 or later are required.

3. 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:

3.1 Support

There are a few support options available:

3.1.1 Community Forum

The Spring Data forum is a message board for all Spring Data (not just Document) users to share information and help each other. Note that registration is needed only for posting.

3.1.2 Professional Support

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

3.2 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 Spring Community forums. 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 SpringSource Data blog or the project team on Twitter (SpringData)

4. 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.

[Important]Important

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. Appendix A, Namespace reference covers XML configuration which is supported across all Spring Data modules supporting the repository API, Appendix B, Repository query keywords covers the query method 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.

4.1 Core concepts

The central interface in Spring Data repository abstraction is Repository (probably not that much of a surprise). It takes the 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 4.1. CrudRepository interface

public interface CrudRepository<T, ID extends Serializable>
    extends Repository<T, ID> {
                                                                                                                       (1)
    <S extends T> S save(S entity);
                                                                                                                       (2)
    T findOne(ID primaryKey);
                                                                                                                       (3)
    Iterable<T> findAll();

    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.


Usually we will have persistence technology specific sub-interfaces to include additional technology specific methods. We will now ship implementations for a variety of Spring Data modules that implement CrudRepository.

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

Example 4.2. 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));

4.2 Query methods

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

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

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

    List<Person> findByLastname(String lastname);
  3. Set up Spring to create proxy instances for those interfaces.

    <?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>
    [Note]Note

    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.

  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.

4.2.1 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.

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.

Example 4.3. Selectively exposing CRUD methods

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 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.

4.2.2 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 an additionally created query. Available options depend on the actual store. However, there's got to be an strategy that decides what actual query is created. Let's have a look at the available options.

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. Some strategies may not be supported for particular datastores.

CREATE

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 the section called “Query creation”.

USE_DECLARED_QUERY

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)

CREATE_IF_NOT_FOUND 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.

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, 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 4.4. 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 Strings, 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 the section called “Special parameter handling”.

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 Persons have Addresses with ZipCodes. 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);

Special parameter handling

To handle parameters to 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 4.5. Using Pageable and Sort in query methods

Page<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. 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.

[Note]Note

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.

4.2.3 Creating repository instances

In this section you create instances and bean definitions for the repository interfaces defined. The easiest way to do so is by using the Spring namespace that is shipped with each Spring Data module that supports the repository mechanism.

XML configuration

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

<?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 subpackages for interfaces extending Repository or one of its subinterfaces. 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 have a pattern of scanned packages.

Using filters

By default the infrastructure picks up every interface extending the persistence technology-specific Repository subinterface 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 4.6. 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.


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 4.7. Sample annotation based repository configuration

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

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

[Note]Note

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.

Standalone usage

You can also use the repository infrastructure outside of a Spring container. 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 4.8. Standalone usage of repository factory

RepositoryFactorySupport factory = … // Instantiate factory here
UserRepository repository = factory.getRepository(UserRepository.class);

4.3 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.

4.3.1 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 4.9. Interface for custom repository functionality

interface UserRepositoryCustom {

  public void someCustomMethod(User user);
}

Example 4.10. Implementation of custom repository functionality

class UserRepositoryImpl implements UserRepositoryCustom {

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

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, take part in aspects, and so on.


Example 4.11. Changes to the your basic repository interface

public interface UserRepository extends CrudRepository<User, Long>, UserRepositoryCustom {

  // Declare query methods here
}

Let your standard repository interface extend the custom one. Doing so makes CRUD and custom functionality 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 4.12. 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, where the second example will try to lookup com.acme.repository.UserRepositoryFooBar.

Manual wiring

The preceding approach 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 4.13. Manual wiring of custom implementations (I)

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

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

4.3.2 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.

  1. To add custom behavior to all repositories, you first add an intermediate interface to declare the shared behavior.

    Example 4.14. An interface declaring custom shared behavior

    public interface MyRepository<T, ID extends Serializable>
      extends JpaRepository<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.

  2. 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 4.15. Custom repository base class

    public class MyRepositoryImpl<T, ID extends Serializable>
      extends SimpleJpaRepository<T, ID> implements MyRepository<T, ID> {
    
      private EntityManager entityManager;
    
      // There are two constructors to choose from, either can be used.
      public MyRepositoryImpl(Class<T> domainClass, EntityManager entityManager) {
        super(domainClass, entityManager);
    
        // This is the recommended method for accessing inherited class dependencies.
        this.entityManager = entityManager;
      }
    
      public void sharedCustomMethod(ID id) {
        // implementation goes here
      }
    }

    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 or move it outside of the configured base-package.

  3. Then create a custom repository factory to replace the default RepositoryFactoryBean that will in turn produce a custom RepositoryFactory. The new repository factory will then provide your MyRepositoryImpl as the implementation of any interfaces that extend the Repository interface, replacing the SimpleJpaRepository implementation you just extended.

    Example 4.16. Custom repository factory bean

    public class MyRepositoryFactoryBean<R extends JpaRepository<T, I>, T, I extends Serializable>
      extends JpaRepositoryFactoryBean<R, T, I> {
    
      protected RepositoryFactorySupport createRepositoryFactory(EntityManager entityManager) {
    
        return new MyRepositoryFactory(entityManager);
      }
    
      private static class MyRepositoryFactory<T, I extends Serializable> extends JpaRepositoryFactory {
    
        private EntityManager entityManager;
    
        public MyRepositoryFactory(EntityManager entityManager) {
          super(entityManager);
    
          this.entityManager = entityManager;
        }
    
        protected Object getTargetRepository(RepositoryMetadata metadata) {
    
          return new MyRepositoryImpl<T, I>((Class<T>) metadata.getDomainClass(), entityManager);
        }
    
        protected Class<?> getRepositoryBaseClass(RepositoryMetadata metadata) {
    
          // The RepositoryMetadata can be safely ignored, it is used by the JpaRepositoryFactory
          //to check for QueryDslJpaRepository's which is out of scope.
          return MyRepository.class;
        }
      }
    }

  4. Finally, either declare beans of the custom factory directly or use the factory-class attribute of the Spring namespace to tell the repository infrastructure to use your custom factory implementation.

    Example 4.17. Using the custom factory with the namespace

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

4.4 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.

4.4.1 Web support

[Note]Note

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 Section 4.4.3, “Legacy web support”.

Also note that the JavaConfig support introduced in Spring Data Commons 1.6 requires Spring 3.2 due to some issues with JavaConfig and overridden methods in Spring 3.1.

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 4.18. 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 4.19. 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 4.20. 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.

[Note]Note

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 4.21. 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 4.1. Request parameters evaluated for Pageable instances

pagePage you want to retrieve.
sizeSize of the page you want to retrieve.
sortProperties 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 Pageables or Sorts 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 enrichting 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 4.22. 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.

4.4.2 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 4.23. 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 4.24. 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:jackson-populator location="classpath:data.json" />

</beans>

This declaration causes the data.json file being read, deserialized by 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 4.25. 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 location="classpath:data.json" unmarshaller-ref="unmarshaller" />

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

</beans>

4.4.3 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!");
    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";
  }
}
ConversionService

In Spring 3.0 and later the PropertyEditor support is superseded by a new conversion infrastructure that eliminates the drawbacks of PropertyEditors and uses a stateless X to Y conversion approach. Spring Data now ships with a DomainClassConverter that mimics the behavior of DomainClassPropertyEditorRegistrar. To configure, simply declare a bean instance and pipe the ConversionService being used into its constructor:

<mvc:annotation-driven conversion-service="conversionService" />

<bean class="org.springframework.data.repository.support.DomainClassConverter">
  <constructor-arg ref="conversionService" />
</bean>

If you are using JavaConfig, you can simply extend Spring MVC's WebMvcConfigurationSupport and hand the FormatingConversionService that the configuration superclass provides into the DomainClassConverter instance you create.

class WebConfiguration extends WebMvcConfigurationSupport {

  // Other configuration omitted

  @Bean
  public DomainClassConverter<?> domainClassConverter() {
    return new DomainClassConverter<FormattingConversionService>(mvcConversionService());
  }
}

Web pagination

When working with pagination in the web layer you usually have to write a lot of boilerplate code yourself to extract the necessary metadata from the request. The less desirable approach shown in the example below requires the method to contain an HttpServletRequest parameter that has to be parsed manually. This example also omits appropriate failure handling, which would make the code even more verbose.

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

  // DI code omitted

  @RequestMapping
  public String showUsers(Model model, HttpServletRequest request) {

    int page = Integer.parseInt(request.getParameter("page"));
    int pageSize = Integer.parseInt(request.getParameter("pageSize"));

    Pageable pageable = new PageRequest(page, pageSize);

    model.addAttribute("users", userService.getUsers(pageable));
    return "users";
  }
}

The bottom line is that the controller should not have to handle the functionality of extracting pagination information from the request. So Spring Data ships with a PageableHandlerArgumentResolver that will do the work for you. The Spring MVC JavaConfig support exposes a WebMvcConfigurationSupport helper class to customize the configuration as follows:

@Configuration
public class WebConfig extends WebMvcConfigurationSupport {

  @Override
  public void configureMessageConverters(List<HttpMessageConverter<?>> converters) {
    converters.add(new PageableHandlerArgumentResolver());
  }
}

If you're stuck with XML configuration you can register the resolver as follows:

<bean class="….web.servlet.mvc.method.annotation.RequestMappingHandlerAdapter">
  <property name="customArgumentResolvers">
    <list>
      <bean class="org.springframework.data.web.PageableHandlerArgumentResolver" />
    </list>
  </property>
</bean>

When using Spring 3.0.x versions use the PageableArgumentResolver instead. Once you've configured the resolver with Spring MVC it allows you to simplify controllers down to something like this:

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

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

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

The PageableArgumentResolver automatically resolves request parameters to build a PageRequest instance. By default it expects the following structure for the request parameters.

Table 4.2. Request parameters evaluated by PageableArgumentResolver

pagePage you want to retrieve.
page.sizeSize of the page you want to retrieve.
page.sortProperty that should be sorted by.
page.sort.dirDirection that should be used for sorting.

In case you need multiple Pageables 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 and the related subproperties.

Configuring a global default on bean declaration

The PageableArgumentResolver will use a PageRequest with the first page and a page size of 10 by default. It will use that value if it cannot resolve a PageRequest from the request (because of missing parameters, for example). You can configure a global default on the bean declaration directly. If you might need controller method specific defaults for the Pageable, annotate the method parameter with @PageableDefaults and specify page (through pageNumber), page size (through value), sort (list of properties to sort by), and sortDir (the direction to sort by) as annotation attributes:

public String showUsers(Model model, 
  @PageableDefaults(pageNumber = 0, value = 30) Pageable pageable) { … }

Part II. Reference Documentation

Document Structure

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

Chapter 5, MongoDB support introduces the MongoDB module feature set.

Chapter 6, MongoDB repositories introduces the repository support for MongoDB.

5. 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 implementatin of Repository interfaces including support for custom finder methods.

  • QueryDSL integration to support type-safe queries.

  • Cross-store persistance - 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 org.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.

5.1 Getting Started

Spring MongoDB support requires MongoDB 1.4 or higher and Java SE 5 or higher. The latest production release (2.0.x as of this writing) is recommended. 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>1.1.0.RELEASE</version>
  </dependency>

</dependencies>

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

<spring.framework.version>3.1.2.RELEASE</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.springsource.org/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.document.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

5.2 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.

5.3 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.

[Note]Note

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.

5.3.1 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 5.1. 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 MongoFactoryBean. 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 annoated 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 5.2. Registering a com.mongodb.Mongo object using Spring's MongoFactoryBean and enabling Spring's exception translation support

@Configuration
public class AppConfig {

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

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


5.3.2 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 alows 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 5.3. 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 5.4. 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 5.5. XML schema to configure com.mongodb.Mongo object with Replica Sets

<mongo:mongo id="replicaSetMongo" replica-set="127.0.0.1:27017,localhost:27018"/>	   


5.3.3 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 contiainer 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.

5.3.4 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());
  }
}

5.3.5 Registering a MongoDbFactory instance using XML based metadata

The mongo namespace provides a convient 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 show the use of a property placeholder to parameterise 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>

5.4 Introduction to MongoTemplate

The class MongoTemplate, located in the package org.springframework.data.document.mongodb, is the central class of the Spring's MongoDB support providng 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.

[Note]Note

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 MongoCoverters 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 as as 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 MongOperations 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 operatiosn.

[Note]Note

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 additonal 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.

[Note]Note

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 Execution Callbacks for more information.

Now let's look at a examples of how to work with the MongoTemplate in the context of the Spring container.

5.4.  Instantiating MongoTemplate

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

Example 5.6. 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.

[Note]Note

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

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 WriteResultChecking 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.

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.

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();
  }
}

5.5 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.

[Note]Note

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.

[Note]Note

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 stynax used in the example is explained in more detail in the section Querying Documents.

5.5.1 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.

5.5.2 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. It's default behaviour 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 5.7. 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 persistet 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 5.8. 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 5.9. 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 5.10. Configuring a custom MongoTypeMapper via XML

<mongo:mapping-converter type-mapper-ref="customMongoTypeMapper"/>

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

5.5.3 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>.

[Note]Note

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 qualfied) of the class. You may also call the save operation with a specific collection name. The collection to store the object can be overriden using mapping metadata.

When inserting or saving, if the Id property is not set, the assumption is that its value will be autogenerated by the database. As such, for autogeneration 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 5.11. 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 Insert 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 ispects each object and inserts it to the appropriate collection based on the rules specified above.

  • save Save the object ovewriting 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.

5.5.4 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 5.12. 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 kickstart 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

5.5.5 Upserting documents in a collection

Related to perfomring 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);

5.5.6 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 snippit 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));

5.5.7 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.

5.6 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 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 5.13. 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.

5.6.1 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 5.14. 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 retuns 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 withinCenter (Circle circle) Creates a geospatial criterion using $within $center operators

  • Criteria withinCenterSphere (Circle circle) Creates a geospatial criterion using $within $center operators. This is only available for MongoDB 1.7 and higher.

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

  • 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 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)

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

5.6.2 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.

5.6.3 GeoSpatial Queries

MongoDB supports GeoSpatial queries through the use of operators such as $near, $within, 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").withinCenter(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").withinCenterSphere(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").withinBox(box)), Venue.class);

To find venues near a Point, the following query 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);

To find venues near a Point using spherical coordines 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 to access the average distance of all results. A single GeoResult object simply carries the entity found plus its distance from the origin.

5.7 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.

5.7.1 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 occurance 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 occurance 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.

5.8 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 shareded 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.

5.8.1 Example Usage

In order to understand how group operations work the following example is used, which is somewhat artifical. 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 tha 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);

5.9 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:The MongoDB aggregation framework provides a means to calculate aggregated values without having to use map-reduce. While map-reduce is powerful, it is often more difficult than necessary for many simple aggregation tasks, such as totaling or averaging field values.

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

5.9.1 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 pipline instructions. Aggregations are created by inoking 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 aggreation 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 explicity input-collection is provided the latter takes precedence.

5.9.2 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

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

Table 5.1. Aggregation Operations currently supported by Spring Data MongoDB

Pipeline Aggregation Operatorsproject, skip, limit, unwind, group, sort, geoNear
Group Aggregation OperatorsaddToSet, first, last, max, min, avg, push, sum, (*count)
Arithmetic Aggregation Operatorsadd (*via plus), subtract (*via minus), multiply, divide, mod
Comparison Aggregation Operatorseq (*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.

5.9.3 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.

Example 5.15. 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 Expresison 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.

Example 5.16. Complex calulations 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 Example 5.21, “Aggregation Framework Example 5” and Example 5.22, “Aggregation Framework Example 6”. You can find more usage examples for supported SpEL expression constructs in SpelExpressionTransformerUnitTests.

5.9.4 Aggregation Framework Examples

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

Example 5.17. Aggregation Framework Example 1

In this introductory example we want to aggregate a list of tags to get the occurence count of a particular tag from a MongoDB collection called "tags" sorted by the occurence 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 occurence 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 occurence count in descending order via the sort operation.

  • Finally we call the aggregate Method on the MongoTemplate in order to let MongoDB perform the acutal 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.

Example 5.18. 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 implict 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.

Example 5.19. 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.

Example 5.20. 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.

Example 5.21. 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();

Example 5.22. 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 shippingCosts 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.

5.10 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.

[Note]Note

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

5.10.1 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;
  }
}

5.10.2 Reading using a Spring Converter

An example implemention of a Converter that converts from a DBObject ot a Person object is shownn 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;
  }
}

5.10.3 Registering Spring Converters with the MongoConverter

The Mongo Spring namespace provides a convenience way to register Spring Converters 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>

5.10.4 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 Strings into Longs 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 at the converter implementation.

5.11 Index and Collection managment

MongoTemplate provides a few methods for managing indexes and collections. These are collected into a helper interface called IndexOperations. You access these operations by calilng 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();
}

5.11.1 Methods for creating an Index

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

Example 5.23. 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 both standard indexes and geospatial indexes using the classes IndexDefinition and GeoSpatialIndex respectfully. 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"));

5.11.2 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 collectcion. 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]]

5.11.3 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 5.24. 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.

5.12 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.

5.12.1 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.

5.13 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 infastructure 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.

Example 5.25. 

public class BeforeConvertListener extends AbstractMongoEventListener<Person> {
  @Override
  public void onBeforeConvert(Person p) {
    ... 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.

Example 5.26. 

public class BeforeSaveListener extends AbstractMongoEventListener<Person> {
  @Override
  public void onBeforeSave(Person p, DBObject dbo) {
    … 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 MongoTempnlate find, findAndRemove, findOne and getCollection methods after the DBObject is retrieved from the database.

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

5.14 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.

5.15 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 thexe 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;
  }
});

5.16 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 5.27. 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 5.28. 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>

You can no get the template injected and perform storing and retrieving operations to it.

Example 5.29. 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 marshalled 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 5.30. 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")))
  }
}

[Note]Note

Currently MongoDB does not support defining sort criterias when retrieving files from GridFS. Thus any sort criterias 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 5.31. 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.

6. MongoDB repositories

6.1 Introduction

This chapter will point out the specialties for repository support for MongoDB. This builds on the core repository support explained in Chapter 4, Working with Spring Data Repositories. So make sure you've got a sound understanding of the basic concepts explained there.

6.2 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 6.1. 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 typeObjectId. The default serialization mechanism used in MongoTemplate (which is backing the repository support) regards properties named id as document id. Currently we supportString, ObjectId and BigInteger as id-types.

Example 6.2. 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 6.3. 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 6.4. 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 Persons at a page size of 10 would simply look something like this:

Example 6.5. 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.

6.3 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 6.6. PersonRepository with query methods

public interface PersonRepository extends PagingAndSortingRepository<Person, String> {

    List<Person> findByLastname(String lastname);

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

    Person findByShippingAddresses(Address address);

}     

The first 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}. The second example shows how pagination is applied 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. The third examples shows that you can query based on properties which are not a primitive type.

[Note]Note

Note that for version 1.0 we currently don't support referring to parameters that are mapped as DBRef in the domain class.

Table 6.1. Supported keywords for query methods

KeywordSampleLogical result
GreaterThanfindByAgeGreaterThan(int age){"age" : {"$gt" : age}}
LessThanfindByAgeLessThan(int age){"age" : {"$lt" : age}}
BetweenfindByAgeBetween(int from, int to){"age" : {"$gt" : from, "$lt" : to}}
IsNotNull, NotNullfindByFirstnameNotNull(){"age" : {"$ne" : null}}
IsNull, NullfindByFirstnameNull(){"age" : null}
LikefindByFirstnameLike(String name){"age" : age} ( age as regex)
RegexfindByFirstnameRegex(String firstname){"firstname" : {"$regex" : firstname }}
(No keyword)findByFirstname(String name){"age" : name}
NotfindByFirstnameNot(String name){"age" : {"$ne" : name}}
NearfindByLocationNear(Point point){"location" : {"$near" : [x,y]}}
WithinfindByLocationWithin(Circle circle){"location" : {"$within" : {"$center" : [ [x, y], distance]}}}
WithinfindByLocationWithin(Box box){"location" : {"$within" : {"$box" : [ [x1, y1], x2, y2]}}}True
IsTrue, TruefindByActiveIsTrue(){"active" : true}
IsFalse, FalsefindByActiveIsFalse(){"active" : false}
ExistsfindByLocationExists(boolean exists){"location" : {"$exists" : exists }}


6.3.1 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 look at some examples:

Example 6.7. 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 6.8. 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.

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);

  // {'geoNear' : 'location', 'near' : [x, y] }
  GeoResults<Person> findByLocationNear(Point location);
}

6.3.2 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.

6.3.3 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 using 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 additiion 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.

6.4 Miscellaneous

6.4.1 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 an 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();
  }
}

7. Mapping

Rich maping 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.

[Note]Note

SimpleMongoConverter has been deprecated in Spring Data MongoDB M3 as all of its functionality has been subsumed into MappingMongoConverter.

7.1 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. Otherewise the zero arg constructor will be used. if there is more than one non-zero argument constructor an exception will be thrown.

7.1.1 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 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 delected 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.

7.2 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 7.1. @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

  @Override
  protected void afterMappingMongoConverterCreation(MappingMongoConverter converter) {
    Set<Converter<?, ?>> converterList = new HashSet<Converter<?, ?>>();
    converterList.add(new org.springframework.data.mongodb.test.PersonReadConverter());
    converterList.add(new org.springframework.data.mongodb.test.PersonWriteConverter());
    converter.setCustomConverters(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 @org.springframework.data.mongodb.core.mapping.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 MongoMappingEvents that are posted onto Spring's ApplicationContextEvent infrastructure.

[Note]Note

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 7.2. 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.

7.3 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 @org.springframework.data.mongodb.core.mapping.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 7.3. 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;

}
      

[Important]Important

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 ensureIndex on that property of your document, making searches faster.

7.3.1 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.

  • @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.

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 ommitted

7.3.2 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 an MappingException will be thrown indicating that the given constructor parameter could not be bound.

class OrderItem {
  
  @Id String id;
  int quantity;
  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);
[Note]Note

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.

7.3.3 Compound Indexes

Compound indexes are also supported. They are defined at the class level, rather than on indidvidual properties.

[Note]Note

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 7.4. 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;

}
          


7.3.4 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):

Example 7.5. 

@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're wanting 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.

[Important]Important

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.

7.3.5 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.

7.3.6 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 selectivly handle the conversion for a particular type or to optimize performance.

To selectivly handle the conversion yourself, register one or more one or more org.springframework.core.convert.converter.Converter instances with the MongoConverter.

[Note]Note

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 3 Type Conversion.

The setConverters method on SimpleMongoConverter and MappingMongoConverter should be used for this purpose. The method afterMappingMongoConverterCreation in AbstractMongoConfiguration can be overriden to configure a MappingMongoConverter. The examples here at the begining 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.

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.

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;
  }

}

8. 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 implemenatation 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.

8.1 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 spring-data-mongodb-cross-store module. Using Maven this is done by adding a dependency to your pom:

Example 8.1. 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 8.2. 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 8.3. 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>

8.2 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 persited. 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 succesfull 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 8.4. 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 8.5. 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 8.6. 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 8.7. 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" }

9. 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.

9.1 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.

10. 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.

10.1 MongoDB JMX Configuration

Spring's Mongo namespace enables you to easily enable JMX functionality

Example 10.1. XML schmea 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">

<beans>

    <!-- 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

Part III. Appendix

Appendix A. Namespace reference

A.1 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 A.1. Attributes

NameDescription
base-packageDefines 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-postfixDefines 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-strategyDetermines the strategy to be used to create finder queries. See the section called “Query lookup strategies” for details. Defaults to create-if-not-found.

Appendix B. Repository query keywords

B.1 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 B.1. Query keywords

Logical keywordKeyword expressions
ANDAnd
OROr
AFTERAfter, IsAfter
BEFOREBefore, IsBefore
CONTAININGContaining, IsContaining, Contains
BETWEENBetween, IsBetween
ENDING_WITHEndingWith, IsEndingWith, EndsWith
EXISTSExists
FALSEFalse, IsFalse
GREATER_THANGreaterThan, IsGreaterThan
GREATER_THAN_EQUALSGreaterThanEqual, IsGreaterThanEqual
INIn, IsIn
ISIs, Equals, (or no keyword)
IS_NOT_NULLNotNull, IsNotNull
IS_NULLNull, IsNull
LESS_THANLessThan, IsLessThan
LESS_THAN_EQUALLessThanEqual, IsLessThanEqual
LIKELike, IsLike
NEARNear, IsNear
NOTNot, IsNot
NOT_INNotIn, IsNotIn
NOT_LIKENotLike, IsNotLike
REGEXRegex, MatchesRegex, Matches
STARTING_WITHStartingWith, IsStartingWith, StartsWith
TRUETrue, IsTrue
WITHINWithin, IsWithin