1.4.3.RELEASE
Copyright © 2008-2014 The original authors.
Table of Contents
The Spring Data MongoDB project applies core Spring concepts to the development of solutions using the MongoDB document style data store. We provide a "template" as a high-level abstraction for storing and querying documents. You will notice similarities to the JDBC support in the Spring Framework.
This document is the reference guide for Spring Data - Document Support. It explains Document module concepts and semantics and the syntax for various 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.
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.
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.
The manual introduces MongoDB and contains links to getting started guides, reference documentation and tutorials.
The online shell provides a convenient way to interact with a MongoDB instance in combination with the online tutorial.
MongoDB Java Language Center
Several books available for purchase
Karl Seguin's online book: "The Little MongoDB Book"
Spring Data MongoDB 1.x binaries requires JDK level 6.0 and above, and Spring Framework 3.2.x and above.
In terms of document stores, MongoDB preferably version 2.4.
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:
There are a few support options available:
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.
Professional, from-the-source support, with guaranteed response time, is available from Pivotal Sofware, Inc., the company behind Spring Data and Spring.
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)
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 | |
---|---|
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 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. |
The central interface in Spring Data repository abstraction is
Repository
(probably not that much of a
surprise). It takes the domain class to manage as well as the id type of
the domain class as type arguments. This interface acts primarily as a
marker interface to capture the types to work with and to help you to
discover interfaces that extend this one. The
CrudRepository
provides sophisticated CRUD
functionality for the entity class that is being managed.
Example 3.1. CrudRepository
interface
public interface CrudRepository<T, ID extends Serializable> extends Repository<T, ID> { <S extends T> S save(S entity); T findOne(ID primaryKey); Iterable<T> findAll(); Long count(); void delete(T entity); boolean exists(ID primaryKey); // … more functionality omitted. }
Saves the given entity. | |
Returns the entity identified by the given id. | |
Returns all entities. | |
Returns the number of entities. | |
Deletes the given entity. | |
Indicates whether an entity with the given id exists. |
Note | |
---|---|
We also provide persistence technology-specific abstractions like
e.g. |
On top of the CrudRepository
there is
a PagingAndSortingRepository
abstraction
that adds additional methods to ease paginated access to entities:
Example 3.2. 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));
Standard CRUD functionality repositories usually have queries on the underlying datastore. With Spring Data, declaring those queries becomes a four-step process:
Declare an interface extending
Repository
or one of its subinterfaces
and type it to the domain class and ID type that it will
handle.
public interface PersonRepository extends Repository<User, Long> { … }
Declare query methods on the interface.
List<Person> findByLastname(String lastname);
Set up Spring to create proxy instances for those interfaces. Either via JavaConfig:
import org.springframework.data.jpa.repository.config.EnableJpaRepositories; @EnableJpaRepositories class Config {}
or via XML 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:jpa="http://www.springframework.org/schema/data/jpa" xsi:schemaLocation="http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans.xsd http://www.springframework.org/schema/data/jpa http://www.springframework.org/schema/data/jpa/spring-jpa.xsd"> <jpa:repositories base-package="com.acme.repositories"/> </beans>
The JPA namespace is used in this example. If you are using the
repository abstraction for any other store, you need to change this to
the appropriate namespace declaration of your store module which
should be exchanging jpa
in favor of, for example,
mongodb
. Also, note that the JavaConfig variant doesn't
configure a package explictly as the package of the annotated class is
used by default. To customize the package to scan
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.
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
.
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.
Note | |
---|---|
This allows you to define your own abstractions on top of the provided Spring Data Repositories functionality. |
Example 3.3. Selectively exposing CRUD methods
@NoRepositoryBean interface MyBaseRepository<T, ID extends Serializable> extends Repository<T, ID> { T findOne(ID id); T save(T entity); } interface UserRepository extends MyBaseRepository<User, Long> { User findByEmailAddress(EmailAddress emailAddress); }
In this first step you defined a common base interface for all
your domain repositories and exposed
findOne(…)
as well as
save(…)
.These methods will be routed into the
base repository implementation of the store of your choice provided by
Spring Data ,e.g. in the case if JPA
SimpleJpaRepository
, because they are matching
the method signatures in
CrudRepository
. So the
UserRepository
will now be able to save
users, and find single ones by id, as well as triggering a query to
find User
s by their email
address.
Note | |
---|---|
Note, that the intermediate repository interface is annotated
with |
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 manually defined 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.
The following strategies are available for the repository
infrastructure to resolve the query. You can configure the strategy at
the namespace through the query-lookup-strategy
attribute
in case of XML configuration or via the
queryLookupStrategy
attribute of the
Enable${store}Repositories
annotation in case
of Java config. Some strategies may not be supported for particular
datastores.
CREATE
attempts to construct a store-specific
query from the query method name. The general approach is to remove
a given set of well-known prefixes from the method name and parse
the rest of the method. Read more about query construction in the section called “Query creation”.
USE_DECLARED_QUERY
tries to find a declared query
and will throw an exception in case it can't find one. The query can
be defined by an annotation somewhere or declared by other means.
Consult the documentation of the specific store to find available
options for that store. If the repository infrastructure does not
find a declared query for the method at bootstrap time, it
fails.
CREATE_IF_NOT_FOUND
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.
The query builder mechanism built into Spring Data repository
infrastructure is useful for building constraining queries over
entities of the repository. The mechanism strips the prefixes
find…By
, read…By
, query…By
,
count…By
, and get…By
from the method and
starts parsing the rest of it. The introducing clause can contain
further expressions such as a Distinct
to set a distinct
flag on the query to be created. However, the first By
acts as delimiter to indicate the start of the actual criteria. At a
very basic level you can define conditions on entity properties and
concatenate them with And
and Or
.
Example 3.4. 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
String
s, 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 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 Person
s
have Address
es with
ZipCode
s. 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);
If your property names contain underscores (e.g.
first_name
) you can escape the underscore in the method
name with a second underscore. For a first_name
property
the query method would have to be named
findByFirst__name(…)
.
To handle parameters in your query you simply define method
parameters as already seen in the examples above. Besides that the
infrastructure will recognize certain specific types like
Pageable
and
Sort
to apply pagination and sorting to your
queries dynamically.
Example 3.5. 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 | |
---|---|
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. |
In this section you create instances and bean definitions for the repository interfaces defined. One way to do so is using the Spring namespace that is shipped with each Spring Data module that supports the repository mechanism although we generally recommend to use the Java-Config style configuration.
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
define a pattern of scanned packages.
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 3.6. 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.
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 3.7. Sample annotation based repository configuration
@Configuration @EnableJpaRepositories("com.acme.repositories") class ApplicationConfiguration { @Bean public EntityManagerFactory entityManagerFactory() { // … } }
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
|
You can also use the repository infrastructure outside of a
Spring container, e.g. in CDI environments. You still need some Spring
libraries in your classpath, but generally you can set up repositories
programmatically as well. The Spring Data modules that provide
repository support ship a persistence technology-specific
RepositoryFactory
that you can use as
follows.
Example 3.8. Standalone usage of repository factory
RepositoryFactorySupport factory = … // Instantiate factory here UserRepository repository = factory.getRepository(UserRepository.class);
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.
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 3.9. Interface for custom repository functionality
interface UserRepositoryCustom { public void someCustomMethod(User user); }
Example 3.10. Implementation of custom repository functionality
class UserRepositoryImpl implements UserRepositoryCustom { public void someCustomMethod(User user) { // Your custom implementation } }
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 like a
|
Example 3.11. 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 combines the CRUD and custom functionality and makes it available to clients.
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 3.12. 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, whereas the second example will
try to lookup
com.acme.repository.UserRepositoryFooBar
.
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 3.13. Manual wiring of custom implementations (I)
<repositories base-package="com.acme.repository" /> <beans:bean id="userRepositoryImpl" class="…"> <!-- further configuration --> </beans:bean>
The preceding approach is not feasible when you want to add a single method to all your repository interfaces.
To add custom behavior to all repositories, you first add an intermediate interface to declare the shared behavior.
Example 3.14. 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.
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 3.15. 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
.
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 3.16. 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; } } }
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 3.17. Using the custom factory with the namespace
<repositories base-package="com.acme.repository" factory-class="com.acme.MyRepositoryFactoryBean" />
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.
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 3.4.3, “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 3.18. 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 3.19. 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" />
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.
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 3.20. 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 | |
---|---|
Currently the repository has to implement
|
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 3.21. 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 3.1. Request parameters evaluated for Pageable instances
page | Page you want to retrieve. |
size | Size of the page you want to retrieve. |
sort | Properties that should be sorted by in the format
property,property(,ASC|DESC) . Default sort
direction is ascending. Use multiple sort
parameters if you want to switch directions, e.g.
?sort=firstname&sort=lastname,asc . |
To customize this behavior extend either
SpringDataWebConfiguration
or the
HATEOAS-enabled equivalent and override the
pageableResolver()
or
sortResolver()
methods and import your
customized configuration file instead of using the
@Enable
-annotation.
In case you need multiple
Pageable
s or
Sort
s 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.
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 3.22. 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.
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 3.23. 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 3.24. 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 locations="classpath:data.json" /> </beans>
This declaration causes the data.json
file to
be read and deserialized via a Jackson
ObjectMapper
. The type to which the JSON object will be unmarshalled to will
be determined by inspecting the _class
attribute of the
JSON document. The infrastructure will eventually select the appropriate
repository to handle the object just deserialized.
To rather use XML to define the data the repositories shall be
populated with, you can use the unmarshaller-populator
element. You configure it to use one of the XML marshaller options
Spring OXM provides you with. See the Spring reference
documentation for details.
Example 3.25. 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 locations="classpath:data.json" unmarshaller-ref="unmarshaller" /> <oxm:jaxb2-marshaller contextPath="com.acme" /> </beans>
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.
For Spring versions before 3.0 simple Java
PropertyEditor
s 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"; } }
In Spring 3.0 and later the
PropertyEditor
support is superseded
by a new conversion infrastructure that eliminates the drawbacks of
PropertyEditor
s 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()); } }
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 3.2. Request parameters evaluated by
PageableArgumentResolver
page | Page you want to retrieve. |
page.size | Size of the page you want to retrieve. |
page.sort | Property that should be sorted by. |
page.sort.dir | Direction that should be used for sorting. |
In case you need multiple
Pageable
s 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.
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) { … }
[1] JavaConfig in the Spring reference documentation - http://static.springsource.org/spring/docs/3.1.x/spring-framework-reference/html/beans.html#beans-java
[2] Spring HATEOAS - https://github.com/SpringSource/spring-hateoas
This part of the reference documentation explains the core functionality offered by Spring Data Document.
Chapter 4, MongoDB support introduces the MongoDB module feature set.
Chapter 5, MongoDB repositories introduces the repository support for MongoDB.
The MongoDB support contains a wide range of features which are summarized below.
Spring configuration support using Java based @Configuration classes or an XML namespace for a Mongo driver instance and replica sets
MongoTemplate helper class that increases productivity performing common Mongo operations. Includes integrated object mapping between documents and POJOs.
Exception translation into Spring's portable Data Access Exception hierarchy
Feature Rich Object Mapping integrated with Spring's Conversion Service
Annotation based mapping metadata but extensible to support other metadata formats
Persistence and mapping lifecycle events
Java based Query, Criteria, and Update DSLs
Automatic implementation of Repository interfaces including support for custom finder methods.
QueryDSL integration to support type-safe queries.
Cross-store 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.
Spring MongoDB support requires MongoDB 1.4 or higher and Java SE 5 or higher. The latest production release (2.4.9 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>1.4.2.RELEASE</version> </dependency> </dependencies>
Also change the version of Spring in the pom.xml to be
<spring.framework.version>3.2.8.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.spring.io/libs-milestone</url> </repository> </repositories>
The repository is also browseable here.
You may also want to set the logging level to DEBUG
to
see some additional information, edit the log4j.properties file to
have
log4j.category.org.springframework.data.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
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.
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 | |
---|---|
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. |
An example of using Java based bean metadata to register an
instance of a com.mongodb.Mongo
is shown below
Example 4.1. 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 4.2. 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.
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 4.3. 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 4.4. 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 4.5. XML schema to configure com.mongodb.Mongo object with Replica Sets
<mongo:mongo id="replicaSetMongo" replica-set="127.0.0.1:27017,localhost:27018"/>
While com.mongodb.Mongo
is the entry point
to the MongoDB driver API, connecting to a specific MongoDB database
instance requires additional information such as the database name and
an optional username and password. With that information you can obtain
a com.mongodb.DB object and access all the functionality of a specific
MongoDB database instance. Spring provides the
org.springframework.data.mongodb.core.MongoDbFactory
interface shown below to bootstrap connectivity to the database.
public interface MongoDbFactory { DB getDb() throws DataAccessException; DB getDb(String dbName) throws DataAccessException; }
The following sections show how you can use the container with
either Java or the XML based metadata to configure an instance of the
MongoDbFactory
interface. In turn, you can use
the MongoDbFactory
instance to configure
MongoTemplate.
The class
org.springframework.data.mongodb.core.SimpleMongoDbFactory
provides implements the MongoDbFactory interface and is created with a
standard com.mongodb.Mongo
instance, the database
name and an optional
org.springframework.data.authentication.UserCredentials
constructor argument.
Instead of using the IoC container to create an instance of MongoTemplate, you can just use them in standard Java code as shown below.
public class MongoApp { private static final Log log = LogFactory.getLog(MongoApp.class); public static void main(String[] args) throws Exception { MongoOperations mongoOps = new MongoTemplate(new SimpleMongoDbFactory(new Mongo(), "database")); mongoOps.insert(new Person("Joe", 34)); log.info(mongoOps.findOne(new Query(where("name").is("Joe")), Person.class)); mongoOps.dropCollection("person"); } }
The code in bold highlights the use of SimpleMongoDbFactory and is the only difference between the listing shown in the getting started section.
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()); } }
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>
Activating auditing functionality is just a matter of adding the
Spring Data Mongo auditing
namespace element to your
configuration:
Example 4.6. Activating auditing using XML configuration
<mongo:auditing mapping-context-ref="customMappingContext" auditor-aware-ref="yourAuditorAwareImpl"/>
Since Spring Data MongoDB 1.4 auditing can be enabled by annotating
a configuration class with the @EnableMongoAuditing
annotation.
Example 4.7. Activating auditing using JavaConfig
@Configuration @EnableMongoAuditing class Config { @Bean public AuditorAware<AuditableUser> myAuditorProvider() { return new AuditorAwareImpl(); } }
If you expose a bean of type
AuditorAware
to the
ApplicationContext
, the auditing
infrastructure will pick it up automatically and use it to determine the
current user to be set on domain types. If you have multiple
implementations registered in the
ApplicationContext
, you can select the one
to be used by explicitly setting the auditorAwareRef
attribute of @EnableJpaAuditing
.
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 | |
---|---|
Once configured, |
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 | |
---|---|
The preferred way to reference the operations on
|
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 | |
---|---|
In the M2 release |
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.
You can use Java to create and register an instance of MongoTemplate as shown below.
Example 4.8. 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 | |
---|---|
The preferred way to reference the operations on
|
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.
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.
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(); } }
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 | |
---|---|
|
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 | |
---|---|
This example is meant to show the use of save, update and remove operations on MongoTemplate and not to show complex mapping functionality |
The query syntax used in the example is explained in more detail in the section Querying Documents.
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.
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 4.9. Type mapping
public class Sample { Contact value; } public abstract class Contact { … } public class Person extends Contact { … } Sample sample = new Sample(); sample.value = new Person(); mongoTemplate.save(sample); { "_class" : "com.acme.Sample", "value" : { "_class" : "com.acme.Person" } }
As you can see we store the type information for the actual root
class persistent as well as for the nested type as it is complex and a
subtype of Contact
. So if you're now using
mongoTemplate.findAll(Object.class, "sample")
we are able to find out that the document stored shall be a
Sample
instance. We are also able to find out
that the value property shall be a Person
actually.
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 4.10. 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.
The following example demonstrates how to configure a custom
MongoTypeMapper
in
MappingMongoConverter
.
Example 4.11. 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 4.12. Configuring a custom MongoTypeMapper via XML
<mongo:mapping-converter type-mapper-ref="customMongoTypeMapper"/> <bean name="customMongoTypeMapper" class="com.bubu.mongo.CustomMongoTypeMapper"/>
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 | |
---|---|
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 auto-generated by the database. As
such, for auto-generation of an ObjectId to succeed the type of the Id
property/field in your class must be either a
String
, ObjectId
, or
BigInteger
.
Here is a basic example of using the save operation and retrieving its contents.
Example 4.13. 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.
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.
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 inspects each object and inserts it to the
appropriate collection based on the rules specified
above.
save Save the object overwriting any object that might exist with the same id.
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.
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 $inc
operator.
Example 4.14. Updating documents using the MongoTemplate
import static org.springframework.data.mongodb.core.query.Criteria.where; import static org.springframework.data.mongodb.core.query.Query; import static org.springframework.data.mongodb.core.query.Update; ... WriteResult wr = mongoTemplate.updateMulti(new Query(where("accounts.accountType").is(Account.Type.SAVINGS)), new Update().inc("accounts.$.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.
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.
The Update class can be used with a little 'syntax sugar' as its
methods are meant to be chained together and you can kick-start the
creation of a new Update instance via the static method
public static Update update(String key, Object
value)
and using static imports.
Here is a listing of methods on the Update class
Update
addToSet
(String key, Object value)
Update using the $addToSet
update
modifier
Update
inc
(String key, Number inc)
Update
using the $inc
update modifier
Update
pop
(String key, Update.Position pos)
Update using the $pop
update
modifier
Update
pull
(String key, Object value)
Update using the $pull
update modifier
Update
pullAll
(String key, Object[] values)
Update using the $pullAll
update
modifier
Update
push
(String key, Object value)
Update using the $push
update modifier
Update
pushAll
(String key, Object[] values)
Update using the $pushAll
update
modifier
Update
rename
(String oldName, String newName)
Update using the $rename
update
modifier
Update
set
(String key, Object value)
Update using the $set
update modifier
Update
unset
(String key)
Update using the
$unset
update modifier
Related to performing an updateFirst
operations, you can also perform an upsert operation which will perform
an insert if no document is found that matches the query. The document
that is inserted is a combination of the query document and the update
document. Here is an example
template.upsert(query(where("ssn").is(1111).and("firstName").is("Joe").and("Fraizer").is("Update")), update("address", addr), Person.class);
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));
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.
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 4.15. 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.
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 4.16. 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.
Criteria
all
(Object o)
Creates a criterion
using the $all
operator
Criteria
and
(String key)
Adds a chained
Criteria
with the specified
key
to the current
Criteria
and returns the newly created
one
Criteria
andOperator (Criteria...
criteria)
Creates an and query using the
$and
operator for all of the provided
criteria (requires MongoDB 2.0 or later)
Criteria
elemMatch (Criteria c)
Creates a criterion using the
$elemMatch
operator
Criteria
exists
(boolean b)
Creates a criterion
using the $exists
operator
Criteria
gt
(Object o)
Creates a criterion
using the $gt
operator
Criteria
gte
(Object o)
Creates a criterion
using the $gte
operator
Criteria
in
(Object... o)
Creates a criterion
using the $in
operator for a varargs
argument.
Criteria
in
(Collection<?> collection)
Creates a criterion using the $in
operator using a collection
Criteria
is
(Object o)
Creates a criterion
using the $is
operator
Criteria
lt
(Object o)
Creates a criterion
using the $lt
operator
Criteria
lte
(Object o)
Creates a criterion
using the $lte
operator
Criteria
mod
(Number value, Number
remainder)
Creates a criterion using the
$mod
operator
Criteria
ne
(Object o)
Creates a criterion
using the $ne
operator
Criteria
nin
(Object... o)
Creates a criterion
using the $nin
operator
Criteria
norOperator (Criteria...
criteria)
Creates an nor query using the
$nor
operator for all of the provided
criteria
Criteria
not
()
Creates a criterion using the
$not
meta operator which affects the clause
directly following
Criteria
orOperator (Criteria...
criteria)
Creates an or query using the
$or
operator for all of the provided
criteria
Criteria
regex
(String re)
Creates a criterion
using a $regex
Criteria
size
(int s)
Creates a criterion using
the $size
operator
Criteria
type
(int t)
Creates a criterion using
the $type
operator
There are also methods on the Criteria class for geospatial queries. Here is a listing but look at the section on GeoSpatial Queries to see them in action.
Criteria
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.
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
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.
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);
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.
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.
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.
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.
In order to understand how group operations work the following example is used, which is somewhat artificial. For a more realistic example consult the book 'MongoDB - The definitive guide'. A collection named "group_test_collection" created with the following rows.
{ "_id" : ObjectId("4ec1d25d41421e2015da64f1"), "x" : 1 } { "_id" : ObjectId("4ec1d25d41421e2015da64f2"), "x" : 1 } { "_id" : ObjectId("4ec1d25d41421e2015da64f3"), "x" : 2 } { "_id" : ObjectId("4ec1d25d41421e2015da64f4"), "x" : 3 } { "_id" : ObjectId("4ec1d25d41421e2015da64f5"), "x" : 3 } { "_id" : ObjectId("4ec1d25d41421e2015da64f6"), "x" : 3 }
We would like to group by the only field in each row, the 'x' field and aggregate the number of times each specific value of 'x' occurs. To do this we need to create an initial document that contains our count variable and also a reduce function which will increment it each time it is encountered. The Java code to execute the group operation is shown below
GroupByResults<XObject> results = mongoTemplate.group("group_test_collection", GroupBy.key("x").initialDocument("{ count: 0 }").reduceFunction("function(doc, prev) { prev.count += 1 }"), XObject.class);
The first argument is the name of the collection to run the group
operation over, the second is a fluent API that specifies properties of
the group operation via a GroupBy
class. In this
example we are using just the intialDocument
and reduceFunction
methods. You can also
specify a key-function, as well as a finalizer as part of the fluent
API. If you have multiple keys to group by, you can pass in a comma
separated list of keys.
The raw results of the group operation is a JSON document that looks like this
{ "retval" : [ { "x" : 1.0 , "count" : 2.0} , { "x" : 2.0 , "count" : 1.0} , { "x" : 3.0 , "count" : 3.0} ] , "count" : 6.0 , "keys" : 3 , "ok" : 1.0 }
The document under the "retval" field is mapped onto the third argument in the group method, in this case XObject which is shown below.
public class XObject { private float x; private float count; public float getX() { return x; } public void setX(float x) { this.x = x; } public float getCount() { return count; } public void setCount(float count) { this.count = count; } @Override public String toString() { return "XObject [x=" + x + " count = " + count + "]"; } }
You can also obtain the raw result as a
DbObject
by calling the method
getRawResults
on the
GroupByResults
class.
There is an additional method overload of the group method on
MongoOperations
which lets you specify a
Criteria
object for selecting a subset of the
rows. An example which uses a Criteria
object,
with some syntax sugar using static imports, as well as referencing a
key-function and reduce function javascript files via a Spring Resource
string is shown below.
import static org.springframework.data.mongodb.core.mapreduce.GroupBy.keyFunction; import static org.springframework.data.mongodb.core.query.Criteria.where; GroupByResults<XObject> results = mongoTemplate.group(where("x").gt(0), "group_test_collection", keyFunction("classpath:keyFunction.js").initialDocument("{ count: 0 }").reduceFunction("classpath:groupReduce.js"), XObject.class);
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.
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
aggregation result in the form of an
DBObject
, to the mapped objects and
information which performed the aggregation.
The canonical example for using the Spring Data MongoDB support for the MongoDB Aggregation Framework looks as follows:
import static org.springframework.data.mongodb.core.aggregation.Aggregation.*; Aggregation agg = newAggregation( pipelineOP1(), pipelineOP2(), pipelineOPn() ); AggregationResults<OutputType> results = mongoTemplate.aggregate(agg, "INPUT_COLLECTION_NAME", OutputType.class); List<OutputType> mappedResult = results.getMappedResults();
Note that if you provide an input class as the first parameter to
the newAggregation
method the
MongoTemplate
will derive the name of the input
collection from this class. Otherwise if you don't not specify an input
class you must provide the name of the input collection explicitly. If
an input-class and an input-collection is provided the latter takes
precedence.
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 4.1. Aggregation Operations currently supported by Spring Data MongoDB
Pipeline Aggregation Operators | project, skip, limit, unwind, group, sort, geoNear |
Group Aggregation Operators | addToSet, first, last, max, min, avg, push, sum, (*count) |
Arithmetic Aggregation Operators | add (*via plus), subtract (*via minus), multiply, divide, mod |
Comparison Aggregation Operators | eq (*via: is), gt, gte, lt, lte, ne |
Note that the aggregation operations not listed here are currently
not supported by Spring Data MongoDB. Comparison aggregation operators
are expressed as Criteria
expressions.
*) The operation is mapped or added by Spring Data MongoDB.
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 4.17. 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: $foo}}
Note that more examples for project operations can be found in
the AggregationTests
class.
Note that further details regarding the projection expressions can be found in the corresponding section of the MongoDB Aggregation Framework reference documentation.
As of Version 1.4.0 we support the use of SpEL expression in
projection expressions via the andExpression
method of the ProjectionOperation
class. This
allows you to define the desired expression as a SpEL expression which
is translated into a corresponding MongoDB projection expression part
on query execution. This makes it much easier to express complex
calculations.
Example 4.18. Complex calculations with SpEL expressions
The following SpEL expression:
1 + (q + 1) / (q - 1)
will be translated into the following projection expression part:
{ "$add" : [ 1, { "$divide" : [ { "$add":["$q", 1]}, { "$subtract":[ "$q", 1]} ] }]}
Have a look at an example in more context in Example 4.23, “Aggregation Framework Example 5” and Example 4.24, “Aggregation Framework Example 6”. You can find more
usage examples for supported SpEL expression constructs in
SpelExpressionTransformerUnitTests
.
The following examples demonstrate the usage patterns for the MongoDB Aggregation Framework with Spring Data MongoDB.
Example 4.19. Aggregation Framework Example 1
In this introductory example we want to aggregate a list of tags
to get the occurrence count of a particular tag from a MongoDB
collection called "tags"
sorted by the occurrence count
in descending order. This example demonstrates the usage of grouping,
sorting, projections (selection) and unwinding (result
splitting).
class TagCount { String tag; int n; }
import static org.springframework.data.mongodb.core.aggregation.Aggregation.*; Aggregation agg = newAggregation( project("tags"), unwind("tags"), group("tags").count().as("n"), project("n").and("tag").previousOperation(), sort(DESC, "n") ); AggregationResults<TagCount> results = mongoTemplate.aggregate(agg, "tags", TagCount.class); List<TagCount> tagCount = results.getMappedResults();
In order to do this we first create a new aggregation via the
newAggregation
static factory method to
which we pass a list of aggregation operations. These aggregate
operations define the aggregation pipeline of our
Aggregation
.
As a second step we select the "tags"
field
(which is an array of strings) from the input collection with the
project
operation.
In a third step we use the unwind
operation to generate a new document for each tag within the
"tags"
array.
In the forth step we use the group
operation to define a group for each "tags"
-value for
which we aggregate the occurrence count via the
count
aggregation operator and collect the
result in a new field called "n"
.
As a fifth step we select the field "n"
and
create an alias for the id-field generated from the previous group
operation (hence the call to previousOperation()
) with
the name "tag"
.
As the sixth step we sort the resulting list of tags by their
occurrence count in descending order via the
sort
operation.
Finally we call the aggregate
Method
on the MongoTemplate in order to let MongoDB perform the 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 4.20. 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 implicit 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 4.21. 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 4.22. 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 4.23. 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 4.24. 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.
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 | |
---|---|
For more information on the Spring type conversion service see the reference docs here. |
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; } }
An example implementation 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; } }
The Mongo Spring namespace provides a convenience way to register
Spring Converter
s with the
MappingMongoConverter
. The configuration snippet
below shows how to manually register converter beans as well as
configuring the wrapping MappingMongoConverter
into a MongoTemplate
.
<mongo:db-factory dbname="database"/> <mongo:mapping-converter> <mongo:custom-converters> <mongo:converter ref="readConverter"/> <mongo:converter> <bean class="org.springframework.data.mongodb.test.PersonWriteConverter"/> </mongo:converter> </mongo:custom-converters> </mongo:mapping-converter> <bean id="readConverter" class="org.springframework.data.mongodb.test.PersonReadConverter"/> <bean id="mongoTemplate" class="org.springframework.data.mongodb.core.MongoTemplate"> <constructor-arg name="mongoDbFactory" ref="mongoDbFactory"/> <constructor-arg name="mongoConverter" ref="mappingConverter"/> </bean>
You can also use the base-package attribute of the
custom-converters element to enable classpath scanning for all
Converter
and
GenericConverter
implementations below
the given package.
<mongo:mapping-converter> <mongo:custom-converters base-package="com.acme.**.converters" /> </mongo:mapping-converter>
Generally we inspect the Converter
implementations for the source and target types they convert from and
to. Depending on whether one of those is a type MongoDB can handle
natively we will register the converter instance as reading or writing
one. Have a look at the following samples:
// Write converter as only the target type is one Mongo can handle natively class MyConverter implements Converter<Person, String> { … } // Read converter as only the source type is one Mongo can handle natively class MyConverter implements Converter<String, Person> { … }
In case you write a Converter
whose
source and target type are native Mongo types there's no way for us to
determine whether we should consider it as reading or writing converter.
Registering the converter instance as both might lead to unwanted
results then. E.g. a Converter<String,
Long>
is ambiguous although it probably does not make
sense to try to convert all String
s into
Long
s 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.
MongoTemplate
provides a few methods for
managing indexes and collections. These are collected into a helper
interface called IndexOperations
. You
access these operations by calling the method
indexOps
and pass in either the collection name
or the java.lang.Class
of your entity (the collection
name will be derived from the .class either by name or via annotation
metadata).
The IndexOperations
interface is
shown below
public interface IndexOperations { void ensureIndex(IndexDefinition indexDefinition); void dropIndex(String name); void dropAllIndexes(); void resetIndexCache(); List<IndexInfo> getIndexInfo(); }
We can create an index on a collection to improve query performance.
Example 4.25. 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"));
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]]
It's time to look at some code examples showing how to use the
MongoTemplate
. First we look at creating our
first collection.
Example 4.26. 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.
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.
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 4.27.
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 4.28.
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.
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.
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; } });
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 4.29. 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 4.30. XML configuration for a GridFsTemplate
<?xml version="1.0" encoding="UTF-8"?> <beans xmlns="http://www.springframework.org/schema/beans" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:mongo="http://www.springframework.org/schema/data/mongo" xsi:schemaLocation="http://www.springframework.org/schema/data/mongo http://www.springframework.org/schema/data/mongo/spring-mongo.xsd http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans.xsd"> <mongo:db-factory id="mongoDbFactory" dbname="database" /> <mongo:mapping-converter id="converter" /> <bean class="org.springframework.data.mongodb.gridfs.GridFsTemplate"> <constructor-arg ref="mongoDbFactory" /> <constructor-arg ref="converter" /> </bean> </beans>
The template can now be injected and used to perform storage and retrieval operations.
Example 4.31. 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 4.32. 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 | |
---|---|
Currently MongoDB does not support defining sort criterias when
retrieving files from GridFS. Thus any sort criterias defined on the
|
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 4.33. 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.
This chapter will point out the specialties for repository support for MongoDB. This builds on the core repository support explained in Chapter 3, Working with Spring Data Repositories. So make sure you've got a sound understanding of the basic concepts explained there.
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 5.1. 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 5.2. 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 5.3. 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 5.4. 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
Person
s at a page size of 10 would simply look
something like this:
Example 5.5. 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.
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 5.6. 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 that for version 1.0 we currently don't support referring to
parameters that are mapped as |
Table 5.1. Supported keywords for query methods
Keyword | Sample | Logical result |
---|---|---|
GreaterThan | findByAgeGreaterThan(int
age) | {"age" : {"$gt" : age}} |
GreaterThanEqual | findByAgeGreaterThanEqual(int
age) | {"age" : {"$gte" : age}} |
LessThan | findByAgeLessThan(int
age) | {"age" : {"$lt" : age}} |
LessThanEqual | findByAgeLessThanEqual(int
age) | {"age" : {"$lte" : age}} |
Between | findByAgeBetween(int from, int
to) | {"age" : {"$gt" : from, "$lt" : to}} |
In | findByAgeIn(Collection ages)
| {"age" : {"$in" : [ages...]}} |
NotIn | findByAgeNotIn(Collection ages)
| {"age" : {"$nin" : [ages...]}} |
IsNotNull ,
NotNull | findByFirstnameNotNull() | {"age" : {"$ne" : null}} |
IsNull ,
Null | findByFirstnameNull() | {"age" : null} |
Like | findByFirstnameLike(String
name) | {"age" : age} ( age as
regex) |
Regex | findByFirstnameRegex(String
firstname) | {"firstname" : {"$regex" : firstname
}} |
(No keyword) | findByFirstname(String
name) | {"age" : name} |
Not | findByFirstnameNot(String
name) | {"age" : {"$ne" : name}} |
Near | findByLocationNear(Point
point) | {"location" : {"$near" : [x,y]}} |
Within | findByLocationWithin(Circle
circle) | {"location" : {"$within" : {"$center" : [ [x, y],
distance]}}} |
Within | findByLocationWithin(Box
box) | {"location" : {"$within" : {"$box" : [ [x1, y1],
x2, y2]}}}True |
IsTrue ,
True | findByActiveIsTrue() | {"active" : true} |
IsFalse ,
False | findByActiveIsFalse() | {"active" : false} |
Exists | findByLocationExists(boolean
exists) | {"location" : {"$exists" : exists }} |
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 5.7. 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 $code.
Example 5.8. Using Distance
with Metrics
Point point = new Point(43.7, 48.8); Distance distance = new Distance(200, Metrics.KILOMETERS); … = repository.findByLocationNear(point, distance); // {'location' : {'$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.
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); }
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.
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 addition to other repository interfaces. This is shown below
public interface PersonRepository extends MongoRepository<Person, String>, QueryDslPredicateExecutor<Person> { // additional finder methods go here }
We think you will find this an extremely powerful tool for writing MongoDB queries.
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(); } }
Rich mapping support is provided by the
MongoMappingConverter
.
MongoMappingConverter
has a rich metadata model that
provides a full feature set of functionality to map domain objects to
MongoDB documents.The mapping metadata model is populated using annotations
on your domain objects. However, the infrastructure is not limited to using
annotations as the only source of metadata information. The
MongoMappingConverter
also allows you to map objects
to documents without providing any additional metadata, by following a set
of conventions.
In this section we will describe the features of the MongoMappingConverter. How to use conventions for mapping objects to documents and how to override those conventions with annotation based mapping metadata.
Note | |
---|---|
|
MongoMappingConverter
has a few conventions
for mapping objects to documents when no additional mapping metadata is
provided. The conventions are:
The short Java class name is mapped to the collection name in
the following manner. The class
'com.bigbank.SavingsAccount
' maps to
'savingsAccount
' collection name.
All nested objects are stored as nested objects in the document and *not* as DBRefs
The converter will use any Spring Converters registered with it to override the default mapping of object properties to document field/values.
The fields of an object are used to convert to and from fields in the document. Public JavaBean properties are not used.
You can have a single non-zero argument constructor whose constructor argument names match top level field names of document, that constructor will be used. Otherwise the zero arg constructor will be used. if there is more than one non-zero argument constructor an exception will be thrown.
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 detected to the MongoDBdriver. If the specified 'id' value cannot be converted to an ObjectId, then the value will be stored as is in the document's _id field.
If a field named ' id' id field is not declared as a String, BigInteger, or ObjectID in the Java class then you should assign it a value in your application so it can be stored 'as-is' in the document's _id field.
If no field named 'id' is present in the Java class then an implicit '_id' file will be generated by the driver but not mapped to a property or field of the Java class.
When querying and updating MongoTemplate
will use the converter to handle conversions of the
Query
and Update
objects
that correspond to the above rules for saving documents so field names
and types used in your queries will be able to match what is in your
domain classes.
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 6.1. @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 @Bean @Override public CustomConversions customConversions() throws Exception { List<Converter<?, ?>> converterList = new ArrayList<Converter<?, ?>>(); converterList.add(new org.springframework.data.mongodb.test.PersonReadConverter()); converterList.add(new org.springframework.data.mongodb.test.PersonWriteConverter()); return new CustomConversions(converterList); } @Bean public LoggingEventListener<MongoMappingEvent> mappingEventsListener() { return new LoggingEventListener<MongoMappingEvent>(); } }
AbstractMongoConfiguration
requires you to
implement methods that define a com.mongodb.Mongo
as well as provide a database name.
AbstractMongoConfiguration
also has a method you
can override named 'getMappingBasePackage
' which
tells the converter where to scan for classes annotated with the
@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
MongoMappingEvent
s that are posted onto Spring's
ApplicationContextEvent
infrastructure.
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 6.2. 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.
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 6.3. 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 | |
---|---|
The |
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
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 { private @Id String id; private int quantity; private double unitPrice; OrderItem(String id, @Value("#root.qty ?: 0") int quantity, double unitPrice) { this.id = id; this.quantity = quantity; this.unitPrice = unitPrice; } // getters/setters ommitted } DBObject input = new BasicDBObject("id", "4711"); input.put("unitPrice", 2.5); input.put("qty",5); OrderItem item = converter.read(OrderItem.class, input);
Note | |
---|---|
The SpEL expression in the |
Additional examples for using the
@PersistenceConstructor
annotation can be found
in the MappingMongoConverterUnitTests
test suite.
Compound indexes are also supported. They are defined at the class level, rather than on indidvidual properties.
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 6.4. 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; }
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 6.5.
@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 | |
---|---|
The mapping framework does not handle cascading saves. If you
change an |
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.
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 | |
---|---|
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 method customConversions
in
AbstractMongoConfiguration
can be used to
configure Converters. 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.
@ReadingConverter public class PersonReadConverter implements Converter<DBObject, Person> { public Person convert(DBObject source) { Person p = new Person((ObjectId) source.get("_id"), (String) source.get("name")); p.setAge((Integer) source.get("age")); return p; } }
Here is an example that converts from a Person to a DBObject.
@WritingConverter public class PersonWriteConverter implements Converter<Person, DBObject> { public DBObject convert(Person source) { DBObject dbo = new BasicDBObject(); dbo.put("_id", source.getId()); dbo.put("name", source.getFirstName()); dbo.put("age", source.getAge()); return dbo; } }
Sometimes you need to store data in multiple data stores and these data stores can be of different types. One might be relational while the other a document store. For this use case we have created a separate module in the MongoDB support that handles what we call cross-store support. The current implementation is based on JPA as the driver for the relational database and we allow select fields in the Entities to be stored in a Mongo database. In addition to allowing you to store your data in two stores we also coordinate persistence operations for the non-transactional MongoDB store with the transaction life-cycle for the relational database.
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 7.1. 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 7.2. 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 7.3. 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>
We are assuming that you have a working JPA application so we will
only cover the additional steps needed to persist part of your Entity in
your Mongo database. First you need to identify the field you want
persisted. It should be a domain class and follow the general rules for the
Mongo mapping support covered in previous chapters. The field you want
persisted in MongoDB should be annotated using the
@RelatedDocument
annotation. That is really all you
need to do!. The cross-store aspects take care of the rest. This includes
marking the field with @Transient so it won't be persisted using JPA,
keeping track of any changes made to the field value and writing them to
the database on successful transaction completion, loading the document
from MongoDB the first time the value is used in your application. Here is
an example of a simple Entity that has a field annotated with
@RelatedEntity.
Example 7.4. 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 7.5. 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 7.6. 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 7.7. 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" }
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.
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.
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.
Spring's Mongo namespace enables you to easily enable JMX functionality
Example 9.1. 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"> <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
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
Name | Description |
---|---|
base-package | Defines the package to be used to be scanned for repository
interfaces extending *Repository
(actual interface is determined by specific Spring Data module) in
auto detection mode. All packages below the configured package
will be scanned, too. Wildcards are allowed. |
repository-impl-postfix | Defines the postfix to autodetect custom repository
implementations. Classes whose names end with the configured
postfix will be considered as candidates. Defaults to
Impl . |
query-lookup-strategy | Determines the strategy to be used to create finder
queries. See the section called “Query lookup strategies” for
details. Defaults to create-if-not-found . |
named-queries-location | Defines the location to look for a Properties file containing externally defined queries. |
consider-nested-repositories | Controls whether nested repository interface definitions
should be considered. Defaults to
false . |
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 keyword | Keyword expressions |
---|---|
AND | And |
OR | Or |
AFTER | After ,
IsAfter |
BEFORE | Before ,
IsBefore |
CONTAINING | Containing ,
IsContaining ,
Contains |
BETWEEN | Between ,
IsBetween |
ENDING_WITH | EndingWith ,
IsEndingWith ,
EndsWith |
EXISTS | Exists |
FALSE | False ,
IsFalse |
GREATER_THAN | GreaterThan ,
IsGreaterThan |
GREATER_THAN_EQUALS | GreaterThanEqual ,
IsGreaterThanEqual |
IN | In , IsIn |
IS | Is , Equals , (or no
keyword) |
IS_NOT_NULL | NotNull ,
IsNotNull |
IS_NULL | Null , IsNull |
LESS_THAN | LessThan ,
IsLessThan |
LESS_THAN_EQUAL | LessThanEqual ,
IsLessThanEqual |
LIKE | Like , IsLike |
NEAR | Near , IsNear |
NOT | Not , IsNot |
NOT_IN | NotIn ,
IsNotIn |
NOT_LIKE | NotLike ,
IsNotLike |
REGEX | Regex , MatchesRegex ,
Matches |
STARTING_WITH | StartingWith ,
IsStartingWith ,
StartsWith |
TRUE | True , IsTrue |
WITHIN | Within ,
IsWithin |