1.0.1.RELEASE
Copyright © 2008-2014 The original authors.
Table of Contents
The Spring Data Cassandra project applies core Spring concepts to the development of solutions using the Cassandra Columnar 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 - Cassandra Support. It explains Cassandra module concepts and semantics and the syntax for various stores namespaces.
This section provides some basic introduction to Spring and the Cassandra database. The rest of the document refers only to Spring Data Cassandra features and assumes the user is familiar with Cassandra 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 Cassandra 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 Cassandra,
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 Cassandra Columnar NoSQL Datastore supported by DATACASS. 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 Cassandra is cassandra.apache.org/. Here is a list of other useful resources.
The Planet Cassandra site has many valuable resources for Cassandra best practices.
The DataStax site offers commercial support and many resources.
Spring Data Cassandra 1.x binaries requires JDK level 6.0 and above, and Spring Framework 3.2.x and above.
Currently we support Cassandra 2.X using the DataStax Java Driver (2.0.X)
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 Cassandra 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 Cassandra) 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 Prowave Consulting.
For information on the Spring Data Cassandra source code repository, nightly builds and snapshot artifacts please see the Spring Data Cassandra 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 Cassandra 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.
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));
In addition to finder methods, query derivation for both count and delete queries, is available.
Example 3.3. Derived Count Query
public interface UserRepository extends CrudRepository<User, Long> { Long countByLastname(String lastname); }
Example 3.4. Derived Delete Query
public interface UserRepository extends CrudRepository<User, Long> { Long deleteByLastname(String lastname); List<User> removeByLastname(String lastname); }
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 3.5. 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 3.6. 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 3.7. 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 3.8. 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 3.9. 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 3.10. 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 3.11. Interface for custom repository functionality
interface UserRepositoryCustom { public void someCustomMethod(User user); }
Example 3.12. 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 3.13. 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 3.14. 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 3.15. 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 3.16. 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 3.17. 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 3.18. 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 3.19. 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 3.20. 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 3.21. 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 3.22. 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 3.23. 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 3.24. 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 3.25. 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 3.26. 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 3.27. 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 Cassandra.
Chapter 4, Cassandra support introduces the Cassandra module feature set.
Chapter 5, Cassandra repositories introduces the repository support for Cassandra.
The Cassandra 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 Cassandra driver instance and replica sets
CassandraTemplate helper class that increases productivity performing common Cassandra operations. Includes integrated object mapping between CQL Tables 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.
For most tasks you will find yourself using
CassandraTemplate
or the Repository support that both leverage
the rich mapping functionality. CassandraTemplate is the place to look for
accessing functionality such as incrementing counters or ad-hoc CRUD
operations. CassandraTemplate also provides callback methods so that it is
easy for you to get a hold of the low level API artifacts such as
com.datastax.driver.core.Session
to communicate directly with
Cassandra. The goal with naming conventions on various API artifacts is to
copy those in the base DataStax Java driver so you can easily map your
existing knowledge onto the Spring APIs.
Spring Data Cassandra uses the DataStax Java Driver version 2.X, which supports DataStax Enterprise 4/Cassandra 2.0, and Java SE 6 or higher. The latest commercial release (2.X as of this writing) is recommended. An easy way to bootstrap setting up a working environment is to create a Spring based project in STS.
First you need to set up a running Cassandra server.
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.cassandra.example.
Then add the following to pom.xml dependencies section.
<dependencies> <!-- other dependency elements omitted --> <dependency> <groupId>org.springframework.data</groupId> <artifactId>spring-data-cassandra</artifactId> <version>1.0.0.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.
Create a simple Employee class to persist.
package org.spring.cassandra.example; import org.springframework.data.cassandra.mapping.PrimaryKey; import org.springframework.data.cassandra.mapping.Table; @Table public class Person { @PrimaryKey private String id; private String name; private int age; public Person(String id, String name, int age) { this.id = id; 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.cassandra.example; import java.net.InetAddress; import java.net.UnknownHostException; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import org.springframework.data.cassandra.core.CassandraOperations; import org.springframework.data.cassandra.core.CassandraTemplate; import com.datastax.driver.core.Cluster; import com.datastax.driver.core.Session; import com.datastax.driver.core.querybuilder.QueryBuilder; import com.datastax.driver.core.querybuilder.Select; public class CassandraApp { private static final Logger LOG = LoggerFactory.getLogger(CassandraApp.class); private static Cluster cluster; private static Session session; public static void main(String[] args) { try { cluster = Cluster.builder().addContactPoints(InetAddress.getLocalHost()).build(); session = cluster.connect("mykeyspace"); CassandraOperations cassandraOps = new CassandraTemplate(session); cassandraOps.insert(new Person("1234567890", "David", 40)); Select s = QueryBuilder.select().from("person"); s.where(QueryBuilder.eq("id", "1234567890")); LOG.info(cassandraOps.queryForObject(s, Person.class).getId()); cassandraOps.truncate("person"); } catch (UnknownHostException e) { e.printStackTrace(); } } }
Even in this simple example, there are a few things to observe.
You can create an instance of CassandraTemplate with a Cassandra Session, derived from the Cluster.
You must annotate your POJO as a Cassandra @Table, and also annotate the @PrimaryKey. Optionally you can override these mapping names to match your Cassandra database table and column names.
You can use CQL String, or the DataStax QueryBuilder to construct you queries.
After the initial release of Spring Data Cassandra 1.0.0, we will start working on a showcase repository with full examples.
Create a properties file with the information you need to connect to Cassandra. The contact points are keyspace are the minimal required fields, but port is added here for clarity.
We will call this cassandra.properties
cassandra.contactpoints=10.1.55.80,10.1.55.81 cassandra.port=9042 cassandra.keyspace=showcase
We will use spring to load these properties into the Spring Context in the next two examples.
The XML Configuration elements for a basic Cassandra configuration are shown below. These elements all use default bean names to keep the configuration code clean and readable.
While this example show how easy it is to configure Spring to connect to Cassandra, there are many other options. Basically, any option available with the DataStax Java Driver is also available in the Spring Data Cassandra configuration. This is including, but not limited to Authentication, Load Balancing Policies, Retry Policies and Pooling Options. All of the Spring Data Cassandra method names and XML elements are named exactly (or as close as possible) like the configuration options on the driver so mapping any existing driver configuration should be straight forward.
<?xml version='1.0'?> <beans xmlns="http://www.springframework.org/schema/beans" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:cassandra="http://www.springframework.org/schema/data/cassandra" xmlns:context="http://www.springframework.org/schema/context" xsi:schemaLocation="http://www.springframework.org/schema/cql http://www.springframework.org/schema/cql/spring-cql-1.0.xsd http://www.springframework.org/schema/data/cassandra http://www.springframework.org/schema/data/cassandra/spring-cassandra-1.0.xsd http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans.xsd http://www.springframework.org/schema/context http://www.springframework.org/schema/context/spring-context-3.2.xsd"> <!-- Loads the properties into the Spring Context and uses them to fill in placeholders in the bean definitions --> <context:property-placeholder location="classpath:cassandra.properties" /> <!-- REQUIRED: The Cassandra Cluster --> <cassandra:cluster contact-points="${cassandra.contactpoints}" port="${cassandra.port}" /> <!-- REQUIRED: The Cassandra Session, built from the Cluster, and attaching to a keyspace --> <cassandra:session keyspace-name="${cassandra.keyspace}" /> <!-- REQUIRED: The Default Cassandra Mapping Context used by CassandraConverter --> <cassandra:mapping /> <!-- REQUIRED: The Default Cassandra Converter used by CassandraTemplate --> <cassandra:converter /> <!-- REQUIRED: The Cassandra Template is the building block of all Spring Data Cassandra --> <cassandra:template id="cassandraTemplate" /> <!-- OPTIONAL: If you are using Spring Data Cassandra Repositories, add your base packages to scan here --> <cassandra:repositories base-package="org.spring.cassandra.example.repo" /> </beans>
The following class show a basic and minimal Cassandra configuration using the AnnotationConfigApplicationContext (aka JavaConfig).
package org.spring.cassandra.example.config; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.context.annotation.Bean; import org.springframework.context.annotation.Configuration; import org.springframework.context.annotation.PropertySource; import org.springframework.core.env.Environment; import org.springframework.data.cassandra.config.CassandraClusterFactoryBean; import org.springframework.data.cassandra.config.CassandraSessionFactoryBean; import org.springframework.data.cassandra.config.SchemaAction; import org.springframework.data.cassandra.convert.CassandraConverter; import org.springframework.data.cassandra.convert.MappingCassandraConverter; import org.springframework.data.cassandra.core.CassandraOperations; import org.springframework.data.cassandra.core.CassandraTemplate; import org.springframework.data.cassandra.mapping.BasicCassandraMappingContext; import org.springframework.data.cassandra.mapping.CassandraMappingContext; import org.springframework.data.cassandra.repository.config.EnableCassandraRepositories; @Configuration @PropertySource(value = { "classpath:cassandra.properties" }) @EnableCassandraRepositories(basePackages = { "org.spring.cassandra.example.repo" }) public class CassandraConfig { private static final Logger LOG = LoggerFactory.getLogger(CassandraConfig.class); @Autowired private Environment env; @Bean public CassandraClusterFactoryBean cluster() { CassandraClusterFactoryBean cluster = new CassandraClusterFactoryBean(); cluster.setContactPoints(env.getProperty("cassandra.contactpoints")); cluster.setPort(Integer.parseInt(env.getProperty("cassandra.port"))); return cluster; } @Bean public CassandraMappingContext mappingContext() { return new BasicCassandraMappingContext(); } @Bean public CassandraConverter converter() { return new MappingCassandraConverter(mappingContext()); } @Bean public CassandraSessionFactoryBean session() throws Exception { CassandraSessionFactoryBean session = new CassandraSessionFactoryBean(); session.setCluster(cluster().getObject()); session.setKeyspaceName(env.getProperty("cassandra.keyspace")); session.setConverter(converter()); session.setSchemaAction(SchemaAction.NONE); return session; } @Bean public CassandraOperations cassandraTemplate() throws Exception { return new CassandraTemplate(session().getObject()); } }
CassandraTemplate
should always be configured
as a Spring Bean, although we show an example above where you can
instantiate it directly. But for the purposes of this being a Spring
module, lets assume we are using the Spring Container.
CassandraTemplate
is an implementation of
CassandraOperations
. You should always assign your
CassandraTemplate
to its interface definition,
CassandraOperations
.
There are 2 easy ways to get a
CassandraTemplate
, depending on how you load you
Spring Application Context.
@Autowired private CassandraOperations cassandraOperations;
Like all Spring Autowiring, this assumes there is only one bean of
type CassandraOperations
in the
ApplicationContext
. If you have multiple
CassandraTemplate
beans (which will be the case if
you are working with multiple keyspaces in the same project), use the
@Qualifier
annotation to designate which bean you
want to Autowire.
@Autowired @Qualifier("myTemplateBeanId") private CassandraOperations cassandraOperations;
You can also just lookup the CassandraTemplate
bean from the ApplicationContext
.
CassandraOperations cassandraOperations = applicationContext.getBean("cassandraTemplate", CassandraOperations.class);
CassandraTemplate
provides a simple way for
you to save, update, and delete your domain objects and map those objects
to documents stored in Cassandra.
Cassandra requires that you have at least 1 Partition Key field for a CQL Table. Alternately, you can have one or more Clustering Key fields. When your CQL Table has a composite Primary Key field you must create a @PrimaryKeyClass to define the structure of the composite PK. In this context, composite PK means one or more partition columns, or 1 partition column plus one or more clustering columns.
The simplest for of a Composite key is a key with one partition key and one clustering key. Here is an example of a CQL Table, and the corresponding POJOs that represent the table and it's composite key.
CQL Table defined in Cassandra
create table login_event( person_id text, event_time timestamp, event_code int, ip_address text, primary key (person_id, event_time)) with CLUSTERING ORDER BY (event_time DESC) ;
Class defining the Composite Primary Key.
NOTE: PrimaryKeyClass must implement
Serializable
and provide implementation of
hashCode()
and equals()
just
like the example.
package org.spring.cassandra.example; import java.io.Serializable; import java.util.Date; import org.springframework.cassandra.core.Ordering; import org.springframework.cassandra.core.PrimaryKeyType; import org.springframework.data.cassandra.mapping.PrimaryKeyClass; import org.springframework.data.cassandra.mapping.PrimaryKeyColumn; @PrimaryKeyClass public class LoginEventKey implements Serializable { @PrimaryKeyColumn(name = "person_id", ordinal = 0, type = PrimaryKeyType.PARTITIONED) private String personId; @PrimaryKeyColumn(name = "event_time", ordinal = 1, type = PrimaryKeyType.CLUSTERED, ordering = Ordering.DESCENDING) private Date eventTime; public String getPersonId() { return personId; } public void setPersonId(String personId) { this.personId = personId; } public Date getEventTime() { return eventTime; } public void setEventTime(Date eventTime) { this.eventTime = eventTime; } @Override public int hashCode() { final int prime = 31; int result = 1; result = prime * result + ((eventTime == null) ? 0 : eventTime.hashCode()); result = prime * result + ((personId == null) ? 0 : personId.hashCode()); return result; } @Override public boolean equals(Object obj) { if (this == obj) return true; if (obj == null) return false; if (getClass() != obj.getClass()) return false; LoginEventKey other = (LoginEventKey) obj; if (eventTime == null) { if (other.eventTime != null) return false; } else if (!eventTime.equals(other.eventTime)) return false; if (personId == null) { if (other.personId != null) return false; } else if (!personId.equals(other.personId)) return false; return true; } }
Class defining the CQL Table, having the Composite
Primary Key as an attribute and annotated as the
PrimaryKey
.
package org.spring.cassandra.example; import org.springframework.data.cassandra.mapping.Column; import org.springframework.data.cassandra.mapping.PrimaryKey; import org.springframework.data.cassandra.mapping.Table; @Table(value = "login_event") public class LoginEvent { @PrimaryKey private LoginEventKey pk; @Column(value = "event_code") private int eventCode; @Column(value = "ip_address") private String ipAddress; public LoginEventKey getPk() { return pk; } public void setPk(LoginEventKey pk) { this.pk = pk; } public int getEventCode() { return eventCode; } public void setEventCode(int eventCode) { this.eventCode = eventCode; } public String getIpAddress() { return ipAddress; } public void setIpAddress(String ipAddress) { this.ipAddress = ipAddress; } }
The annotations provided with Spring Data Cassandra can handle any key combination available in Cassandra. Here is one more example of a Composite Primary Key with 5 columns, 2 of which are a composite partition key, and the remaining 3 are ordered clustering keys. The getters/setters, hashCode and equals are omitted for brevity.
package org.spring.cassandra.example; import java.io.Serializable; import java.util.Date; import org.springframework.cassandra.core.Ordering; import org.springframework.cassandra.core.PrimaryKeyType; import org.springframework.data.cassandra.mapping.PrimaryKeyClass; import org.springframework.data.cassandra.mapping.PrimaryKeyColumn; @PrimaryKeyClass public class DetailedLoginEventKey implements Serializable { @PrimaryKeyColumn(name = "person_id", ordinal = 0, type = PrimaryKeyType.PARTITIONED) private String personId; @PrimaryKeyColumn(name = "wks_id", ordinal = 1, type = PrimaryKeyType.PARTITIONED) private String workstationId; @PrimaryKeyColumn(ordinal = 2, type = PrimaryKeyType.CLUSTERED, ordering = Ordering.ASCENDING) private Date application; @PrimaryKeyColumn(name = "event_code", ordinal = 3, type = PrimaryKeyType.CLUSTERED, ordering = Ordering.ASCENDING) private Date eventCode; @PrimaryKeyColumn(name = "event_time", ordinal = 4, type = PrimaryKeyType.CLUSTERED, ordering = Ordering.DESCENDING) private Date eventTime; ... }
Spring Data Cassandra relies on the DataStax Java Driver type mapping component. This approach ensures that as types are added or changed, the Spring Data Cassandra module will continue to function without requiring changes. For more information on the DataStax CQL3 to Java Type mappings, please see their Documentation here.
To insert one row at a time, there are many options. At this point you should already have a cassandraTemplate available to you so we will just how the relevant code for each section, omitting the template setup.
Insert a record with an annotated POJO.
cassandraOperations.insert(new Person("123123123", "Alison", 39));
Insert a row using the QueryBuilder.Insert object that is part of the DataStax Java Driver.
Insert insert = QueryBuilder.insertInto("person"); insert.setConsistencyLevel(ConsistencyLevel.ONE); insert.value("id", "123123123"); insert.value("name", "Alison"); insert.value("age", 39); cassandraOperations.execute(insert);
Then there is always the old fashioned way. You can write your own CQL statements.
String cql = "insert into person (id, name, age) values ('123123123', 'Alison', 39)"; cassandraOperations.execute(cql);
CQLOperations, which is extended by CassandraOperations is a
lower level Template that you can use for just about anything you need
to accomplish with Cassandra. CqlOperations includes several
overloaded methods named ingest()
.
Use these methods to pass a CQL String with Bind Markers, and your preferred flavor of data set (Object[][] and List<List<T>>).
The ingest method takes advantage of static PreparedStatements that are only prepared once for performance. Each record in your data list is bound to the same PreparedStatement, then executed asynchronously for high performance.
String cqlIngest = "insert into person (id, name, age) values (?, ?, ?)"; List<Object> person1 = new ArrayList<Object>(); person1.add("10000"); person1.add("David"); person1.add(40); List<Object> person2 = new ArrayList<Object>(); person2.add("10001"); person2.add("Roger"); person2.add(65); List<List<?>> people = new ArrayList<List<?>>(); people.add(person1); people.add(person2); cassandraOperations.ingest(cqlIngest, people);
Much like inserting, there are several flavors of update from which you can choose.
Update a record with an annotated POJO.
cassandraOperations.update(new Person("123123123", "Alison", 35));
Update a row using the QueryBuilder.Update object that is part of the DataStax Java Driver.
Update update = QueryBuilder.update("person"); update.setConsistencyLevel(ConsistencyLevel.ONE); update.with(QueryBuilder.set("age", 35)); update.where(QueryBuilder.eq("id", "123123123")); cassandraOperations.execute(update);
Then there is always the old fashioned way. You can write your own CQL statements.
String cql = "update person set age = 35 where id = '123123123'"; cassandraOperations.execute(cql);
Much like inserting, there are several flavors of delete from which you can choose.
Delete a record with an annotated POJO.
cassandraOperations.delete(new Person("123123123", null, 0));
Delete a row using the QueryBuilder.Delete object that is part of the DataStax Java Driver.
Delete delete = QueryBuilder.delete().from("person"); delete.where(QueryBuilder.eq("id", "123123123")); cassandraOperations.execute(delete);
Then there is always the old fashioned way. You can write your own CQL statements.
String cql = "delete from person where id = '123123123'"; cassandraOperations.execute(cql);
Much like inserting, there are several flavors of truncate from which you can choose.
Truncate a table using the truncate() method.
cassandraOperations.truncate("person");
Truncate a table using the QueryBuilder.Truncate object that is part of the DataStax Java Driver.
Truncate truncate = QueryBuilder.truncate("person"); cassandraOperations.execute(truncate);
Then there is always the old fashioned way. You can write your own CQL statements.
String cql = "truncate person"; cassandraOperations.execute(cql);
Tthere are several flavors of select and query from which you can choose. Please see the CassandraTemplate API documentation for all overloads available.
Query a table for multiple rows and map the results to a POJO.
String cqlAll = "select * from person"; List<Person> results = cassandraOperations.select(cqlAll, Person.class); for (Person p : results) { LOG.info(String.format("Found People with Name [%s] for id [%s]", p.getName(), p.getId())); }
Query a table for a single row and map the result to a POJO.
String cqlOne = "select * from person where id = '123123123'"; Person p = cassandraOperations.selectOne(cqlOne, Person.class); LOG.info(String.format("Found Person with Name [%s] for id [%s]", p.getName(), p.getId()));
Query a table using the QueryBuilder.Select object that is part of the DataStax Java Driver.
Select select = QueryBuilder.select().from("person"); select.where(QueryBuilder.eq("id", "123123123")); Person p = cassandraOperations.selectOne(select, Person.class); LOG.info(String.format("Found Person with Name [%s] for id [%s]", p.getName(), p.getId()));
Then there is always the old fashioned way. You can write your own CQL statements, and there are several callback handlers for mapping the results. The example uses the RowMapper interface.
String cqlAll = "select * from person"; List<Person> results = cassandraOperations.query(cqlAll, new RowMapper<Person>() { public Person mapRow(Row row, int rowNum) throws DriverException { Person p = new Person(row.getString("id"), row.getString("name"), row.getInt("age")); return p; } }); for (Person p : results) { LOG.info(String.format("Found People with Name [%s] for id [%s]", p.getName(), p.getId())); }
In order to have more fine grained control over the mapping process
you can register Spring converters with the
CassandraConverter
implementations such as the
MappingCassandraConverter
.
The MappingCassandraConverter
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 MappingCassandraConverter
,
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. |
The CassandraTemplate has many overloads for execute() and executeAsync(). Pass in the CQL command you wish to be executed, and handle the appropriate response.
This example uses the basic AsynchronousQueryListener that comes with Spring Data Cassandra. Please see the API documentation for all the options. There should be nothing you cannot perform in Cassandra with the execute() and executeAsync() methods.
cassandraOperations.executeAsynchronously("delete from person where id = '123123123'", new AsynchronousQueryListener() { public void onQueryComplete(ResultSetFuture rsf) { LOG.info("Async Query Completed"); } });
This example shows how to create and drop a table, using different API objects, all passed to the execute() methods.
cassandraOperations.execute("create table test_table (id uuid primary key, event text)"); DropTableSpecification dropper = DropTableSpecification.dropTable("test_table"); cassandraOperations.execute(dropper);
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 Cassandra extends this feature to
the Cassandra 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 Cassandra Exceptions. 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.
This chapter will point out the specialties for repository support for Cassandra. 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 Cassandra you can leverage our sophisticated repository support that eases implementing those quite significantly. To do so, simply create an interface for your repository:
TODO
The Spring Data Cassandra CDI extension will pick up the
CassandraTemplate
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
CassandraMappingConverter
.
CassandraMappingConverter
has a rich metadata model that
provides a full feature set of
functionality to map domain objects to
CQL Tables. 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
CassandraMappingConverter
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 CassandraMappingConverter. How to use conventions for mapping objects to documents and how to override those conventions with annotation based mapping metadata.
CassandraMappingConverter
has a few conventions
for mapping objects to CQL Tables when no
additional mapping metadata is
provided. The conventions are:
The short Java class name is mapped to the table name in
the
following manner. The class
'
com.bigbank.SavingsAccount
' maps to
'
savings_account
' table name.
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.
Unless explicitly configured, an instance of
CassandraMappingConverter
is created by default when
creating a
CassandraTemplate
. You can create your own
instance of the
MappingCassandraConverter
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
CassandraMappingConverter
and CassandraTemplate
either using Java or XML based metadata. Here
is an
example using Spring's
Java based configuration
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 |