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Table of Contents

Preface

The Spring Data for Apache Cassandra project applies core Spring concepts to the development of solutions using the Cassandra Columnar data store. A "template" is provided as a high-level abstraction for storing and querying documents. You will notice similarities to the JDBC support in the core Spring Framework.

This document is the reference guide for Spring Data support for Cassandra. It explains Cassandra module concepts, semantics and the syntax for various stores namespaces.

This section provides a basic introduction to Spring, Spring Data and the Cassandra database. The rest of the document refers only to Spring Data for Apache Cassandra features and assumes the user is familiar with Cassandra as well as core Spring concepts.

1. Knowing Spring

Spring Data uses the Spring Framework’s core functionality, such as the IoC container, validation, type conversion and data binding, expression language, AOP, JMX integration, DAO support, and specifically the 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 no matter what 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 for Apache 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.

2. Knowing NoSQL and Cassandra

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

The starting ground for learning about Cassandra is cassandra.apache.org. Also, here is a list of other useful resources:

The DataStax site offers commercial support and many resources, including, but not limited to, documentation, DataStax Academy, a Tech Blog and so on.
The DataStax Academy introduction to cassandra
The Cassandra Quick Start Guide.

3. Requirements

Spring Data for Apache Cassandra 1.x binaries require JDK level 6.0 and above, and Spring Framework 4.3.24.RELEASE and above.

In terms of Cassandra at least 2.0.

4. Additional Help Resources

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

4.1. Support

There are a few support options available:

4.1.1. Community Forum

Spring Data on Stackoverflow is a tag for all Spring Data (not just Cassandra) users to share information and help each other. Note that registration is needed only for posting.

Developers post questions and answers on . The two key tags to search for related answers to this project are:

4.1.2. Professional Support

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

4.2. Following Development

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

4.3. Project Metadata

Version Control - https://github.com/spring-projects/spring-data-cassandra
Bugtracker - https://jira.spring.io/browse/DATACASS
Release repository - https://repo.spring.io/libs-release
Milestone repository - https://repo.spring.io/libs-milestone
Snapshot repository - https://repo.spring.io/libs-snapshot

5. New & Noteworthy

5.1. What’s new in Spring Data for Apache Cassandra 1.5

Assert compatibility with Cassandra 3.0 and Cassandra Java Driver 3.0.
Configurable ProtocolVersion and QueryOptions on Cluster level.
Support for Optional as query method result and argument.
Declarative query methods using query derivation
Support for User-Defined types and mapped User-Defined types using @UserDefinedType.
The following annotations have been enabled to build own, composed annotations: @Table, @UserDefinedType, @PrimaryKey, @PrimaryKeyClass, @PrimaryKeyColumn, @Column, @Query, @CassandraType.

6. Dependencies

Due to the different inception dates of individual Spring Data modules, most of them carry different major and minor version numbers. The easiest way to find compatible ones is to rely on the Spring Data Release Train BOM that we ship with the compatible versions defined. In a Maven project, you would declare this dependency in the <dependencyManagement /> section of your POM, as follows:

Example 1. Using the Spring Data release train BOM

<dependencyManagement>
  <dependencies>
    <dependency>
      <groupId>org.springframework.data</groupId>
      <artifactId>spring-data-releasetrain</artifactId>
      <version>Ingalls-SR22</version>
      <scope>import</scope>
      <type>pom</type>
    </dependency>
  </dependencies>
</dependencyManagement>

The current release train version is Ingalls-SR22. The train names ascend alphabetically and the currently available trains are listed here. The version name follows the following pattern: ${name}-${release}, where release can be one of the following:

BUILD-SNAPSHOT: Current snapshots
M1, M2, and so on: Milestones
RC1, RC2, and so on: Release candidates
RELEASE: GA release
SR1, SR2, and so on: Service releases

A working example of using the BOMs can be found in our Spring Data examples repository. With that in place, you can declare the Spring Data modules you would like to use without a version in the <dependencies /> block, as follows:

Example 2. Declaring a dependency to a Spring Data module

<dependencies>
  <dependency>
    <groupId>org.springframework.data</groupId>
    <artifactId>spring-data-jpa</artifactId>
  </dependency>
<dependencies>

6.1. Dependency Management with Spring Boot

Spring Boot selects a recent version of Spring Data modules for you. If you still want to upgrade to a newer version, configure the property spring-data-releasetrain.version to the train name and iteration you would like to use.

6.2. Spring Framework

The current version of Spring Data modules require Spring Framework in version 4.3.24.RELEASE or better. The modules might also work with an older bugfix version of that minor version. However, using the most recent version within that generation is highly recommended. :spring-framework-docs: http://docs.spring.io/spring/docs/4.3.24.RELEASE/spring-framework-reference/html

7. Working with Spring Data Repositories

The goal of the Spring Data repository abstraction is to significantly reduce the amount of boilerplate code required to implement data access layers for various persistence stores.

Spring Data repository documentation and your module

This chapter explains the core concepts and interfaces of Spring Data repositories. The information in this chapter is pulled from the Spring Data Commons module. It uses the configuration and code samples for the Java Persistence API (JPA) module. You should adapt the XML namespace declaration and the types to be extended to the equivalents of the particular module that you use. “Namespace reference” covers XML configuration, which is supported across all Spring Data modules supporting the repository API. “Repository query keywords” covers the query method keywords supported by the repository abstraction in general. For detailed information on the specific features of your module, see the chapter on that module of this document.

7.1. Core concepts

The central interface in the Spring Data repository abstraction is Repository. It takes the domain class to manage as well as the ID type of the domain class as type arguments. This interface acts primarily as a marker interface to capture the types to work with and to help you to discover interfaces that extend this one. The CrudRepository provides sophisticated CRUD functionality for the entity class that is being managed.

Example 3. CrudRepository interface

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

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

    T findOne(ID primaryKey);       (2)

    Iterable<T> findAll();          (3)

    Long count();                   (4)

    void delete(T entity);          (5)

    boolean exists(ID primaryKey);  (6)

    // … more functionality omitted.
}

1	Saves the given entity.
2	Returns the entity identified by the given ID.
3	Returns all entities.
4	Returns the number of entities.
5	Deletes the given entity.
6	Indicates whether an entity with the given ID exists.

We also provide persistence technology-specific abstractions, such as JpaRepository or MongoRepository. Those interfaces extend CrudRepository and expose the capabilities of the underlying persistence technology in addition to the rather generic persistence technology-agnostic interfaces such as CrudRepository.

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

Example 4. PagingAndSortingRepository interface

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

  Iterable<T> findAll(Sort sort);

  Page<T> findAll(Pageable pageable);
}

To access the second page of User by a page size of 20, you could do something like the following:

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

In addition to query methods, query derivation for both count and delete queries is available. The following list shows the interface definition for a derived count query:

Example 5. Derived Count Query

public interface UserRepository extends CrudRepository<User, Long> {

  Long countByLastname(String lastname);
}

The following list shows the interface definition for a derived delete query:

Example 6. Derived Delete Query

public interface UserRepository extends CrudRepository<User, Long> {

  Long deleteByLastname(String lastname);

  List<User> removeByLastname(String lastname);

}

7.2. Query methods

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

Declare an interface extending Repository or one of its subinterfaces and type it to the domain class and ID type that it should handle, as shown in the following example:
```
interface PersonRepository extends Repository<Person, Long> { … }
```

Declare query methods on the interface.

interface PersonRepository extends Repository<Person, Long> {
  List<Person> findByLastname(String lastname);
}

Set up Spring to create proxy instances for those interfaces, either with JavaConfig or with XML configuration.
1. To use Java configuration, create a class similar to the following:
  import org.springframework.data.jpa.repository.config.EnableJpaRepositories; @EnableJpaRepositories class Config {}
2. To use XML configuration, define a bean similar to the following:
  <?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 use the repository abstraction for any other store, you need to change this to the appropriate namespace declaration of your store module. In other words, you should exchange jpa in favor of, for example, mongodb.

+ Also, note that the JavaConfig variant does not configure a package explicitly, because the package of the annotated class is used by default. To customize the package to scan, use one of the basePackage… attributes of the data-store-specific repository’s @Enable${store}Repositories-annotation.

Inject the repository instance and use it, as shown in the following example:

public class SomeClient {

  @Autowired
  private PersonRepository repository;

  public void doSomething() {
    List<Person> persons = repository.findByLastname("Matthews");
  }
}

The sections that follow explain each step in detail:

Defining Repository Interfaces
Defining Query Methods
Creating Repository Instances
Custom implementations for Spring Data repositories

7.3. Defining Repository Interfaces

First, define a domain class-specific repository interface. The interface must extend Repository and be typed to the domain class and an ID type. If you want to expose CRUD methods for that domain type, extend CrudRepository instead of Repository.

7.3.1. Fine-tuning Repository Definition

Typically, your repository interface extends Repository, CrudRepository, or PagingAndSortingRepository. Alternatively, if you do not want to extend Spring Data interfaces, you can also annotate your repository interface with @RepositoryDefinition. Extending CrudRepository exposes a complete set of methods to manipulate your entities. If you prefer to be selective about the methods being exposed, copy the methods you want to expose from CrudRepository into your domain repository.

Doing so lets you define your own abstractions on top of the provided Spring Data Repositories functionality.

The following example shows how to selectively expose CRUD methods (findById and save, in this case):

Example 7. Selectively exposing CRUD methods

@NoRepositoryBean
interface MyBaseRepository<T, ID extends Serializable> extends Repository<T, ID> {

  T findOne(ID id);

  T save(T entity);
}

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

In the prior example, you defined a common base interface for all your domain repositories and exposed findOne(…) as well as save(…).These methods are routed into the base repository implementation of the store of your choice provided by Spring Data (for example, if you use JPA, the implementation is SimpleJpaRepository), because they match the method signatures in CrudRepository. So the UserRepository can now save users, find individual users by ID, and trigger a query to find Users by email address.

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

7.3.2. Using Repositories with Multiple Spring Data Modules

Using a unique Spring Data module in your application makes things simple, because all repository interfaces in the defined scope are bound to the Spring Data module. Sometimes, applications require using more than one Spring Data module. In such cases, a repository definition must distinguish between persistence technologies. When it detects multiple repository factories on the class path, Spring Data enters strict repository configuration mode. Strict configuration uses details on the repository or the domain class to decide about Spring Data module binding for a repository definition:

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

The following example shows a repository that uses module-specific interfaces (JPA in this case):

Example 8. Repository definitions using module-specific interfaces

interface MyRepository extends JpaRepository<User, Long> { }

@NoRepositoryBean
interface MyBaseRepository<T, ID extends Serializable> extends JpaRepository<T, ID> {
  …
}

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

MyRepository and UserRepository extend JpaRepository in their type hierarchy. They are valid candidates for the Spring Data JPA module.

The following example shows a repository that uses generic interfaces:

Example 9. Repository definitions using generic interfaces

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

@NoRepositoryBean
interface MyBaseRepository<T, ID extends Serializable> extends CrudRepository<T, ID> {
  …
}

interface AmbiguousUserRepository extends MyBaseRepository<User, Long> {
  …
}

AmbiguousRepository and AmbiguousUserRepository extend only Repository and CrudRepository in their type hierarchy. While this is perfectly fine when using a unique Spring Data module, multiple modules cannot distinguish to which particular Spring Data these repositories should be bound.

The following example shows a repository that uses domain classes with annotations:

Example 10. Repository definitions using domain classes with annotations

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

@Entity
public class Person {
  …
}

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

@Document
public class User {
  …
}

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

The following bad example shows a repository that uses domain classes with mixed annotations:

Example 11. Repository definitions using domain classes with mixed annotations

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

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

@Entity
@Document
public class Person {
  …
}

This example shows a domain class using both JPA and Spring Data MongoDB annotations. It defines two repositories, JpaPersonRepository and MongoDBPersonRepository. One is intended for JPA and the other for MongoDB usage. Spring Data is no longer able to tell the repositories apart, which leads to undefined behavior.

Repository type details and distinguishing domain class annotations are used for strict repository configuration to identify repository candidates for a particular Spring Data module. Using multiple persistence technology-specific annotations on the same domain type is possible and enables reuse of domain types across multiple persistence technologies. However, Spring Data can then no longer determine a unique module with which to bind the repository.

The last way to distinguish repositories is by scoping repository base packages. Base packages define the starting points for scanning for repository interface definitions, which implies having repository definitions located in the appropriate packages. By default, annotation-driven configuration uses the package of the configuration class. The base package in XML-based configuration is mandatory.

The following example shows annotation-driven configuration of base packages:

Example 12. Annotation-driven configuration of base packages

@EnableJpaRepositories(basePackages = "com.acme.repositories.jpa")
@EnableMongoRepositories(basePackages = "com.acme.repositories.mongo")
interface Configuration { }

7.4. Defining Query Methods

The repository proxy has two ways to derive a store-specific query from the method name:

By deriving the query from the method name directly.
By using a manually defined query.

Available options depend on the actual store. However, there must be a strategy that decides what actual query is created. The next section describes the available options.

7.4.1. Query Lookup Strategies

The following strategies are available for the repository infrastructure to resolve the query. With XML configuration, you can configure the strategy at the namespace through the query-lookup-strategy attribute. For Java configuration, you can use the queryLookupStrategy attribute of the Enable${store}Repositories annotation. Some strategies may not be supported for particular datastores.

CREATE 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. You can read more about query construction in “Query Creation”.
USE_DECLARED_QUERY tries to find a declared query and throws an exception if cannot find one. The query can be defined by an annotation somewhere or declared by other means. Consult the documentation of the specific store to find available options for that store. If the repository infrastructure does not find a declared query for the method at bootstrap time, it fails.
CREATE_IF_NOT_FOUND (default) combines CREATE and USE_DECLARED_QUERY. It looks up a declared query first, and, if no declared query is found, it creates a custom method name-based query. This is the default lookup strategy and, thus, is used if you do not configure anything explicitly. It allows quick query definition by method names but also custom-tuning of these queries by introducing declared queries as needed.

7.4.2. Query Creation

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

Example 13. Query creation from method names

public interface PersonRepository extends Repository<User, Long> {

  List<Person> findByEmailAddressAndLastname(EmailAddress emailAddress, String lastname);

  // Enables the distinct flag for the query
  List<Person> findDistinctPeopleByLastnameOrFirstname(String lastname, String firstname);
  List<Person> findPeopleDistinctByLastnameOrFirstname(String lastname, String firstname);

  // Enabling ignoring case for an individual property
  List<Person> findByLastnameIgnoreCase(String lastname);
  // Enabling ignoring case for all suitable properties
  List<Person> findByLastnameAndFirstnameAllIgnoreCase(String lastname, String firstname);

  // Enabling static ORDER BY for a query
  List<Person> findByLastnameOrderByFirstnameAsc(String lastname);
  List<Person> findByLastnameOrderByFirstnameDesc(String lastname);
}

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

The expressions are usually property traversals combined with operators that can be concatenated. You can combine property expressions with AND and OR. You also get support for operators such as Between, LessThan, GreaterThan, and 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 supports ignoring case (usually String instances — for example, findByLastnameAndFirstnameAllIgnoreCase(…)). Whether ignoring cases is supported may vary by store, so consult the relevant sections in the reference documentation for the store-specific query method.
You can apply static ordering by appending an OrderBy clause to the query method that references a property and by providing a sorting direction (Asc or Desc). To create a query method that supports dynamic sorting, see “Special parameter handling”.

7.4.3. Property Expressions

Property expressions can refer only to a direct property of the managed entity, as shown in the preceding example. At query creation time, you already make sure that the parsed property is a property of the managed domain class. However, you can also define constraints by traversing nested properties. Consider the following method signature:

List<Person> findByAddressZipCode(ZipCode zipCode);

Assume a Person has an Address with a ZipCode. In that case, the method creates the property traversal x.address.zipCode. The resolution algorithm starts by interpreting the entire part (AddressZipCode) as the property and checks the domain class for a property with that name (uncapitalized). If the algorithm succeeds, it uses that property. If not, the algorithm splits up the source at the camel case parts from the right side into a head and a tail and tries to find the corresponding property — in our example, AddressZip and Code. If the algorithm finds a property with that head, it takes the tail and continues building the tree down from there, splitting the tail up in the way just described. If the first split does not match, the algorithm moves the split point to the left (Address, ZipCode) and continues.

Although this should work for most cases, it is possible for the algorithm to select the wrong property. Suppose the Person class has an addressZip property as well. The algorithm would match in the first split round already, choose the wrong property, and fail (as the type of addressZip probably has no code property).

To resolve this ambiguity you can use _ inside your method name to manually define traversal points. So our method name would be as follows:

List<Person> findByAddress_ZipCode(ZipCode zipCode);

Because we treat the underscore character as a reserved character, we strongly advise following standard Java naming conventions (that is, not using underscores in property names but using camel case instead).

7.4.4. Special parameter handling

To handle parameters in your query, define method parameters as already seen in the preceding examples. Besides that, the infrastructure recognizes certain specific types like Pageable and Sort, to apply pagination and sorting to your queries dynamically. The following example demonstrates these features:

Example 14. Using Pageable, Slice, and Sort in query methods

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

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

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

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

The first method lets you pass an org.springframework.data.domain.Pageable instance to the query method to dynamically add paging to your statically defined query. A Page knows about the total number of elements and pages available. It does so by the infrastructure triggering a count query to calculate the overall number. As this might be expensive (depending on the store used), you can instead return a Slice. A Slice only knows about whether a next Slice is available, which might be sufficient when walking through a larger result set.

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

To find out how many pages you get for an entire query, you have to trigger an additional count query. By default, this query is derived from the query you actually trigger.

7.4.5. Limiting Query Results

The results of query methods can be limited by using the first or top keywords, which can be used interchangeably. An optional numeric value can be appended to top or first to specify the maximum result size to be returned. If the number is left out, a result size of 1 is assumed. The following example shows how to limit the query size:

Example 15. Limiting the result size of a query with Top and First

User findFirstByOrderByLastnameAsc();

User findTopByOrderByAgeDesc();

Page<User> queryFirst10ByLastname(String lastname, Pageable pageable);

Slice<User> findTop3ByLastname(String lastname, Pageable pageable);

List<User> findFirst10ByLastname(String lastname, Sort sort);

List<User> findTop10ByLastname(String lastname, Pageable pageable);

The limiting expressions also support the Distinct keyword. Also, for the queries limiting the result set to one instance, wrapping the result into with the Optional keyword is supported.

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

Limiting the results in combination with dynamic sorting by using a Sort parameter lets you express query methods for the 'K' smallest as well as for the 'K' biggest elements.

7.4.6. Streaming query results

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

Example 16. Stream the result of a query with Java 8 Stream<T>

@Query("select u from User u")
Stream<User> findAllByCustomQueryAndStream();

Stream<User> readAllByFirstnameNotNull();

@Query("select u from User u")
Stream<User> streamAllPaged(Pageable pageable);

A Stream potentially wraps underlying data store-specific resources and must, therefore, be closed after usage. You can either manually close the Stream by using the close() method or by using a Java 7 try-with-resources block, as shown in the following example:

Example 17. Working with a Stream<T> result in a try-with-resources block

try (Stream<User> stream = repository.findAllByCustomQueryAndStream()) {
  stream.forEach(…);
}

Not all Spring Data modules currently support Stream<T> as a return type.

7.4.7. Async query results

Repository queries can be run asynchronously by using Spring’s asynchronous method execution capability. This means the method returns immediately upon invocation while the actual query execution occurs in a task that has been submitted to a Spring TaskExecutor. Asynchronous query execution is different from reactive query execution and should not be mixed. Refer to store-specific documentation for more details on reactive support. The following example shows a number of asynchronous queries:

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

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

@Async
ListenableFuture<User> findOneByLastname(String lastname);    (3)

1	Use `java.util.concurrent.Future` as the return type.
2	Use a Java 8 `java.util.concurrent.CompletableFuture` as the return type.
3	Use a `org.springframework.util.concurrent.ListenableFuture` as the return type.

7.5. Creating Repository Instances

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

7.5.1. XML configuration

Each Spring Data module includes a repositories element that lets you define a base package that Spring scans for you, as shown in the following example:

Example 18. Enabling Spring Data repositories via XML

<?xml version="1.0" encoding="UTF-8"?>
<beans:beans xmlns:beans="http://www.springframework.org/schema/beans"
  xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xmlns="http://www.springframework.org/schema/data/jpa"
  xsi:schemaLocation="http://www.springframework.org/schema/beans
    http://www.springframework.org/schema/beans/spring-beans.xsd
    http://www.springframework.org/schema/data/jpa
    http://www.springframework.org/schema/data/jpa/spring-jpa.xsd">

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

</beans:beans>

In the preceding example, Spring is instructed to scan com.acme.repositories and all its sub-packages for interfaces extending Repository or one of its sub-interfaces. For each interface found, the infrastructure registers the persistence technology-specific FactoryBean to create the appropriate proxies that handle invocations of the query methods. Each bean is registered under a bean name that is derived from the interface name, so an interface of UserRepository would be registered under userRepository. The base-package attribute allows wildcards so that you can define a pattern of scanned packages.

Using filters

By default, the infrastructure picks up every interface extending the persistence technology-specific Repository sub-interface located under the configured base package and creates a bean instance for it. However, you might want more fine-grained control over which interfaces have bean instances created for them. To do so, use <include-filter /> and <exclude-filter /> elements inside the <repositories /> element. The semantics are exactly equivalent to the elements in Spring’s context namespace. For details, see the Spring reference documentation for these elements.

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

Example 19. Using exclude-filter element

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

The preceding example excludes all interfaces ending in SomeRepository from being instantiated.

7.5.2. JavaConfig

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

A sample configuration to enable Spring Data repositories resembles the following:

Example 20. Sample annotation based repository configuration

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

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

The preceding example uses the JPA-specific annotation, which you would change according to the store module you actually use. The same applies to the definition of the EntityManagerFactory bean. See the sections covering the store-specific configuration.

7.5.3. Standalone usage

You can also use the repository infrastructure outside of a Spring container — for example, in CDI environments. You still need some Spring libraries in your classpath, but, generally, you can set up repositories programmatically as well. The Spring Data modules that provide repository support ship a persistence technology-specific RepositoryFactory that you can use as follows:

Example 21. Standalone usage of repository factory

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

7.6. Custom implementations for Spring Data repositories

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

7.6.1. Adding custom behavior to single repositories

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

Example 22. Interface for custom repository functionality

interface UserRepositoryCustom {
  public void someCustomMethod(User user);
}

Then you can let your repository interface additionally extend from the fragment interface, as shown in the following example:

Example 23. Implementation of custom repository functionality

class UserRepositoryImpl implements UserRepositoryCustom {

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

The most important bit for the class to be found is the Impl postfix of the name on it compared to the core repository interface (see below).

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

You can let your repository interface extend the fragment interface, as shown in the following example:

Example 24. Changes to the your basic repository interface

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

  // Declare query methods here
}

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

Configuration

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

Example 25. Configuration example

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

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

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

Manual Wiring

If your custom implementation uses annotation-based configuration and autowiring only, the preceding approach shown works well, because it is treated as any other Spring bean. If your custom implementation bean needs special wiring, you can declare the bean and name it according to the conventions described in the preceding section. The infrastructure then refers to the manually defined bean definition by name instead of creating one itself. The following example shows how to manually wire a custom implementation:

Example 26. Manual wiring of custom implementations

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

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

7.6.2. Adding custom behavior to all repositories

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

Example 27. An interface declaring custom shared behavior

@NoRepositoryBean
public interface MyRepository<T, ID extends Serializable>
  extends PagingAndSortingRepository<T, ID> {

  void sharedCustomMethod(ID id);
}

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

Example 28. Custom repository base class

public class MyRepositoryImpl<T, ID extends Serializable>
  extends SimpleJpaRepository<T, ID> implements MyRepository<T, ID> {

  private final EntityManager entityManager;

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

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

  public void sharedCustomMethod(ID id) {
    // implementation goes here
  }
}

The class needs to have a constructor of the super class which the store-specific repository factory implementation uses. If the repository base class has multiple constructors, override the one taking an EntityInformation plus a store specific infrastructure object (such as an EntityManager or a template class).

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

The final step is to make the Spring Data infrastructure aware of the customized repository base class. In Java configuration, you can do so by using the repositoryBaseClass attribute of the @Enable${store}Repositories annotation, as shown in the following example:

Example 29. Configuring a custom repository base class using JavaConfig

@Configuration
@EnableJpaRepositories(repositoryBaseClass = MyRepositoryImpl.class)
class ApplicationConfiguration { … }

A corresponding attribute is available in the XML namespace, as shown in the following example:

Example 30. Configuring a custom repository base class using XML

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

7.7. Publishing Events from Aggregate Roots

Entities managed by repositories are aggregate roots. In a Domain-Driven Design application, these aggregate roots usually publish domain events. Spring Data provides an annotation called @DomainEvents that you can use on a method of your aggregate root to make that publication as easy as possible, as shown in the following example:

Example 31. Exposing domain events from an aggregate root

class AnAggregateRoot {

    @DomainEvents (1)
    Collection<Object> domainEvents() {
        // … return events you want to get published here
    }

    @AfterDomainEventsPublication (2)
    void callbackMethod() {
       // … potentially clean up domain events list
    }
}

1	The method using `@DomainEvents` can return either a single event instance or a collection of events. It must not take any arguments.
2	After all events have been published, we have a method annotated with `@AfterDomainEventsPublication`. It can be used to potentially clean the list of events to be published (among other uses).

The methods are called every time one of a Spring Data repository’s save(…) methods is called.

7.8. Spring Data Extensions

This section documents a set of Spring Data extensions that enable Spring Data usage in a variety of contexts. Currently, most of the integration is targeted towards Spring MVC.

7.8.1. Querydsl Extension

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

Several Spring Data modules offer integration with Querydsl through QueryDslPredicateExecutor, as shown in the following example:

Example 32. QueryDslPredicateExecutor interface

public interface QueryDslPredicateExecutor<T> {

    T findOne(Predicate predicate);             (1)

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

    long count(Predicate predicate);            (3)

    boolean exists(Predicate predicate);        (4)

    // … more functionality omitted.
}

1	Finds and returns a single entity matching the `Predicate`.
2	Finds and returns all entities matching the `Predicate`.
3	Returns the number of entities matching the `Predicate`.
4	Returns whether an entity that matches the `Predicate` exists.

To make use of Querydsl support, extend QueryDslPredicateExecutor on your repository interface, as shown in the following example

Example 33. Querydsl integration on repositories

interface UserRepository extends CrudRepository<User, Long>, QueryDslPredicateExecutor<User> {
}

The preceding example lets you write typesafe queries using Querydsl Predicate instances, as shown in the following example:

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

userRepository.findAll(predicate);

7.8.2. Web support

This section contains the documentation for the Spring Data web support as it is implemented in the current (and later) versions of Spring Data Commons. As the newly introduced support changes many things, we kept the documentation of the former behavior in Legacy web support.

Spring Data modules that support the repository programming model ship with a variety of web support. The web related components require Spring MVC JARs to be on the classpath. Some of them even provide integration with Spring HATEOAS. In general, the integration support is enabled by using the @EnableSpringDataWebSupport annotation in your JavaConfig configuration class, as shown in the following example:

Example 34. 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 use XML configuration, register either SpringDataWebConfiguration or HateoasAwareSpringDataWebConfiguration as Spring beans, as shown in the following example (for SpringDataWebConfiguration):

Example 35. Enabling Spring Data web support in XML

<bean class="org.springframework.data.web.config.SpringDataWebConfiguration" />

<!-- If you use Spring HATEOAS, register this one *instead* of the former -->
<bean class="org.springframework.data.web.config.HateoasAwareSpringDataWebConfiguration" />

Basic Web Support

The configuration shown in the previous section registers a few basic components:

A DomainClassConverter to let Spring MVC resolve instances of repository-managed domain classes from request parameters or path variables.
HandlerMethodArgumentResolver implementations to let Spring MVC resolve Pageable and Sort instances from request parameters.

`DomainClassConverter`

The DomainClassConverter lets you use domain types in your Spring MVC controller method signatures directly, so that you need not manually lookup the instances through the repository, as shown in the following example:

Example 36. A Spring MVC controller using domain types in method signatures

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

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

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

As you can see, the method receives a User instance directly, and no further lookup is necessary. The instance can be resolved by letting Spring MVC convert the path variable into the id type of the domain class first and eventually access the instance through calling findOne(…) on the repository instance registered for the domain type.

Currently, the repository has to implement CrudRepository to be eligible to be discovered for conversion.

HandlerMethodArgumentResolvers for Pageable and Sort

The configuration snippet shown in the previous section also registers a PageableHandlerMethodArgumentResolver as well as an instance of SortHandlerMethodArgumentResolver. The registration enables Pageable and Sort as valid controller method arguments, as shown in the following example:

Example 37. 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";
  }
}

The preceding method signature causes Spring MVC try to derive a Pageable instance from the request parameters by using the following default configuration:

Table 1. Request parameters evaluated for `Pageable` instances
`page`	Page you want to retrieve. 0-indexed and defaults to 0.
`size`	Size of the page you want to retrieve. Defaults to 20.
`sort`	Properties that should be sorted by in the format `property,property(,ASC\|DESC)`. Default sort direction is ascending. Use multiple `sort` parameters if you want to switch directions — for example, `?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.

If you need multiple Pageable or Sort instances to be resolved from the request (for multiple tables, for example), you can use Spring’s @Qualifier annotation to distinguish one from another. The request parameters then have to be prefixed with ${qualifier}_. The followig example shows the resulting method signature:

public String showUsers(Model model,
      @Qualifier("thing1") Pageable first,
      @Qualifier("thing2") Pageable second) { … }

you have to populate thing1_page and thing2_page and so on.

The default Pageable passed into the method is equivalent to a new PageRequest(0, 20) but can be customized by using the @PageableDefault annotation on the Pageable parameter.

Hypermedia Support for Pageables

Spring HATEOAS ships with a representation model class (PagedResources) that allows enriching the content of a Page instance with the necessary Page metadata as well as links to let the clients easily navigate the pages. The conversion of a Page to a PagedResources is done by an implementation of the Spring HATEOAS ResourceAssembler interface, called the PagedResourcesAssembler. The following example shows how to use a PagedResourcesAssembler as a controller method argument:

Example 38. Using a PagedResourcesAssembler as controller method argument

@Controller
class PersonController {

  @Autowired PersonRepository repository;

  @RequestMapping(value = "/persons", method = RequestMethod.GET)
  HttpEntity<PagedResources<Person>> persons(Pageable pageable,
    PagedResourcesAssembler assembler) {

    Page<Person> persons = repository.findAll(pageable);
    return new ResponseEntity<>(assembler.toResources(persons), HttpStatus.OK);
  }
}

Enabling the configuration as shown in the preceding example lets the PagedResourcesAssembler be used as a controller method argument. Calling toResources(…) on it has the following effects:

The content of the Page becomes the content of the PagedResources instance.
The PagedResources object gets a PageMetadata instance attached, and it is populated with information from the Page and the underlying PageRequest.
The PagedResources may get prev and next links attached, depending on the page’s state. The links point to the URI to which the method maps. The pagination parameters added to the method match the setup of the PageableHandlerMethodArgumentResolver to make sure the links can be resolved later.

Assume we have 30 Person instances in the database. You can now trigger a request (GET http://localhost:8080/persons) and see output similar to the following:

{ "links" : [ { "rel" : "next",
                "href" : "http://localhost:8080/persons?page=1&size=20 }
  ],
  "content" : [
     … // 20 Person instances rendered here
  ],
  "pageMetadata" : {
    "size" : 20,
    "totalElements" : 30,
    "totalPages" : 2,
    "number" : 0
  }
}

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

Web Databinding Support

Spring Data projections (described in Projections) can be used to bind incoming request payloads by either using JSONPath expressions (requires Jayway JsonPath or XPath expressions (requires XmlBeam), as shown in the following example:

Example 39. HTTP payload binding using JSONPath or XPath expressions

@ProjectedPayload
public interface UserPayload {

  @XBRead("//firstname")
  @JsonPath("$..firstname")
  String getFirstname();

  @XBRead("/lastname")
  @JsonPath({ "$.lastname", "$.user.lastname" })
  String getLastname();
}

The type shown in the preceding example can be used as a Spring MVC handler method argument or by using ParameterizedTypeReference on one of RestTemplate's methods. The preceding method declarations would try to find firstname anywhere in the given document. The lastname XML lookup is performed on the top-level of the incoming document. The JSON variant of that tries a top-level lastname first but also tries lastname nested in a user sub-document if the former does not return a value. That way, changes in the structure of the source document can be mitigated easily without having clients calling the exposed methods (usually a drawback of class-based payload binding).

Nested projections are supported as described in Projections. If the method returns a complex, non-interface type, a Jackson ObjectMapper is used to map the final value.

For Spring MVC, the necessary converters are registered automatically as soon as @EnableSpringDataWebSupport is active and the required dependencies are available on the classpath. For usage with RestTemplate, register a ProjectingJackson2HttpMessageConverter (JSON) or XmlBeamHttpMessageConverter manually.

For more information, see the web projection example in the canonical Spring Data Examples repository.

Querydsl Web Support

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

Consider the following query string:

?firstname=Dave&lastname=Matthews

Given the User object from previous examples, a query string can be resolved to the following value by using the QuerydslPredicateArgumentResolver.

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

The feature is automatically enabled, along with @EnableSpringDataWebSupport, when Querydsl is found on the classpath.

Adding a @QuerydslPredicate to the method signature provides a ready-to-use Predicate, which can be run by using the QuerydslPredicateExecutor.

Type information is typically resolved from the method’s return type. Since that information does not necessarily match the domain type, it might be a good idea to use the root attribute of QuerydslPredicate.

The following exampe shows how to use @QuerydslPredicate in a method signature:

@Controller
class UserController {

  @Autowired UserRepository repository;

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

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

    return "index";
  }
}

1	Resolve query string arguments to matching `Predicate` for `User`.

The default binding is as follows:

Object on simple properties as eq.
Object on collection like properties as contains.
Collection on simple properties as in.

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

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

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

    bindings.bind(user.username).first((path, value) -> path.contains(value))    (3)
    bindings.bind(String.class)
      .first((StringPath path, String value) -> path.containsIgnoreCase(value)); (4)
    bindings.excluding(user.password);                                           (5)
  }
}

1	`QueryDslPredicateExecutor` provides access to specific finder methods for `Predicate`.
2	`QuerydslBinderCustomizer` defined on the repository interface is automatically picked up and shortcuts `@QuerydslPredicate(bindings=…)`.
3	Define the binding for the `username` property to be a simple `contains` binding.
4	Define the default binding for `String` properties to be a case-insensitive `contains` match.
5	Exclude the `password` property from `Predicate` resolution.

7.8.3. Repository Populators

If you work with the Spring JDBC module, you are probably familiar with the support to populate a DataSource with SQL scripts. A similar abstraction is available on the repositories level, although it does not use SQL as the data definition language because it must be store-independent. Thus, the populators support XML (through Spring’s OXM abstraction) and JSON (through Jackson) to define data with which to populate the repositories.

Assume you have a file data.json with the following content:

Example 40. Data defined in JSON

[ { "_class" : "com.acme.Person",
 "firstname" : "Dave",
  "lastname" : "Matthews" },
  { "_class" : "com.acme.Person",
 "firstname" : "Carter",
  "lastname" : "Beauford" } ]

You can populate your repositories by using the populator elements of the repository namespace provided in Spring Data Commons. To populate the preceding data to your PersonRepository, declare a populator similar to the following:

Example 41. Declaring a Jackson repository populator

<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
  xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xmlns:repository="http://www.springframework.org/schema/data/repository"
  xsi:schemaLocation="http://www.springframework.org/schema/beans
    http://www.springframework.org/schema/beans/spring-beans.xsd
    http://www.springframework.org/schema/data/repository
    http://www.springframework.org/schema/data/repository/spring-repository.xsd">

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

</beans>

The preceding declaration causes the data.json file to be read and deserialized by a Jackson ObjectMapper.

The type to which the JSON object is unmarshalled is determined by inspecting the _class attribute of the JSON document. The infrastructure eventually selects the appropriate repository to handle the object that was deserialized.

To instead use XML to define the data the repositories should be populated with, you can use the unmarshaller-populator element. You configure it to use one of the XML marshaller options available in Spring OXM. See the Spring reference documentation for details. The following example shows how to unmarshal a repository populator with JAXB:

Example 42. Declaring an unmarshalling repository populator (using JAXB)

<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
  xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xmlns:repository="http://www.springframework.org/schema/data/repository"
  xmlns:oxm="http://www.springframework.org/schema/oxm"
  xsi:schemaLocation="http://www.springframework.org/schema/beans
    http://www.springframework.org/schema/beans/spring-beans.xsd
    http://www.springframework.org/schema/data/repository
    http://www.springframework.org/schema/data/repository/spring-repository.xsd
    http://www.springframework.org/schema/oxm
    http://www.springframework.org/schema/oxm/spring-oxm.xsd">

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

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

</beans>

7.8.4. Legacy web support

Domain class web binding for Spring MVC

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

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

  private final UserRepository userRepository;

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

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

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

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

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

PropertyEditors

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

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

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

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

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

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

Reference Documentation

Document Structure

This part of the reference documentation explains the core functionality offered by Spring Data for Apache Cassandra.

Cassandra support introduces the Cassandra module feature set.

Cassandra repositories introduces the repository support for Cassandra.

8. Cassandra support

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

Spring configuration support using Java-based @Configuration classes or the XML namespace to create a Cassandra instance with replica sets using the driver.
CassandraTemplate helper class that increases productivity by handling common Cassandra operations properly. 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 data oriented tasks you will use the CassandraTemplate or the Repository support, which leverage the rich mapping functionality. CassandraTemplate is commonly used to increment counters or perform ad-hoc CRUD operations. CassandraTemplate also provides callback methods making it easy to get a hold of low-level API objects such as com.datastax.driver.core.Session allowing you to communicate directly with Cassandra. Spring Data for Apache Cassandra uses consistent naming conventions on objects in various APIs to those found in the DataStax Java Driver so that they are familiar and so you can map your existing knowledge onto the Spring APIs.

8.1. Spring CQL and Spring Data for Apache Cassandra modules

Spring Data for Apache Cassandra comes with two modules: Spring CQL and Spring Data Cassandra.

The value-add provided by the Spring Data Cassandra abstraction is perhaps best shown by the sequence of actions outlined in the table below. The table shows what actions Spring will take care of and which actions are the responsibility of you, the application developer.

Table 2. Spring CQL - who does what?
Action	Spring	You
Define connection parameters.		X
Open the connection.	X
Specify the CQL statement.		X
Declare parameters and provide parameter values		X
Prepare and execute the statement.	X
Set up the loop to iterate through the results (if any).	X
Do the work for each iteration.		X
Process any exception.	X
Close the Session.	X

Spring CQL takes care of all the low-level details that can make Cassandra and CQL such a tedious API to develop with. Spring Data Cassandra adds schema generation, object mapping and Repository support.

8.1.1. Choosing an approach for Cassandra database access

You can choose among several approaches to form the basis for your Cassandra database access. Spring’s support for Apache Cassandra comes in different flavors. Once you start using one of these approaches, you can still mix and match to include a feature from a different approach.

CqlTemplate is the classic Spring CQL approach and the most popular. This is the "lowest level" approach and all others use a CqlTemplate under the covers.
CassandraTemplate wraps a CqlTemplate to provide query result to object mapping and the use of SELECT, INSERT, UPDATE and DELETE methods instead of writing CQL statements. This approach provides better documentation and ease of use.
Repository Abstraction allows you to create Repository declarations in your data access layer. The goal of Spring Data’s Repository abstraction is to significantly reduce the amount of boilerplate code required to implement data access layers for various persistence stores.

8.2. Getting Started

Spring Apache Cassandra support requires Apache Cassandra 2.1 or higher, Datastax Java Driver 3.0 or higher and Java SE 6 or higher. An easy way to bootstrap setting up a working environment is to create a Spring-based project in STS.

First you need to set up a running Apache Cassandra server. Refer to the Apache Cassandra Quick Start guide for an explanation on how to startup Apache Cassandra. Once installed starting Cassandra is typically a matter of executing the following command: CASSANDRA_HOME/bin/cassandra -f

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 dependencies omitted -->

  <dependency>
    <groupId>org.springframework.data</groupId>
    <artifactId>spring-data-cassandra</artifactId>
    <version>1.5.22.RELEASE</version>
  </dependency>

</dependencies>

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

<spring.framework.version>4.3.24.RELEASE</spring.framework.version>

If using a milestone release instead of a GA release, 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 can also browse the Spring repositories here.

Now we will create a simple Java application that stores and reads a domain object to/from Cassandra.

First, create a simple domain object class to persist.

package org.spring.data.cassandra.example;

import org.springframework.data.cassandra.mapping.PrimaryKey;
import org.springframework.data.cassandra.mapping.Table;

@Table
public class Person {

  @PrimaryKey
  private final String id;

  private final String name;
  private final 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 String.format("{ @type = %1$s, id = %2$s, name = %3$s, age = %4$d }",
      getClass().getName(), getId(), getName(), getAge());
  }
}

Next, create the main application to run.

package org.spring.data.cassandra.example;

import java.io.Closeable;
import java.util.UUID;

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 CassandraApplication {

  private static final Logger LOGGER = LoggerFactory.getLogger(CassandraApplication.class);

  protected static Person newPerson(String name, int age) {
    return newPerson(UUID.randomUUID().toString(), name, age);
  }

  protected static Person newPerson(String id, String name, int age) {
    return new Person(id, name, age);
  }

  public static void main(String[] args) {

    Cluster cluster = Cluster.builder().addContactPoints("localhost").build();
    Session session = cluster.connect("mykeyspace");

    CassandraOperations template = new CassandraTemplate(session);

    Person jonDoe = template.insert(newPerson("Jon Doe", 40));

    Select selectStatement = QueryBuilder.select().from("person");
    selectStatement.where(QueryBuilder.eq("id", jonDoe.getId()));

    LOGGER.info(template.queryForObject(selectStatement, Person.class).getId());

    template.truncate("person");
    session.close();
    cluster.close();
  }
}

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 a 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 either use a CQL String or the DataStax QueryBuilder API to construct you queries.

8.3. Examples Repository

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

8.4. Connecting to Cassandra with Spring

One of the first tasks when using Apache Cassandra and Spring is to create a com.datastax.driver.core.Session object using the Spring IoC container. There are two main ways to do this, either using Java-based bean metadata or XML-based bean metadata. These are discussed in the following sections.

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

8.4.1. Registering a Session instance using Java based metadata

An example of using Java-based bean metadata to register an instance of a com.datastax.driver.core.Session is shown below.

Example 43. Registering a com.datastax.driver.core.Session object using Java based bean metadata

@Configuration
public class AppConfig {

  /*
   * Use the standard Cassandra driver API to create a com.datastax.driver.core.Session instance.
   */
  public @Bean Session session() {
    Cluster cluster = Cluster.builder().addContactPoints("localhost").build();
    return cluster.connect("mykeyspace");
  }
}

This approach allows you to use the standard com.datastax.driver.core.Session API that you may already be used to using.

An alternative is to register an instance of com.datastax.driver.core.Session instance with the container using Spring’s CassandraCqlSessionFactoryBean and CassandraCqlClusterFactoryBean. As compared to instantiating a com.datastax.driver.core.Session instance directly, the FactoryBean approach has the added advantage of also providing the container with an ExceptionTranslator implementation that translates Cassandra exceptions to exceptions in Spring’s portable DataAccessException hierarchy for data access classes annotated. 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 44. Registering a com.datastax.driver.core.Session object using Spring’s CassandraCqlSessionFactoryBean and enabling Spring’s exception translation support

@Configuration
public class AppConfig {

  /*
   * Factory bean that creates the com.datastax.driver.core.Session instance
   */
  public @Bean CassandraCqlClusterFactoryBean cluster() {

    CassandraCqlClusterFactoryBean cluster = new CassandraCqlClusterFactoryBean();
    cluster.setContactPoints("localhost");

    return cluster;
  }

  /*
   * Factory bean that creates the com.datastax.driver.core.Session instance
   */
   public @Bean CassandraCqlSessionFactoryBean session() {

    CassandraCqlSessionFactoryBean session = new CassandraCqlSessionFactoryBean();
    session.setCluster(cluster().getObject());
    session.setKeyspaceName("mykeyspace");

    return session;
  }
}

Using CassandraTemplate with object mapping and Repository support requires a CassandraTemplate, CassandraMappingContext, CassandraConverter and enabling Repository support.

Example 45. Registering components to configure object mapping and repository support

@Configuration
@EnableCassandraRepositories(basePackages = { "org.spring.cassandra.example.repo" })
public class CassandraConfig {

  @Bean
  public CassandraClusterFactoryBean cluster() {

    CassandraClusterFactoryBean cluster = new CassandraClusterFactoryBean();
    cluster.setContactPoints("localhost");

    return cluster;
  }

  @Bean
  public CassandraMappingContext mappingContext() {

    BasicCassandraMappingContext mappingContext =  new BasicCassandraMappingContext();
    mappingContext.setUserTypeResolver(new SimpleUserTypeResolver(cluster().getObject(), "mykeyspace"));

    return mappingContext;
  }

  @Bean
  public CassandraConverter converter() {
    return new MappingCassandraConverter(mappingContext());
  }

  @Bean
  public CassandraSessionFactoryBean session() throws Exception {

    CassandraSessionFactoryBean session = new CassandraSessionFactoryBean();
    session.setCluster(cluster().getObject());
    session.setKeyspaceName("mykeyspace");
    session.setConverter(converter());
    session.setSchemaAction(SchemaAction.NONE);

    return session;
  }

  @Bean
  public CassandraOperations cassandraTemplate() throws Exception {
    return new CassandraTemplate(session().getObject());
  }
}

Creating configuration classes registering Spring Data for Apache Cassandra components can be an exhausting challenge so Spring Data for Apache Cassandra comes with a prebuilt configuration support class. Classes extending from AbstractCassandraConfiguration will register beans for Spring Data for Apache Cassandra use. AbstractCassandraConfiguration lets you provide various configuration options such as initial entities, default query options, pooling options, socket options and much more. AbstractCassandraConfiguration will support you also with schema generation based on initial entities, if any are provided. Extending from AbstractCassandraConfiguration requires you to at least provide the Keyspace name by implementing the getKeyspaceName method.

Example 46. Registering Spring Data for Apache Cassandra beans using AbstractCassandraConfiguration

@Configuration
public class AppConfig extends AbstractCassandraConfiguration {

  /*
   * Provide a contact point to the configuration.
   */
  public String getContactPoints() {
    return "localhost";
  }

  /*
   * Provide a keyspace name to the configuration.
   */
  public String getKeyspaceName() {
    return "mykeyspace";
  }
}

8.4.2. XML Configuration

Externalize Connection Properties

Create a properties file containing the information needed to connect to Cassandra. contactpoints and keyspace are required fields; port has been added for clarity.

We will call this properties file, 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.

Registering a Session instance using XML based metadata

While you can use Spring’s traditional <beans/> XML namespace to register an instance of com.datastax.driver.core.Session 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 Session instance. The cql and cassandra namespaces allow you to create a Session instance.

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

Example 47. XML schema to configure Cassandra using the cql namespace

<?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:cql="http://www.springframework.org/schema/data/cql"
  xsi:schemaLocation="
    http://www.springframework.org/schema/cql
    http://www.springframework.org/schema/cql/spring-cql.xsd
    http://www.springframework.org/schema/beans
    http://www.springframework.org/schema/beans/spring-beans.xsd">

  <!-- Default bean name is 'cassandraCluster' -->
  <cql:cluster contact-points="localhost" port="9042">
    <cql:keyspace action="CREATE_DROP" name="mykeyspace" />
  </cql:cluster>

  <!-- Default bean name is 'cassandraSession' -->
  <cql:session keyspace-name="mykeyspace" />

</beans>

Example 48. XML schema to configure Cassandra using the cassandra namespace

<?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:cassandra="http://www.springframework.org/schema/data/cassandra"
  xsi:schemaLocation="
    http://www.springframework.org/schema/data/cassandra
    http://www.springframework.org/schema/data/cassandra/spring-cassandra.xsd
    http://www.springframework.org/schema/beans
    http://www.springframework.org/schema/beans/spring-beans.xsd">

  <!-- Default bean name is 'cassandraCluster' -->
  <cassandra:cluster contact-points="localhost" port="9042">
    <cassandra:keyspace action="CREATE_DROP" name="mykeyspace" />
  </cassandra:cluster>

  <!-- Default bean name is 'cassandraSession' -->
  <cassandra:session keyspace-name="${cassandra.keyspace}" schema-action="NONE" />

</beans>

You may have noticed the slight difference between namespaces: cql and cassandra. Using the cql namespace is limited to low-level CQL support while cassandra extends the cql namespace with object mapping and schema generation support.

The XML configuration elements for more advanced Cassandra configuration are shown below. These elements all use default bean names to keep the configuration code clean and readable.

While this example shows 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 for Apache Cassandra configuration. This is including, but not limited to Authentication, Load Balancing Policies, Retry Policies and Pooling Options. All of the Spring Data for Apache 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.

Example 49. Configuring Spring Data Components via XML

<!-- 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>
  <cassandra:user-type-resolver keyspace-name="${cassandra.keyspace}" />
</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 for Apache Cassandra Repositories, add
your base packages to scan here -->
<cassandra:repositories base-package="org.spring.cassandra.example.repo" />

8.5. Schema Management

Apache Cassandra is a data store that requires a schema definition prior to any data interaction. Spring Data for Apache Cassandra can support you with this task.

8.5.1. Keyspaces and Lifecycle scripts

The very first thing to start with is a Cassandra Keyspace. A Keyspace is a logical grouping of tables that share the same replication factor and replication strategy. Keyspace management is located in the Cluster configuration, which has the notion of KeyspaceSpecification and startup/shutdown CQL script execution.

Declaring a Keyspace with a specification allows creating/dropping of the Keyspace. It will derive CQL from the specification so you’re not required to write CQL yourself.

Example 50. Specifying a Cassandra Keyspace via XML

<cql:cluster>

    <cql:keyspace action="CREATE_DROP" durable-writes="true" name="my_keyspace">

    <cql:replication class="NETWORK_TOPOLOGY_STRATEGY">
      <cql:data-center name="foo" replication-factor="1" />
      <cql:data-center name="bar" replication-factor="2" />
    </cql:replication>
  </cql:keyspace>

</cql:cluster>

Example 51. Specifying a Cassandra Keyspace via JavaConfig

@Configuration
public abstract class AbstractCassandraConfiguration extends AbstractClusterConfiguration
		implements BeanClassLoaderAware {

  @Override
  protected List<CreateKeyspaceSpecification> getKeyspaceCreations() {

    CreateKeyspaceSpecification specification = CreateKeyspaceSpecification.createKeyspace("my_keyspace")
      .with(KeyspaceOption.DURABLE_WRITES, true)
      .withNetworkReplication(DataCenterReplication.dcr("foo", 1), DataCenterReplication.dcr("bar", 2));

    return Arrays.asList(specification);
  }

  @Override
  protected List<DropKeyspaceSpecification> getKeyspaceDrops() {
    return Arrays.asList(DropKeyspaceSpecification.dropKeyspace("my_keyspace"));
  }

  // ...
}

Startup/shutdown CQL execution follows a slightly different approach that is bound to the Cluster lifecycle. You can provide arbitrary CQL that is executed on Cluster initialization and shutdown in the SYSTEM keyspace.

Example 52. Specifying Startup/Shutdown scripts via XML

<cql:cluster>
  <cql:startup-cql><![CDATA[
CREATE KEYSPACE IF NOT EXISTS my_other_keyspace WITH durable_writes = true AND replication = { 'replication_factor' : 1, 'class' : 'SimpleStrategy' };
    ]]></cql:startup-cql>
  <cql:shutdown-cql><![CDATA[
DROP KEYSPACE my_other_keyspace;
    ]]></cql:shutdown-cql>
</cql:cluster>

Example 53. Specifying a Startup/Shutdown scripts via JavaConfig

@Configuration
public class CassandraConfiguration extends AbstractCassandraConfiguration {

  @Override
  protected List<String> getStartupScripts() {

    String script = "CREATE KEYSPACE IF NOT EXISTS my_other_keyspace "
      + "WITH durable_writes = true "
      + "AND replication = { 'replication_factor' : 1, 'class' : 'SimpleStrategy' };";

    return Arrays.asList(script);
  }

  @Override
  protected List<String> getShutdownScripts() {
    return Arrays.asList("DROP KEYSPACE my_other_keyspace;");
  }

  // ...
}

KeyspaceSpecifications and lifecycle CQL scripts are available with the cql and cassandra namespaces.

Keyspace creation allows rapid bootstrapping without the need of external Keyspace management. This can be useful for certain scenarios but should be used with care. Dropping a Keyspace on application shutdown will remove the Keyspace and all data stored inside the tables.

8.5.2. Tables and User-defined types

Spring Data for Apache Cassandra’s approaches data access with mapped entity classes that fit your data model. These entity classes can be used to create Cassandra table specifications and user type definitions.

Schema creation is tied to Session initialization with SchemaAction. Following actions are supported:

SchemaAction.NONE: No tables/types will be created or dropped. This is the default setting.
SchemaAction.CREATE: Create tables and user-defined types from entities annotated with @Table and types annotated with @UserDefinedType. Existing tables/types will cause an error if the type is attempted to be created.
SchemaAction.CREATE_IF_NOT_EXISTS: Like SchemaAction.CREATE but with IF NOT EXISTS applied. Existing tables/types won’t cause any errors but may remain stale.
SchemaAction.RECREATE: Drops and recreate existing tables and types that are known to be used. Tables and types that are not configured in the application are not dropped.
SchemaAction.RECREATE_DROP_UNUSED: Drop all tables and types and recreate only known tables and types.

SchemaAction.RECREATE/SchemaAction.RECREATE_DROP_UNUSED will drop your tables and you will experience data loss. RECREATE_DROP_UNUSED also drops tables and types that are not know to the application.

Enabling Tables and User-Defined Types for Schema Management

Metadata based Mapping explains object mapping using conventions and annotations. Schema management is only active for entities annotated with @Table and user-defined types annotated with @UserDefinedType to prevent unwanted classes from being created as table/type. Entities are discovered by scanning the class path. Entity scanning requires one or more base packages.

Example 54. Specifying Entity Base Packages via XML

<cassandra:mapping entity-base-packages="com.foo,com.bar"/>

Example 55. Specifying Entity Base Packages via JavaConfig

@Configuration
public class CassandraConfiguration extends AbstractCassandraConfiguration {

	@Override
	public String[] getEntityBasePackages() {
		return new String[] { "com.foo", "com.bar" };
	}

	// ...
}

8.6. Introduction to CassandraTemplate

The CassandraTemplate class, located in the package org.springframework.data.cassandra, is the central class in Spring’s Cassandra support providing a rich feature set to interact with the database. The template offers convenience operations to create, update, delete and query Cassandra and provides a mapping between your domain objects and Cassandra rows.

Once configured, CassandraTemplate is Thread-safe and can be reused across multiple instances.

The mapping between Cassandra rows and domain classes is done by delegating to an implementation of the CassandraConverter interface. Spring provides a default implementation, MappingCassandraConverter, but you can also write your own converter. Please refer to the section on Cassandra conversion for more detailed information.

The CassandraTemplate class implements the interface CassandraOperations. In as much as possible, the methods on CassandraOperations are named after methods available with Cassandra to make the API familiar to existing Cassandra developers who are familiar with Cassandra. For example, you will find methods such as "select", "insert", "delete", and "update". The design goal was to make it as easy as possible to transition between the use of the base Cassandra driver and CassandraOperations. A major difference in between the two APIs is that CassandraOperations can be passed domain objects instead of CQL and query objects.

The preferred way to reference operations on a CassandraTemplate instance is via its interface, CassandraOperations.

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

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

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

8.6.1. Instantiating CassandraTemplate

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.

AutoWiring

@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), then use the `@Qualifier`annotation to designate which bean you want to Autowire.

@Autowired
@Qualifier("myTemplateBeanId")
private CassandraOperations cassandraOperations;

Bean Lookup with ApplicationContext

You can also just lookup the CassandraTemplate bean from the ApplicationContext.

CassandraOperations cassandraOperations = applicationContext.getBean("cassandraTemplate", CassandraOperations.class);

8.7. Saving, Updating, and Removing Rows

CassandraTemplate provides a simple way for you to save, update, and delete your domain objects, and map those objects to tables managed in Cassandra.

8.7.1. Working with Primary Keys

Cassandra requires at least one partition key field for a CQL Table. A table can declare additionally one or more clustering key fields. When your CQL Table has a composite primary key, you must create a @PrimaryKeyClass to define the structure of the composite primary key. In this context, composite primary key means one or more partition columns optionally combined with one or more clustering columns.

Primary keys can make use of any singular simple Cassandra type or mapped User-Defined Type. Collection-typed primary keys are not supported.

Simple Primary Key

A simple primary key consists of one partition key field within an entity class. Since it’s one field only, we safely can assume it’s a partition key.

Example 56. CQL Table defined in Cassandra

CREATE TABLE user (
  user_id text,
  firstname text,
  lastname text,
  PRIMARY KEY (user_id))
;

Example 57. Annotated Entity

@Table(value = "login_event")
public class LoginEvent {

  @PrimaryKey("user_id")
  private String userId;

  private String firstname;
  private String lastname;

  // getters and setters omitted for brevity

}

Composite Key

Composite primary keys (or compound keys) consist of more than one primary key fields. That said, a composite primary key can consist of multiple partition keys, a partition key and a clustering key, or a multitude of primary key fields.

Composite keys can be represented in two ways with Spring Data for Apache Cassandra:

Embedded in an entity.
By using @PrimaryKeyClass.

The simplest form 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.

Example 58. CQL Table with a Composite Primary Key

CREATE TABLE login_event(
  person_id text,
  event_code int,
  event_time timestamp,
  ip_address text,
  PRIMARY KEY (person_id, event_code, event_time))
  WITH CLUSTERING ORDER BY (event_time DESC)
;

Flat Composite Primary Key

Flat composite primary keys are embedded inside the entity as flat fields. Primary key fields are annotated with @PrimaryKeyColumn along with other fields in the entity. Selection requires either a query to contain predicates for the individual fields or the use of MapId.

Example 59. Using a flat Composite Primary Key

@Table(value = "login_event")
public class LoginEvent {

  @PrimaryKeyColumn(name = "person_id", ordinal = 0, type = PrimaryKeyType.PARTITIONED)
  private String personId;

  @PrimaryKeyColumn(name = "event_code", ordinal = 1, type = PrimaryKeyType.PARTITIONED)
  private int eventCode;

  @PrimaryKeyColumn(name = "event_time", ordinal = 2, type = PrimaryKeyType.CLUSTERED, ordering = Ordering.DESCENDING)
  private Date eventTime;

  @Column("ip_address)
  private String ipAddress;

  // getters and setters omitted for brevity
}

Primary Key Class

A primary key class is a composite primary key class that is mapped to multiple fields or properties of the entity. It’s annotated with @PrimaryKeyClass and defines equals and hashCode methods. The semantics of value equality for these methods should be consistent with the database equality for the database types to which the key is mapped. Primary key classes can be used with Repositories (as the Id type) and to represent an entities' identity in a single complex object.

Example 60. Composite Primary Key Class

@PrimaryKeyClass
public class LoginEventKey implements Serializable {

  @PrimaryKeyColumn(name = "person_id", ordinal = 0, type = PrimaryKeyType.PARTITIONED)
  private String personId;

  @PrimaryKeyColumn(name = "event_code", ordinal = 1, type = PrimaryKeyType.PARTITIONED)
  private int eventCode;

  @PrimaryKeyColumn(name = "event_time", ordinal = 2, type = PrimaryKeyType.CLUSTERED, ordering = Ordering.DESCENDING)
  private Date eventTime;

  // other methods omitted for brevity
}

Example 61. Using a Composite Primary Key

@Table(value = "login_event")
public class LoginEvent {

  @PrimaryKey
  private LoginEventKey key;

  @Column("ip_address)
  private String ipAddress;

  // getters and setters omitted for brevity
}

PrimaryKeyClass must implement Serializable and should provide implementations of hashCode() and equals().

8.7.2. Type mapping

Spring Data for Apache Cassandra relies on the DataStax Java Driver’s CodecRegistry to ensure type support. As types are added or changed, the Spring Data for Apache Cassandra module will continue to function without requiring changes. See CQL data types and Data mapping and type conversion for the current type mapping matrix.

8.7.3. Methods for saving and inserting rows

Single records inserts

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);

Multiple inserts for high speed ingestion

CqlOperations, which is extended by CassandraOperations is a low-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 set 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);

8.7.4. Updating rows in a CQL table

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);

8.7.5. Methods for removing rows

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);

8.7.6. Methods for truncating tables

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);

8.8. Querying CQL Tables

There 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()));
}

8.9. Overriding default mapping with custom converters

In order to have more fine grained control over the mapping process you can register Spring converters with the 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 MappingCassandraConverter.

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

8.9.1. Saving using a registered Spring Converter

An example implementation of the Converter that converts a Person object to a java.lang.String using Jackson 2 is shown below:

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

import org.springframework.util.StringUtils;
import org.codehaus.jackson.map.ObjectMapper;

static class PersonWriteConverter implements Converter<Person, String> {

  public String convert(Person source) {

    try {
      return new ObjectMapper().writeValueAsString(source);
    } catch (IOException e) {
      throw new IllegalStateException(e);
    }
  }
}

8.9.2. Reading using a Spring Converter

An example implementation of the Converter that converts a java.lang.String into a Person object using Jackson 2 is shown below:

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

import org.springframework.util.StringUtils;
import org.codehaus.jackson.map.ObjectMapper;

static class PersonReadConverter implements Converter<String, Person> {

  public Person convert(String source) {

   if (StringUtils.hasText(source)) {
     try {
       return new ObjectMapper().readValue(source, Person.class);
     } catch (IOException e) {
       throw new IllegalStateException(e);
     }
    }

    return null;
  }
}

8.9.3. Registering Spring Converters with the CassandraConverter

The Spring Data for Apache Cassandra Java Config provides a convenient way to register Spring Converter`s with the `MappingCassandraConverter. The configuration snippet below shows how to manually register converters as well as configuring the CustomConversions.

@Configuration
public static class Config extends AbstractCassandraConfiguration {

  @Override
  public CustomConversions customConversions() {

    List<Converter<?, ?>> converters = new ArrayList<Converter<?, ?>>();
    converters.add(new PersonReadConverter());
    converters.add(new PersonWriteConverter());

    return new CustomConversions(converters);
  }

  // other methods omitted...
}

8.9.4. Converter disambiguation

Generally, we inspect the Converter implementations for both source and target types they convert from and to. Depending on whether one of those is a type Cassandra can handle natively, Spring Data will register the Converter instance as a reading or writing one. Have a look at the following samples:

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

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

In case you write a Converter whose source and target type are native Cassandra types there’s no way for Spring Data to determine whether we should consider it as reading or writing Converter. Registering the Converter instance as both might lead to unwanted results.

E.g. a Converter<String, Long> is ambiguous although it probably does not make sense to try to convert all String instances into Long instances when writing. To be generally able to force the infrastructure to register a Converter for one way only we provide @ReadingConverter as well as @WritingConverter to be used as the appropriate Converter implementation.

8.10. Executing Commands

8.10.1. Methods for executing commands

The CassandraTemplate has many overloads for execute() and executeAsync(). Pass in the CQL command you wish to execute and handle the appropriate response.

This example uses the basic AsynchronousQueryListener that comes with Spring Data for Apache 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);

8.11. Exception Translation

The Spring Framework provides exception translation for a wide variety of database and mapping technologies. This has traditionally been for JDBC and JPA. The Spring support for Apache Cassandra extends this feature to Apache Cassandra 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.

9. Cassandra repositories

9.1. Introduction

This chapter covers the details of the Spring Data Repository support for Apache Cassandra. Cassandra’s Repository support builds on the core Repository support explained in Working with Spring Data Repositories. So make sure you understand of the basic concepts explained there before proceeding.

9.2. Usage

To access domain entities stored in Apache Cassandra, you can leverage Spring Data’s sophisticated Repository support that eases implementing DAOs quite significantly. To do so, simply create an interface for your Repository:

Example 62. Sample Person entity

@Table
public class Person {

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

  // … getters and setters omitted
}

We have a simple domain object here. Note that the entity has a property named id of type String. The default serialization mechanism used in CassandraTemplate (which is backing the Repository support) regards properties named id as row id.

Example 63. Basic Repository interface to persist Person entities

public interface PersonRepository extends CrudRepository<Person, String> {

  // 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 64. General Cassandra 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:cassandra="http://www.springframework.org/schema/data/cassandra"
  xsi:schemaLocation="
    http://www.springframework.org/schema/data/cassandra
    http://www.springframework.org/schema/data/cassandra/spring-cassandra.xsd
    http://www.springframework.org/schema/beans
    http://www.springframework.org/schema/beans/spring-beans.xsd">

    <cassandra:cluster port="9042"/>
    <cassandra:session keyspace-name="keyspaceName"/>

    <cassandra:mapping
            entity-base-packages="com.acme.*.entities">
    </cassandra:mapping>

    <cassandra:converter/>

    <cassandra:template/>

    <cassandra:repositories base-package="com.acme.*.entities"/>
</beans>

The cassandra:repositories namespace element will cause the base packages to be scanned for interfaces extending CrudRepository and create Spring beans for each one found. By default, the Repositories will be wired with a CassandraTemplate Spring bean called cassandraTemplate, so you only need to configure cassandra-template-ref explicitly if you deviate from this convention.

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

Example 65. JavaConfig for repositories

@Configuration
@EnableCassandraRepositories
class ApplicationConfig extends AbstractCassandraConfiguration {

  @Override
  protected String getKeyspaceName() {
    return "keyspace";
  }

  public String[] getEntityBasePackages() {
    return new String[] { "com.oreilly.springdata.cassandra" };
  }
}

As our domain Repository extends CrudRepository it provides you with basic CRUD operations. Working with the Repository instance is just a matter of injecting the Repository as a dependency into a client.

Example 66. Paging access to Person entities

@RunWith(SpringJUnit4ClassRunner.class)
@ContextConfiguration
public class PersonRepositoryTests {

    @Autowired PersonRepository repository;

    @Test
    public void readsPersonTableCorrectly() {

      List<Person> persons = repository.findAll();
      assertThat(persons.isEmpty()).isFalse();
    }
}

The sample creates an application context with Spring’s unit test support, which will perform annotation-based dependency injection into the test class. Inside the test cases (test methods) we simply use the Repository to query the data store. We invoke the Repository query method that requests the all Person instances.

9.3. Query methods

Most of the data access operations you usually trigger on a Repository result in a query being executed against the Apache Cassandra database. Defining such a query is just a matter of declaring a method on the Repository interface.

Example 67. PersonRepository with query methods

public interface PersonRepository extends CrudRepository<Person, String> {

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

    List<Person> findByFirstname(String firstname, Sort sort);         (2)

    Person findByShippingAddress(Address address);                     (3)

    Stream<Person> findAllBy();                                        (4)
}

1	The method shows a query for all people with the given `lastname`. The query will be derived from parsing the method name for constraints which can be concatenated with `And`. Thus the method name will result in a query expression of `SELECT * from person WHERE lastname = 'lastname'`.
2	Applies dynamic sorting to a query. Just add a `Sort` parameter to your method signature and Spring Data will automatically apply ordering to the query accordingly.
3	Shows that you can query based on properties which are not a primitive type using registered Converter’s in `CustomConversions.
4	Uses a Java 8 `Stream` which reads and converts individual elements while iterating the stream.

Querying non-primary key properties requires secondary indexes.

Table 3. Supported keywords for query methods
Keyword	Sample	Logical result
`After`	`findByBirthdateAfter(Date date)`	`birthdate > date`
`GreaterThan`	`findByAgeGreaterThan(int age)`	`age > age`
`GreaterThanEqual`	`findByAgeGreaterThanEqual(int age)`	`age >= age`
`Before`	`findByBirthdateBefore(Date date)`	`birthdate < date`
`LessThan`	`findByAgeLessThan(int age)`	`age < age`
`LessThanEqual`	`findByAgeLessThanEqual(int age)`	`age ⇐ age`
`In`	`findByAgeIn(Collection ages)`	`age IN (ages…)`
`Like`, `StartingWith`, `EndingWith`	`findByFirstnameLike(String name)`	`firstname LIKE (name as like expression)`
`Containing` on String	`findByFirstnameContaining(String name)`	`firstname LIKE (name as like expression)`
`Containing` on Collection	`findByAddressesContaining(Address address)`	`addresses CONTAINING address`
`(No keyword)`	`findByFirstname(String name)`	`firstname = name`
`IsTrue`, `True`	`findByActiveIsTrue()`	`active = true`
`IsFalse`, `False`	`findByActiveIsFalse()`	`active = false`

9.3.1. Projections

Spring Data query methods usually return one or multiple instances of the aggregate root managed by the repository. However, it might sometimes be desirable to create projections based on certain attributes of those types. Spring Data allows modeling dedicated return types, to more selectively retrieve partial views of the managed aggregates.

Imagine a repository and aggregate root type such as the following example:

Example 68. A sample aggregate and repository

class Person {

  @Id UUID id;
  String firstname, lastname;
  Address address;

  static class Address {
    String zipCode, city, street;
  }
}

interface PersonRepository extends Repository<Person, UUID> {

  Collection<Person> findByLastname(String lastname);
}

Now imagine that we want to retrieve the person’s name attributes only. What means does Spring Data offer to achieve this? The rest of this chapter answers that question.

Interface-based Projections

The easiest way to limit the result of the queries to only the name attributes is by declaring an interface that exposes accessor methods for the properties to be read, as shown in the following example:

Example 69. A projection interface to retrieve a subset of attributes

interface NamesOnly {

  String getFirstname();
  String getLastname();
}

The important bit here is that the properties defined here exactly match properties in the aggregate root. Doing so lets a query method be added as follows:

Example 70. A repository using an interface based projection with a query method

interface PersonRepository extends Repository<Person, UUID> {

  Collection<NamesOnly> findByLastname(String lastname);
}

The query execution engine creates proxy instances of that interface at runtime for each element returned and forwards calls to the exposed methods to the target object.

Projections can be used recursively. If you want to include some of the Address information as well, create a projection interface for that and return that interface from the declaration of getAddress(), as shown in the following example:

Example 71. A projection interface to retrieve a subset of attributes

interface PersonSummary {

  String getFirstname();
  String getLastname();
  AddressSummary getAddress();

  interface AddressSummary {
    String getCity();
  }
}

On method invocation, the address property of the target instance is obtained and wrapped into a projecting proxy in turn.

Closed Projections

A projection interface whose accessor methods all match properties of the target aggregate is considered to be a closed projection. The following example (which we used earlier in this chapter, too) is a closed projection:

Example 72. A closed projection

interface NamesOnly {

  String getFirstname();
  String getLastname();
}

If you use a closed projection, Spring Data can optimize the query execution, because we know about all the attributes that are needed to back the projection proxy. For more details on that, see the module-specific part of the reference documentation.

Open Projections

Accessor methods in projection interfaces can also be used to compute new values by using the @Value annotation, as shown in the following example:

Example 73. An Open Projection

interface NamesOnly {

  @Value("#{target.firstname + ' ' + target.lastname}")
  String getFullName();
  …
}

The aggregate root backing the projection is available in the target variable. A projection interface using @Value is an open projection. Spring Data cannot apply query execution optimizations in this case, because the SpEL expression could use any attribute of the aggregate root.

The expressions used in @Value should not be too complex — you want to avoid programming in String variables. For very simple expressions, one option might be to resort to default methods (introduced in Java 8), as shown in the following example:

Example 74. A projection interface using a default method for custom logic

interface NamesOnly {

  String getFirstname();
  String getLastname();

  default String getFullName() {
    return getFirstname.concat(" ").concat(getLastname());
  }
}

This approach requires you to be able to implement logic purely based on the other accessor methods exposed on the projection interface. A second, more flexible, option is to implement the custom logic in a Spring bean and then invoke that from the SpEL expression, as shown in the following example:

Example 75. Sample Person object

@Component
class MyBean {

  String getFullName(Person person) {
    …
  }
}

interface NamesOnly {

  @Value("#{@myBean.getFullName(target)}")
  String getFullName();
  …
}

Notice how the SpEL expression refers to myBean and invokes the getFullName(…) method and forwards the projection target as a method parameter. Methods backed by SpEL expression evaluation can also use method parameters, which can then be referred to from the expression. The method parameters are available through an Object array named args. The following example shows how to get a method parameter from the args array:

Example 76. Sample Person object

interface NamesOnly {

  @Value("#{args[0] + ' ' + target.firstname + '!'}")
  String getSalutation(String prefix);
}

Again, for more complex expressions, you should use a Spring bean and let the expression invoke a method, as described earlier.

Class-based Projections (DTOs)

Another way of defining projections is by using value type DTOs (Data Transfer Objects) that hold properties for the fields that are supposed to be retrieved. These DTO types can be used in exactly the same way projection interfaces are used, except that no proxying happens and no nested projections can be applied.

If the store optimizes the query execution by limiting the fields to be loaded, the fields to be loaded are determined from the parameter names of the constructor that is exposed.

The following example shows a projecting DTO:

Example 77. A projecting DTO

class NamesOnly {

  private final String firstname, lastname;

  NamesOnly(String firstname, String lastname) {

    this.firstname = firstname;
    this.lastname = lastname;
  }

  String getFirstname() {
    return this.firstname;
  }

  String getLastname() {
    return this.lastname;
  }

  // equals(…) and hashCode() implementations
}

Avoid boilerplate code for projection DTOs

You can dramatically simplify the code for a DTO by using Project Lombok, which provides an @Value annotation (not to be confused with Spring’s @Value annotation shown in the earlier interface examples). If you use Project Lombok’s @Value annotation, the sample DTO shown earlier would become the following:

@Value
class NamesOnly {
	String firstname, lastname;
}

Fields are private final by default, and the class exposes a constructor that takes all fields and automatically gets equals(…) and hashCode() methods implemented.

Dynamic Projections

So far, we have used the projection type as the return type or element type of a collection. However, you might want to select the type to be used at invocation time (which makes it dynamic). To apply dynamic projections, use a query method such as the one shown in the following example:

Example 78. A repository using a dynamic projection parameter

interface PersonRepository extends Repository<Person, UUID> {

  <T> Collection<T> findByLastname(String lastname, Class<T> type);
}

This way, the method can be used to obtain the aggregates as is or with a projection applied, as shown in the following example:

Example 79. Using a repository with dynamic projections

void someMethod(PersonRepository people) {

  Collection<Person> aggregates =
    people.findByLastname("Matthews", Person.class);

  Collection<NamesOnly> aggregates =
    people.findByLastname("Matthews", NamesOnly.class);
}

9.4. Miscellaneous

9.4.1. CDI Integration

Instances of the Repository interfaces are usually created by a container, and the Spring container is the most natural choice when working with Spring Data. Spring Data for Apache Cassandra 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 for Apache Cassandra JAR into your classpath. You can now set up the infrastructure by implementing a CDI Producer for the CassandraTemplate:

class CassandraTemplateProducer {

	@Produces
	@Singleton
	public Cluster createCluster() throws Exception {
		CassandraConnectionProperties properties = new CassandraConnectionProperties();

		Cluster cluster = Cluster.builder().addContactPoint(properties.getCassandraHost())
				.withPort(properties.getCassandraPort()).build();
		return cluster;
	}

	@Produces
	@Singleton
	public Session createSession(Cluster cluster) throws Exception {
		return cluster.connect();
	}

	@Produces
	@ApplicationScoped
	public CassandraOperations createCassandraOperations(Session session) throws Exception {

		MappingCassandraConverter cassandraConverter = new MappingCassandraConverter();
		cassandraConverter.setUserTypeResolver(new SimpleUserTypeResolver(session.getCluster(), session.getLoggedKeyspace()));

		CassandraAdminTemplate cassandraTemplate = new CassandraAdminTemplate(session, cassandraConverter);
		return cassandraTemplate;
	}

	public void close(@Disposes Session session) {
		session.close();
	}

	public void close(@Disposes Cluster cluster) {
		cluster.close();
	}
}

The Spring Data for Apache Cassandra CDI extension will pick up CassandraOperations 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();
  }
}

10. Mapping

Rich mapping support is provided by the MappingCassandraConverter . MappingCassandraConverter has a rich metadata model that provides a complete 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. The MappingCassandraConverter also allows you to map domain objects to tables without providing any additional metadata, by following a set of conventions.

In this section we will describe the features of the MappingCassandraConverter, how to use conventions for mapping domain objects to tables and how to override those conventions with annotation-based mapping metadata.

10.1. Convention based Mapping

MappingCassandraConverter uses a few conventions for mapping domain 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 savingsaccount table name.
The converter will use any registered Spring Converters to override the default mapping of object properties to tables fields.
The properties of an object are used to convert to and from properties in the table.

10.2. Data mapping and type conversion

This section explains how types are mapped to an Apache Cassandra representation and vice versa.

Spring Data for Apache Cassandra supports several types that are provided by Apache Cassandra. In addition to these types, Spring Data for Apache Cassandra provides a set of built-in converters to map additional types. You can provide your own converters to adjust type conversion, see Overriding Mapping with explicit Converters for further details.

Table 4. Type
Type	Cassandra types
`String`	`text` (default), `varchar`, `ascii`
`double`, `Double`	`double`
`float`, `Float`	`float`
`long`, `Long`	`bigint` (default), `counter`
`int`, `Integer`	`int`
`short`, `Short`	`smallint`
`byte`, `Byte`	`tinyint`
`boolean`, `Boolean`	`boolean`
`BigInteger`	`varint`
`BigDecimal`	`decimal`
`java.util.Date`	`timestamp`
`com.datastax.driver.core.LocalDate`	`date`
`InetAddress`	`inet`
`ByteBuffer`	`blob`
`java.util.UUID`	`timeuuid`
`UDTValue`, mapped User-Defined types	user type
`java.util.Map<K, V>`	`map`
`java.util.List<E>`	`list`
`java.util.Set<E>`	`set`
`Enum`	`text` (default), `bigint`, `varint`, `int`, `smallint`, `tinyint`
`LocalDate` (Joda, Java 8, JSR310-BackPort)	`date`
`LocalDateTime`, `LocalTime`, `Instant` (Joda, Java 8, JSR310-BackPort)	`timestamp`
`DateMidnight` (Joda)	`date`
`ZoneId` (Java 8, JSR310-BackPort)	`text`

Each supported type maps to a default Cassandra data type. Java types can be mapped to other Cassandra types by using @CassandraType.

.Enum Mapping to Numeric types

@Table
public class EnumToOrdinalMapping {

  @PrimaryKey String id;

  @CassandraType(type = Name.INT) Condition asOrdinal;
}

public enum Condition {
  NEW, USED
}

Enum mapping using ordinal values requires at least Spring 4.3.0. Using earlier Spring versions require custom converters for each Enum type.

10.2.1. Mapping Configuration

Unless explicitly configured, an instance of MappingCassandraConverter 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 for 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.

Example 80. @Configuration class to configure Cassandra mapping support

@Configuration
public static class Config extends AbstractCassandraConfiguration {

  @Override
  protected String getKeyspaceName() {
    return "bigbank";
  }

  // the following are optional

  @Override
  public CustomConversions customConversions() {

    List<Converter<?, ?>> converters = new ArrayList<Converter<?, ?>>();
    converters.add(new PersonReadConverter());
    converters.add(new PersonWriteConverter());

    return new CustomConversions(converters);
  }

  @Override
  public SchemaAction getSchemaAction() {
    return SchemaAction.RECREATE;
  }

  // other methods omitted...
}

AbstractCassandraConfiguration requires you to implement methods that define a keyspace. AbstractCassandraConfiguration also has a method you can override named getEntityBasePackages(…) which tells the Converter where to scan for classes annotated with the @Table annotation.

You can add additional converters to the Converter by overriding the method customConversions.

AbstractCassandraConfiguration will create a CassandraTemplate instance and register it with the container under the name cassandraTemplate.

10.3. Metadata based Mapping

To take full advantage of the object mapping functionality inside the Spring Data for Apache Cassandra support, you should annotate your mapped objects with the @Table annotation. It allows the classpath scanner to find and pre-process your domain objects to extract the necessary metadata. Only annotated entities will be used to perform schema actions. In the worst case, a SchemaAction.RECREATE_DROP_UNUSED will drop your tables and you will experience data loss.

Example 81. Example domain object

package com.mycompany.domain;

@Table
public class Person {

  @Id
  private String id;

  @CassandraType(type = Name.VARINT)
  private Integer ssn;

  private String firstName;

  private String lastName;
}

The @Id annotation tells the mapper which property you want to use for the Cassandra primary key. Composite primary keys can require a slightly different data model.

10.3.1. Mapping annotation overview

The MappingCassandraConverter can use metadata to drive the mapping of objects to rows. An overview of the annotations is provided below:

@Id - applied at the field or property level to mark the property used for identity purpose.
@Table - applied at the class level to indicate this class is a candidate for mapping to the database. You can specify the name of the table where the object will be stored.
@PrimaryKey - Similar to @Id but allows you to specify the column name.
@PrimaryKeyColumn - Cassandra-specific annotation for primary key columns that allows you to specify primary key column attributes such as for clustered/partitioned. Can be used on single and multiple attributes to indicate either a single or a compound primary key.
@PrimaryKeyClass - applied at the class level to indicate this class is a compound primary key class. Requires to be referenced with @PrimaryKey.
@Transient - by default all private fields are mapped to the row, this annotation excludes the field where it is applied from being stored in the database.
@Column - applied at the field level. Describes the column name as it will be represented in the Cassandra table thus allowing the name to be different than the field name of the class.
@CassandraType - applied at the field level to specify a Cassandra data type. Types are derived from the declaration by default.
@UserDefinedType - applied at the type level to specify a Cassandra user-defined data type (UDT). Types are derived from the declaration by default.

The mapping metadata infrastructure is defined in the separate, spring-data-commons project that is technology agnostic.

Here is an example of a more complex mapping.

Example 82. Mapped Person class

@Table("my_person")
public class Person {

  @PrimaryKeyClass
  public static class Key implements Serializable {

    @PrimaryKeyColumn(ordinal = 0, type = PrimaryKeyType.PARTITIONED)
    private String type;

    @PrimaryKeyColumn(ordinal = 1, type = PrimaryKeyType.PARTITIONED)
    private String value;

    @PrimaryKeyColumn(name = "correlated_type", ordinal = 2, type = PrimaryKeyType.CLUSTERED)
    private String correlatedType;

    // other getters/setters ommitted
  }

  @PrimaryKey
  private Person.Key key;

  @CassandraType(type = Name.VARINT)
  private Integer ssn;

  @Column("f_name")
  private String firstName;

  @Column(forceQuote = true)
  private String lastName;

  private Address address;

  @CassandraType(type = Name.UDT, userTypeName = "myusertype")
  private UDTValue usertype;

  @Transient
  private Integer accountTotal;

  @CassandraType(type = Name.SET, typeArguments = Name.BIGINT)
  private Set<Long> timestamps;

  private Map<String, InetAddress> sessions;

  public Person(Integer ssn) {
    this.ssn = ssn;
  }

  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
}

Example 83. Mapped User-Defined type Address

@UserDefinedType("address")
public class Address {

  private String city;

  @CassandraType(type = Name.VARCHAR)
  private String street;

  private Set<String> zipcodes;

  @CassandraType(type = Name.SET, typeArguments = Name.BIGINT)
  private List<Long> timestamps;

  // other getters/setters ommitted
}

Working with User-Defined Types requires a UserTypeResolver configured with the mapping context. See the configuration chapter for how to configure a UserTypeResolver.

10.3.2. Overriding Mapping with explicit Converters

When storing and querying your objects it is convenient to have a CassandraConverter instance handle the mapping of all Java types to Rows. However, sometimes you may want the CassandraConverter to do most of the work but still allow you to selectively handle the conversion for a particular type, or to optimize performance.

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

Spring 3.0 introduced a o.s.core.convert package that provides a general type conversion system. This is described in detail in the Spring reference documentation section entitled Spring Type Conversion.

Below is an example of a Spring Converter implementation that converts from a Row to a Person POJO.

@ReadingConverter
 public class PersonReadConverter implements Converter<Row, Person> {

  public Person convert(Row source) {
    Person p = new Person(row.getString("id"));
    p.setAge(source.getInt("age");
    return p;
  }
}

Appendix

Appendix A: Namespace reference

The `<repositories />` Element

The <repositories /> element triggers the setup of the Spring Data repository infrastructure. The most important attribute is base-package, which defines the package to scan for Spring Data repository interfaces. See “XML configuration”. The following table describes the attributes of the <repositories /> element:

Table 5. Attributes
Name	Description
`base-package`	Defines the package to be scanned for repository interfaces that extend `*Repository` (the actual interface is determined by the specific Spring Data module) in auto-detection mode. All packages below the configured package are scanned, too. Wildcards are allowed.
`repository-impl-postfix`	Defines the postfix to autodetect custom repository implementations. Classes whose names end with the configured postfix are considered as candidates. Defaults to `Impl`.
`query-lookup-strategy`	Determines the strategy to be used to create finder queries. See “Query Lookup Strategies” for details. Defaults to `create-if-not-found`.
`named-queries-location`	Defines the location to search for a Properties file containing externally defined queries.
`consider-nested-repositories`	Whether nested repository interface definitions should be considered. Defaults to `false`.

Appendix B: Populators namespace reference

The <populator /> element

The <populator /> element allows to populate the a data store via the Spring Data repository infrastructure.^[1]

Table 6. Attributes
Name	Description
`locations`	Where to find the files to read the objects from the repository shall be populated with.

Appendix C: Repository query keywords

Supported query keywords

The following table lists the keywords generally supported by the Spring Data repository query derivation mechanism. However, consult the store-specific documentation for the exact list of supported keywords, because some keywords listed here might not be supported in a particular store.

Table 7. Query keywords
Logical keyword	Keyword expressions
`AND`	`And`
`OR`	`Or`
`AFTER`	`After`, `IsAfter`
`BEFORE`	`Before`, `IsBefore`
`CONTAINING`	`Containing`, `IsContaining`, `Contains`
`BETWEEN`	`Between`, `IsBetween`
`ENDING_WITH`	`EndingWith`, `IsEndingWith`, `EndsWith`
`EXISTS`	`Exists`
`FALSE`	`False`, `IsFalse`
`GREATER_THAN`	`GreaterThan`, `IsGreaterThan`
`GREATER_THAN_EQUALS`	`GreaterThanEqual`, `IsGreaterThanEqual`
`IN`	`In`, `IsIn`
`IS`	`Is`, `Equals`, (or no keyword)
`IS_NOT_NULL`	`NotNull`, `IsNotNull`
`IS_NULL`	`Null`, `IsNull`
`LESS_THAN`	`LessThan`, `IsLessThan`
`LESS_THAN_EQUAL`	`LessThanEqual`, `IsLessThanEqual`
`LIKE`	`Like`, `IsLike`
`NEAR`	`Near`, `IsNear`
`NOT`	`Not`, `IsNot`
`NOT_IN`	`NotIn`, `IsNotIn`
`NOT_LIKE`	`NotLike`, `IsNotLike`
`REGEX`	`Regex`, `MatchesRegex`, `Matches`
`STARTING_WITH`	`StartingWith`, `IsStartingWith`, `StartsWith`
`TRUE`	`True`, `IsTrue`
`WITHIN`	`Within`, `IsWithin`

Appendix D: Repository query return types

Supported Query Return Types

The following table lists the return types generally supported by Spring Data repositories. However, consult the store-specific documentation for the exact list of supported return types, because some types listed here might not be supported in a particular store.

Geospatial types (such as GeoResult, GeoResults, and GeoPage) are available only for data stores that support geospatial queries.

Table 8. Query return types
Return type	Description
`void`	Denotes no return value.
Primitives	Java primitives.
Wrapper types	Java wrapper types.
`T`	An unique entity. Expects the query method to return one result at most. If no result is found, `null` is returned. More than one result triggers an `IncorrectResultSizeDataAccessException`.
`Iterator<T>`	An `Iterator`.
`Collection<T>`	A `Collection`.
`List<T>`	A `List`.
`Optional<T>`	A Java 8 or Guava `Optional`. Expects the query method to return one result at most. If no result is found, `Optional.empty()` or `Optional.absent()` is returned. More than one result triggers an `IncorrectResultSizeDataAccessException`.
`Option<T>`	Either a Scala or Javaslang `Option` type. Semantically the same behavior as Java 8’s `Optional`, described earlier.
`Stream<T>`	A Java 8 `Stream`.
`Future<T>`	A `Future`. Expects a method to be annotated with `@Async` and requires Spring’s asynchronous method execution capability to be enabled.
`CompletableFuture<T>`	A Java 8 `CompletableFuture`. Expects a method to be annotated with `@Async` and requires Spring’s asynchronous method execution capability to be enabled.
`ListenableFuture`	A `org.springframework.util.concurrent.ListenableFuture`. Expects a method to be annotated with `@Async` and requires Spring’s asynchronous method execution capability to be enabled.
`Slice`	A sized chunk of data with an indication of whether there is more data available. Requires a `Pageable` method parameter.
`Page<T>`	A `Slice` with additional information, such as the total number of results. Requires a `Pageable` method parameter.
`GeoResult<T>`	A result entry with additional information, such as the distance to a reference location.
`GeoResults<T>`	A list of `GeoResult<T>` with additional information, such as the average distance to a reference location.
`GeoPage<T>`	A `Page` with `GeoResult<T>`, such as the average distance to a reference location.
`Mono<T>`	A Project Reactor `Mono` emitting zero or one element using reactive repositories. Expects the query method to return one result at most. If no result is found, `Mono.empty()` is returned. More than one result triggers an `IncorrectResultSizeDataAccessException`.
`Flux<T>`	A Project Reactor `Flux` emitting zero, one, or many elements using reactive repositories. Queries returning `Flux` can emit also an infinite number of elements.
`Single<T>`	A RxJava `Single` emitting a single element using reactive repositories. Expects the query method to return one result at most. If no result is found, `Mono.empty()` is returned. More than one result triggers an `IncorrectResultSizeDataAccessException`.
`Maybe<T>`	A RxJava `Maybe` emitting zero or one element using reactive repositories. Expects the query method to return one result at most. If no result is found, `Mono.empty()` is returned. More than one result triggers an `IncorrectResultSizeDataAccessException`.
`Flowable<T>`	A RxJava `Flowable` emitting zero, one, or many elements using reactive repositories. Queries returning `Flowable` can emit also an infinite number of elements.

Spring Data for Apache Cassandra - Reference Documentation

Preface

1. Knowing Spring

2. Knowing NoSQL and Cassandra

3. Requirements

4. Additional Help Resources

4.1. Support

4.1.1. Community Forum

4.1.2. Professional Support

4.2. Following Development

4.3. Project Metadata

5. New & Noteworthy

5.1. What’s new in Spring Data for Apache Cassandra 1.5

6. Dependencies

6.1. Dependency Management with Spring Boot

6.2. Spring Framework

7. Working with Spring Data Repositories

7.1. Core concepts

7.2. Query methods

7.3. Defining Repository Interfaces

7.3.1. Fine-tuning Repository Definition

7.3.2. Using Repositories with Multiple Spring Data Modules

7.4. Defining Query Methods

7.4.1. Query Lookup Strategies

7.4.2. Query Creation

7.4.3. Property Expressions

7.4.4. Special parameter handling

7.4.5. Limiting Query Results

7.4.6. Streaming query results

7.4.7. Async query results

7.5. Creating Repository Instances

7.5.1. XML configuration

Using filters

7.5.2. JavaConfig

7.5.3. Standalone usage

7.6. Custom implementations for Spring Data repositories

7.6.1. Adding custom behavior to single repositories

Configuration

Manual Wiring

7.6.2. Adding custom behavior to all repositories

7.7. Publishing Events from Aggregate Roots

7.8. Spring Data Extensions

7.8.1. Querydsl Extension

7.8.2. Web support

Basic Web Support

DomainClassConverter

HandlerMethodArgumentResolvers for Pageable and Sort

Hypermedia Support for Pageables

Web Databinding Support

Querydsl Web Support

7.8.3. Repository Populators

7.8.4. Legacy web support

Domain class web binding for Spring MVC

PropertyEditors

Reference Documentation

Document Structure

8. Cassandra support

8.1. Spring CQL and Spring Data for Apache Cassandra modules

8.1.1. Choosing an approach for Cassandra database access

8.2. Getting Started

8.3. Examples Repository

8.4. Connecting to Cassandra with Spring

8.4.1. Registering a Session instance using Java based metadata

8.4.2. XML Configuration

Externalize Connection Properties

Registering a Session instance using XML based metadata

8.5. Schema Management

8.5.1. Keyspaces and Lifecycle scripts

8.5.2. Tables and User-defined types

Enabling Tables and User-Defined Types for Schema Management

8.6. Introduction to CassandraTemplate

8.6.1. Instantiating CassandraTemplate

AutoWiring

Bean Lookup with ApplicationContext

8.7. Saving, Updating, and Removing Rows

8.7.1. Working with Primary Keys

Simple Primary Key

Composite Key

Flat Composite Primary Key

Primary Key Class

`DomainClassConverter`

The `<repositories />` Element