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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. This project has noticeable 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 and 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 you are familiar with Cassandra as well as core Spring concepts.

1. Knowing Spring

Spring Data uses the Spring Framework’s core functionality, including:

While it is not important to know the Spring APIs, understanding the concepts behind them is important. 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 use all the features of Spring Data for Apache Cassandra, such as the repository support, you must configure some parts of the library by using Spring.

To learn more about Spring, you can refer to the comprehensive documentation that explains the Spring Framework in detail. There are a lot of articles, blog entries, and books on Spring. See 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 you be 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 does not take more then 5-10 minutes to go through them, and, if you come from a RDBMS background, these exercises can often be an eye opener.

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

3. Requirements

Spring Data for Apache Cassandra 2.x binaries require JDK level 8.0 and later and Spring Framework 6.0.7 and later.

It requires Cassandra 2.0 or later and Datastax driver 4.x.

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 the Spring Data for Apache Cassandra module. However, if you encounter issues or you need advice, feel free to use one of the links below:

Community Forum

Spring Data on Stack Overflow 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. The two key tags to search for related answers to this project are spring-data and spring-data-cassandra.

Professional Support

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

4.1. Following Development

For information on the Spring Data for Apache Cassandra source code repository, nightly builds, and snapshot artifacts see the Spring Data for Apache Cassandra home page. You can help make Spring Data best serve the needs of the Spring community by interacting with developers through the community on Stack Overflow. To follow developer activity, look for the mailing list information on the Spring Data for Apache Cassandra home page. 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 ecosystem, subscribe to the Spring Community Portal. Finally, you can follow the Spring blog or the project team on Twitter (SpringData).

4.2. Project Metadata

5. 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-bom</artifactId>
      <version>2023.0.0-M3</version>
      <scope>import</scope>
      <type>pom</type>
    </dependency>
  </dependencies>
</dependencyManagement>

The current release train version is 2023.0.0-M3. The train version uses calver with the pattern YYYY.MINOR.MICRO. The version name follows ${calver} for GA releases and service releases and the following pattern for all other versions: ${calver}-${modifier}, where modifier can be one of the following:

  • SNAPSHOT: Current snapshots

  • M1, M2, and so on: Milestones

  • RC1, RC2, and so on: Release candidates

You can find a working example of using the BOMs 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>

5.1. Dependency Management with Spring Boot

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

See Spring Boot’s documentation (search for "Spring Data Bom") for more details.

5.2. Spring Framework

The current version of Spring Data modules require Spring Framework 6.0.7 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.

6. 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 Jakarta Persistence API (JPA) module. If you want to use XML configuration 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 that support 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.

6.1. Core concepts

The central interface in the Spring Data repository abstraction is Repository. It takes the domain class to manage as well as the identifier 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 and ListCrudRepository interfaces provide sophisticated CRUD functionality for the entity class that is being managed.

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

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

  Optional<T> findById(ID primaryKey); (2)

  Iterable<T> findAll();               (3)

  long count();                        (4)

  void delete(T entity);               (5)

  boolean existsById(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.

The methods declared in this interface are commonly referred to as CRUD methods. ListCrudRepository offers equivalent methods, but they return List where the CrudRepository methods return an Iterable.

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.

Additional to 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>  {

  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(PageRequest.of(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
interface UserRepository extends CrudRepository<User, Long> {

  long countByLastname(String lastname);
}

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

Example 6. Derived Delete Query
interface UserRepository extends CrudRepository<User, Long> {

  long deleteByLastname(String lastname);

  List<User> removeByLastname(String lastname);
}

6.2. Query Methods

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

  1. Declare an interface extending Repository or one of its subinterfaces and type it to the domain class and ID type that it should handle, as shown in the following example:

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

  2. Declare query methods on the interface.

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

  3. Set up Spring to create proxy instances for those interfaces, either with JavaConfig or with XML configuration.

    Java
    import org.springframework.data.….repository.config.EnableJpaRepositories;

@EnableJpaRepositories
class Config { … }
    XML
    <?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
     https://www.springframework.org/schema/beans/spring-beans.xsd
     http://www.springframework.org/schema/data/jpa
     https://www.springframework.org/schema/data/jpa/spring-jpa.xsd">

   <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.

    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 @EnableJpaRepositories-annotation.

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

    class SomeClient {

  private final PersonRepository repository;

  SomeClient(PersonRepository repository) {
    this.repository = repository;
  }

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

The sections that follow explain each step in detail:

6.3. Defining Repository Interfaces

To define a repository interface, you first need to 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, you may extend CrudRepository, or one of its variants instead of Repository.

6.3.1. Fine-tuning Repository Definition

There are a few variants how you can get started with your repository interface.

The typical approach is to extend CrudRepository, which gives you methods for CRUD functionality. CRUD stands for Create, Read, Update, Delete. With version 3.0 we also introduced ListCrudRepository which is very similar to the CrudRepository but for those methods that return multiple entities it returns a List instead of an Iterable which you might find easier to use.

If you are using a reactive store you might choose ReactiveCrudRepository, or RxJava3CrudRepository depending on which reactive framework you are using.

If you are using Kotlin you might pick CoroutineCrudRepository which utilizes Kotlin’s coroutines.

Additional you can extend PagingAndSortingRepository, ReactiveSortingRepository, RxJava3SortingRepository, or CoroutineSortingRepository if you need methods that allow to specify a Sort abstraction or in the first case a Pageable abstraction. Note that the various sorting repositories no longer extended their respective CRUD repository as they did in Spring Data Versions pre 3.0. Therefore, you need to extend both interfaces if you want functionality of both.

If you do not want to extend Spring Data interfaces, you can also annotate your repository interface with @RepositoryDefinition. Extending one of the CRUD repository interfaces 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 the CRUD repository into your domain repository. When doing so, you may change the return type of methods. Spring Data will honor the return type if possible. For example, for methods returning multiple entities you may choose Iterable<T>, List<T>, Collection<T> or a VAVR list.

If many repositories in your application should have the same set of methods you can define your own base interface to inherit from. Such an interface must be annotated with @NoRepositoryBean. This prevents Spring Data to try to create an instance of it directly and failing because it can’t determine the entity for that repository, since it still contains a generic type variable.

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 Repository<T, ID> {

  Optional<T> findById(ID id);

  <S extends T> S save(S 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 findById(…) 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.

6.3.2. 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:

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

  2. If the domain class is annotated with the module-specific type annotation, 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 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 CrudRepository<T, ID> { … }

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

AmbiguousRepository and AmbiguousUserRepository extend only Repository and CrudRepository in their type hierarchy. While this is 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
class Person { … }

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

@Document
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
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")
class Configuration { … }

6.4. 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.

6.4.1. 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 EnableJpaRepositories 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 it cannot find one. The query can be defined by an annotation somewhere or declared by other means. See 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 (the 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.

6.4.2. Query Creation

The query builder mechanism built into the Spring Data repository infrastructure is useful for building constraining queries over entities of the repository.

The following example shows how to create a number of queries:

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

Parsing query method names is divided into subject and predicate. The first part (find…By, exists…By) defines the subject of the query, the second part forms the predicate. The introducing clause (subject) can contain further expressions. Any text between find (or other introducing keywords) and By is considered to be descriptive unless using one of the result-limiting keywords such as a Distinct to set a distinct flag on the query to be created or Top/First to limit query results.

The appendix contains the full list of query method subject keywords and query method predicate keywords including sorting and letter-casing modifiers. However, the first By acts as a delimiter to indicate the start of the actual criteria predicate. At a very basic level, you can define conditions on entity properties and concatenate them with And and Or.

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”.

6.4.3. 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 x.address.zipCode property traversal. 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).

6.4.4. 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);
APIs taking Sort and Pageable expect non-null values to be handed into methods. If you do not want to apply any sorting or pagination, use Sort.unsorted() and Pageable.unpaged().

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 knows only 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 need only 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.
Paging and Sorting

You can define simple sorting expressions by using property names. You can concatenate expressions to collect multiple criteria into one expression.

Example 15. Defining sort expressions
Sort sort = Sort.by("firstname").ascending()
  .and(Sort.by("lastname").descending());

For a more type-safe way to define sort expressions, start with the type for which to define the sort expression and use method references to define the properties on which to sort.

Example 16. Defining sort expressions by using the type-safe API
TypedSort<Person> person = Sort.sort(Person.class);

Sort sort = person.by(Person::getFirstname).ascending()
  .and(person.by(Person::getLastname).descending());
TypedSort.by(…) makes use of runtime proxies by (typically) using CGlib, which may interfere with native image compilation when using tools such as Graal VM Native.

If your store implementation supports Querydsl, you can also use the generated metamodel types to define sort expressions:

Example 17. Defining sort expressions by using the Querydsl API
QSort sort = QSort.by(QPerson.firstname.asc())
  .and(QSort.by(QPerson.lastname.desc()));

6.4.5. Limiting Query Results

You can limit the results of query methods by using the first or top keywords, which you can use interchangeably. You can append an optional numeric value 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 18. 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 for datastores that support distinct queries. Also, for the queries that limit 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 available pages), 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.

6.4.6. Repository Methods Returning Collections or Iterables

Query methods that return multiple results can use standard Java Iterable, List, and Set. Beyond that, we support returning Spring Data’s Streamable, a custom extension of Iterable, as well as collection types provided by Vavr. Refer to the appendix explaining all possible query method return types.

Using Streamable as Query Method Return Type

You can use Streamable as alternative to Iterable or any collection type. It provides convenience methods to access a non-parallel Stream (missing from Iterable) and the ability to directly ….filter(…) and ….map(…) over the elements and concatenate the Streamable to others:

Example 19. Using Streamable to combine query method results
interface PersonRepository extends Repository<Person, Long> {
  Streamable<Person> findByFirstnameContaining(String firstname);
  Streamable<Person> findByLastnameContaining(String lastname);
}

Streamable<Person> result = repository.findByFirstnameContaining("av")
  .and(repository.findByLastnameContaining("ea"));
Returning Custom Streamable Wrapper Types

Providing dedicated wrapper types for collections is a commonly used pattern to provide an API for a query result that returns multiple elements. Usually, these types are used by invoking a repository method returning a collection-like type and creating an instance of the wrapper type manually. You can avoid that additional step as Spring Data lets you use these wrapper types as query method return types if they meet the following criteria:

  1. The type implements Streamable.

  2. The type exposes either a constructor or a static factory method named of(…) or valueOf(…) that takes Streamable as an argument.

The following listing shows an example:

class Product {                                         (1)
  MonetaryAmount getPrice() { … }
}

@RequiredArgsConstructor(staticName = "of")
class Products implements Streamable<Product> {         (2)

  private final Streamable<Product> streamable;

  public MonetaryAmount getTotal() {                    (3)
    return streamable.stream()
      .map(Priced::getPrice)
      .reduce(Money.of(0), MonetaryAmount::add);
  }


  @Override
  public Iterator<Product> iterator() {                 (4)
    return streamable.iterator();
  }
}

interface ProductRepository implements Repository<Product, Long> {
  Products findAllByDescriptionContaining(String text); (5)
}
1 A Product entity that exposes API to access the product’s price.
2 A wrapper type for a Streamable<Product> that can be constructed by using Products.of(…) (factory method created with the Lombok annotation). A standard constructor taking the Streamable<Product> will do as well.
3 The wrapper type exposes an additional API, calculating new values on the Streamable<Product>.
4 Implement the Streamable interface and delegate to the actual result.
5 That wrapper type Products can be used directly as a query method return type. You do not need to return Streamable<Product> and manually wrap it after the query in the repository client.
Support for Vavr Collections

Vavr is a library that embraces functional programming concepts in Java. It ships with a custom set of collection types that you can use as query method return types, as the following table shows:

Vavr collection type Used Vavr implementation type Valid Java source types

io.vavr.collection.Seq

io.vavr.collection.List

java.util.Iterable

io.vavr.collection.Set

io.vavr.collection.LinkedHashSet

java.util.Iterable

io.vavr.collection.Map

io.vavr.collection.LinkedHashMap

java.util.Map

You can use the types in the first column (or subtypes thereof) as query method return types and get the types in the second column used as implementation type, depending on the Java type of the actual query result (third column). Alternatively, you can declare Traversable (the Vavr Iterable equivalent), and we then derive the implementation class from the actual return value. That is, a java.util.List is turned into a Vavr List or Seq, a java.util.Set becomes a Vavr LinkedHashSet Set, and so on.

6.4.7. Null Handling of Repository Methods

As of Spring Data 2.0, repository CRUD methods that return an individual aggregate instance use Java 8’s Optional to indicate the potential absence of a value. Besides that, Spring Data supports returning the following wrapper types on query methods:

  • com.google.common.base.Optional

  • scala.Option

  • io.vavr.control.Option

Alternatively, query methods can choose not to use a wrapper type at all. The absence of a query result is then indicated by returning null. Repository methods returning collections, collection alternatives, wrappers, and streams are guaranteed never to return null but rather the corresponding empty representation. See “Repository query return types” for details.

Nullability Annotations

You can express nullability constraints for repository methods by using Spring Framework’s nullability annotations. They provide a tooling-friendly approach and opt-in null checks during runtime, as follows:

  • @NonNullApi: Used on the package level to declare that the default behavior for parameters and return values is, respectively, neither to accept nor to produce null values.

  • @NonNull: Used on a parameter or return value that must not be null (not needed on a parameter and return value where @NonNullApi applies).

  • @Nullable: Used on a parameter or return value that can be null.

Spring annotations are meta-annotated with JSR 305 annotations (a dormant but widely used JSR). JSR 305 meta-annotations let tooling vendors (such as IDEA, Eclipse, and Kotlin) provide null-safety support in a generic way, without having to hard-code support for Spring annotations. To enable runtime checking of nullability constraints for query methods, you need to activate non-nullability on the package level by using Spring’s @NonNullApi in package-info.java, as shown in the following example:

Example 20. Declaring Non-nullability in package-info.java
@org.springframework.lang.NonNullApi
package com.acme;

Once non-null defaulting is in place, repository query method invocations get validated at runtime for nullability constraints. If a query result violates the defined constraint, an exception is thrown. This happens when the method would return null but is declared as non-nullable (the default with the annotation defined on the package in which the repository resides). If you want to opt-in to nullable results again, selectively use @Nullable on individual methods. Using the result wrapper types mentioned at the start of this section continues to work as expected: an empty result is translated into the value that represents absence.

The following example shows a number of the techniques just described:

Example 21. Using different nullability constraints
package com.acme;                                                       (1)

import org.springframework.lang.Nullable;

interface UserRepository extends Repository<User, Long> {

  User getByEmailAddress(EmailAddress emailAddress);                    (2)

  @Nullable
  User findByEmailAddress(@Nullable EmailAddress emailAdress);          (3)

  Optional<User> findOptionalByEmailAddress(EmailAddress emailAddress); (4)
}
1 The repository resides in a package (or sub-package) for which we have defined non-null behavior.
2 Throws an EmptyResultDataAccessException when the query does not produce a result. Throws an IllegalArgumentException when the emailAddress handed to the method is null.
3 Returns null when the query does not produce a result. Also accepts null as the value for emailAddress.
4 Returns Optional.empty() when the query does not produce a result. Throws an IllegalArgumentException when the emailAddress handed to the method is null.
Nullability in Kotlin-based Repositories

Kotlin has the definition of nullability constraints baked into the language. Kotlin code compiles to bytecode, which does not express nullability constraints through method signatures but rather through compiled-in metadata. Make sure to include the kotlin-reflect JAR in your project to enable introspection of Kotlin’s nullability constraints. Spring Data repositories use the language mechanism to define those constraints to apply the same runtime checks, as follows:

Example 22. Using nullability constraints on Kotlin repositories
interface UserRepository : Repository<User, String> {

  fun findByUsername(username: String): User     (1)

  fun findByFirstname(firstname: String?): User? (2)
}
1 The method defines both the parameter and the result as non-nullable (the Kotlin default). The Kotlin compiler rejects method invocations that pass null to the method. If the query yields an empty result, an EmptyResultDataAccessException is thrown.
2 This method accepts null for the firstname parameter and returns null if the query does not produce a result.

6.4.8. Streaming Query Results

You can process the results of query methods incrementally by using a Java 8 Stream<T> as the 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 23. 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 24. 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.

6.4.9. Asynchronous Query Results

You can run repository queries asynchronously by using Spring’s asynchronous method running capability. This means the method returns immediately upon invocation while the actual query occurs in a task that has been submitted to a Spring TaskExecutor. Asynchronous queries differ from reactive queries and should not be mixed. See the 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)
1 Use java.util.concurrent.Future as the return type.
2 Use a Java 8 java.util.concurrent.CompletableFuture as the return type.

6.5. Creating Repository Instances

This section covers how to create instances and bean definitions for the defined repository interfaces.

6.5.1. Java Configuration

Use the store-specific @EnableJpaRepositories annotation on a Java configuration class to define a configuration for repository activation. For an introduction to 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 25. Sample annotation-based repository configuration
@Configuration
@EnableJpaRepositories("com.acme.repositories")
class ApplicationConfiguration {

  @Bean
  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.

6.5.2. 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 26. 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
    https://www.springframework.org/schema/beans/spring-beans.xsd
    http://www.springframework.org/schema/data/jpa
    https://www.springframework.org/schema/data/jpa/spring-jpa.xsd">

  <jpa: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. Bean names for nested repository interfaces are prefixed with their enclosing type name. The base package attribute allows wildcards so that you can define a pattern of scanned packages.

6.5.3. Using Filters

By default, the infrastructure picks up every interface that extends 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 filter elements inside the repository declaration. The semantics are exactly equivalent to the elements in Spring’s component filters. 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 27. Using filters
Java
@Configuration
@EnableJpaRepositories(basePackages = "com.acme.repositories",
    includeFilters = { @Filter(type = FilterType.REGEX, pattern = ".*SomeRepository") },
    excludeFilters = { @Filter(type = FilterType.REGEX, pattern = ".*SomeOtherRepository") })
class ApplicationConfiguration {

  @Bean
  EntityManagerFactory entityManagerFactory() {
    // …
  }
}
XML
<repositories base-package="com.acme.repositories">
  <context:exclude-filter type="regex" expression=".*SomeRepository" />
  <context:include-filter type="regex" expression=".*SomeOtherRepository" />
</repositories>

The preceding example excludes all interfaces ending in SomeRepository from being instantiated and includes those ending with SomeOtherRepository.

6.5.4. 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 with a persistence technology-specific RepositoryFactory that you can use, as follows:

Example 28. Standalone usage of the repository factory
RepositoryFactorySupport factory = … // Instantiate factory here
UserRepository repository = factory.getRepository(UserRepository.class);

6.6. Custom Implementations for Spring Data Repositories

Spring Data provides various options to create query methods with little coding. But when those options don’t fit your needs you can also provide your own custom implementation for repository methods. This section describes how to do that.

6.6.1. Customizing Individual Repositories

To enrich a repository with custom functionality, you must first define a fragment interface and an implementation for the custom functionality, as follows:

Example 29. Interface for custom repository functionality
interface CustomizedUserRepository {
  void someCustomMethod(User user);
}
Example 30. Implementation of custom repository functionality
class CustomizedUserRepositoryImpl implements CustomizedUserRepository {

  public void someCustomMethod(User user) {
    // Your custom implementation
  }
}
The most important part of the class name that corresponds to the fragment interface is the Impl postfix.

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.

Then you can let your repository interface extend the fragment interface, as follows:

Example 31. Changes to your repository interface
interface UserRepository extends CrudRepository<User, Long>, CustomizedUserRepository {

  // Declare query methods here
}

Extending the fragment interface with your repository interface combines the CRUD and custom functionality and makes it available to clients.

Spring Data repositories are implemented by using fragments that form a repository composition. Fragments are the base repository, functional aspects (such as QueryDsl), and custom interfaces along with their implementations. Each time you add an interface to your repository interface, you enhance the composition by adding a fragment. The base repository and repository aspect implementations are provided by each Spring Data module.

The following example shows custom interfaces and their implementations:

Example 32. Fragments with their implementations
interface HumanRepository {
  void someHumanMethod(User user);
}

class HumanRepositoryImpl implements HumanRepository {

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

interface ContactRepository {

  void someContactMethod(User user);

  User anotherContactMethod(User user);
}

class ContactRepositoryImpl implements ContactRepository {

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

  public User anotherContactMethod(User user) {
    // Your custom implementation
  }
}

The following example shows the interface for a custom repository that extends CrudRepository:

Example 33. Changes to your repository interface
interface UserRepository extends CrudRepository<User, Long>, HumanRepository, ContactRepository {

  // Declare query methods here
}

Repositories may be composed of multiple custom implementations that are imported in the order of their declaration. Custom implementations have a higher priority than the base implementation and repository aspects. This ordering lets you override base repository and aspect methods and resolves ambiguity if two fragments contribute the same method signature. Repository fragments are not limited to use in a single repository interface. Multiple repositories may use a fragment interface, letting you reuse customizations across different repositories.

The following example shows a repository fragment and its implementation:

Example 34. Fragments overriding save(…)
interface CustomizedSave<T> {
  <S extends T> S save(S entity);
}

class CustomizedSaveImpl<T> implements CustomizedSave<T> {

  public <S extends T> S save(S entity) {
    // Your custom implementation
  }
}

The following example shows a repository that uses the preceding repository fragment:

Example 35. Customized repository interfaces
interface UserRepository extends CrudRepository<User, Long>, CustomizedSave<User> {
}

interface PersonRepository extends CrudRepository<Person, Long>, CustomizedSave<Person> {
}
Configuration

The repository infrastructure tries to autodetect custom implementation fragments by scanning for classes below the package in which it found a repository. These classes need to follow the naming convention of appending a postfix defaulting to Impl.

The following example shows a repository that uses the default postfix and a repository that sets a custom value for the postfix:

Example 36. Configuration example
Java
@EnableJpaRepositories(repositoryImplementationPostfix = "MyPostfix")
class Configuration { … }
XML
<repositories base-package="com.acme.repository" />

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

The first configuration in the preceding example tries to look up a class called com.acme.repository.CustomizedUserRepositoryImpl to act as a custom repository implementation. The second example tries to look up com.acme.repository.CustomizedUserRepositoryMyPostfix.

Resolution of Ambiguity

If multiple implementations with matching class names are found in different packages, Spring Data uses the bean names to identify which one to use.

Given the following two custom implementations for the CustomizedUserRepository shown earlier, the first implementation is used. Its bean name is customizedUserRepositoryImpl, which matches that of the fragment interface (CustomizedUserRepository) plus the postfix Impl.

Example 37. Resolution of ambiguous implementations
package com.acme.impl.one;

class CustomizedUserRepositoryImpl implements CustomizedUserRepository {

  // Your custom implementation
}

package com.acme.impl.two;

@Component("specialCustomImpl")
class CustomizedUserRepositoryImpl implements CustomizedUserRepository {

  // Your custom implementation
}

If you annotate the UserRepository interface with @Component("specialCustom"), the bean name plus Impl then matches the one defined for the repository implementation in com.acme.impl.two, and it is used instead of the first one.

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 implementation fragment 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 38. Manual wiring of custom implementations
Java
class MyClass {
  MyClass(@Qualifier("userRepositoryImpl") UserRepository userRepository) {
    …
  }
}
XML
<repositories base-package="com.acme.repository" />

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

6.6.2. Customize the Base Repository

The approach described in the preceding section requires customization of each repository interfaces when you want to customize the base repository behavior so that all repositories are affected. To instead change behavior for all repositories, you can create an implementation that extends the persistence technology-specific repository base class. This class then acts as a custom base class for the repository proxies, as shown in the following example:

Example 39. Custom repository base class
class MyRepositoryImpl<T, ID>
  extends SimpleJpaRepository<T, ID> {

  private final EntityManager entityManager;

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

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

  @Transactional
  public <S extends T> S save(S entity) {
    // 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 final step is to make the Spring Data infrastructure aware of the customized repository base class. In configuration, you can do so by using the repositoryBaseClass, as shown in the following example:

Example 40. Configuring a custom repository base class
Java
@Configuration
@EnableJpaRepositories(repositoryBaseClass = MyRepositoryImpl.class)
class ApplicationConfiguration { … }
XML
<repositories base-package="com.acme.repository"
     base-class="….MyRepositoryImpl" />

6.7. 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 41. Exposing domain events from an aggregate root
class AnAggregateRoot {

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

    @AfterDomainEventPublication (2)
    void callbackMethod() {
       // … potentially clean up domain events list
    }
}
1 The method that uses @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 @AfterDomainEventPublication. You can use it 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(…), saveAll(…), delete(…) or deleteAll(…) methods are called.

6.8. 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.

6.8.1. 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 the following example shows:

Example 42. QuerydslPredicateExecutor interface
public interface QuerydslPredicateExecutor<T> {

  Optional<T> findById(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 use the Querydsl support, extend QuerydslPredicateExecutor on your repository interface, as the following example shows:

Example 43. Querydsl integration on repositories
interface UserRepository extends CrudRepository<User, Long>, QuerydslPredicateExecutor<User> {
}

The preceding example lets you write type-safe queries by using Querydsl Predicate instances, as the following example shows:

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

userRepository.findAll(predicate);

6.8.2. 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 the following example shows:

Example 44. Enabling Spring Data web support
Java
@Configuration
@EnableWebMvc
@EnableSpringDataWebSupport
class WebConfiguration {}
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" />

The @EnableSpringDataWebSupport annotation registers a few components. We discuss those later in this section. It also detects Spring HATEOAS on the classpath and registers integration components (if present) for it as well.

Basic Web Support
Enabling Spring Data web support in XML

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

  • A Using the DomainClassConverter Class 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.

  • Jackson Modules to de-/serialize types like Point and Distance, or store specific ones, depending on the Spring Data Module used.

Using the DomainClassConverter Class

The DomainClassConverter class 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 the following example shows:

Example 45. A Spring MVC controller using domain types in method signatures
@Controller
@RequestMapping("/users")
class UserController {

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

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

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 findById(…) 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 the following example shows:

Example 46. Using Pageable as a controller method argument
@Controller
@RequestMapping("/users")
class UserController {

  private final UserRepository repository;

  UserController(UserRepository repository) {
    this.repository = repository;
  }

  @RequestMapping
  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)(,IgnoreCase). The default sort direction is case-sensitive ascending. Use multiple sort parameters if you want to switch direction or case sensitivity — for example, ?sort=firstname&sort=lastname,asc&sort=city,ignorecase.

To customize this behavior, register a bean that implements the PageableHandlerMethodArgumentResolverCustomizer interface or the SortHandlerMethodArgumentResolverCustomizer interface, respectively. Its customize() method gets called, letting you change settings, as the following example shows:

@Bean SortHandlerMethodArgumentResolverCustomizer sortCustomizer() {
    return s -> s.setPropertyDelimiter("<-->");
}

If setting the properties of an existing MethodArgumentResolver is not sufficient for your purpose, extend either SpringDataWebConfiguration or the HATEOAS-enabled equivalent, 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 following example shows the resulting method signature:

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

You have to populate thing1_page, thing2_page, and so on.

The default Pageable passed into the method is equivalent to a PageRequest.of(0, 20), but you can customize it by using the @PageableDefault annotation on the Pageable parameter.

Hypermedia Support for Page and Slice

Spring HATEOAS ships with a representation model class (PagedModel/SlicedModel) that allows enriching the content of a Page or Slice instance with the necessary Page/Slice metadata as well as links to let the clients easily navigate the pages. The conversion of a Page to a PagedModel is done by an implementation of the Spring HATEOAS RepresentationModelAssembler interface, called the PagedResourcesAssembler. Similarly Slice instances can be converted to a SlicedModel using a SlicedResourcesAssembler. The following example shows how to use a PagedResourcesAssembler as a controller method argument, as the SlicedResourcesAssembler works exactly the same:

Example 47. Using a PagedResourcesAssembler as controller method argument
@Controller
class PersonController {

  private final PersonRepository repository;

  // Constructor omitted

  @GetMapping("/people")
  HttpEntity<PagedModel<Person>> people(Pageable pageable,
    PagedResourcesAssembler assembler) {

    Page<Person> people = repository.findAll(pageable);
    return ResponseEntity.ok(assembler.toModel(people));
  }
}

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

  • The content of the Page becomes the content of the PagedModel instance.

  • The PagedModel object gets a PageMetadata instance attached, and it is populated with information from the Page and the underlying Pageable.

  • The PagedModel 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/people) 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
  }
}
The JSON envelope format shown here doesn’t follow any formally specified structure and it’s not guaranteed stable and we might change it at any time. It’s highly recommended to enable the rendering as a hypermedia-enabled, official media type, supported by Spring HATEOAS, like HAL. Those can be activated by using its @EnableHypermediaSupport annotation. Find more information in the Spring HATEOAS reference documentation.

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 you can customize that by passing a custom Link to be used as base to build the pagination links, which overloads the PagedResourcesAssembler.toModel(…) method.

Spring Data Jackson Modules

The core module, and some of the store specific ones, ship with a set of Jackson Modules for types, like org.springframework.data.geo.Distance and org.springframework.data.geo.Point, used by the Spring Data domain.
Those Modules are imported once web support is enabled and com.fasterxml.jackson.databind.ObjectMapper is available.

During initialization SpringDataJacksonModules, like the SpringDataJacksonConfiguration, get picked up by the infrastructure, so that the declared com.fasterxml.jackson.databind.Modules are made available to the Jackson ObjectMapper.

Data binding mixins for the following domain types are registered by the common infrastructure.

org.springframework.data.geo.Distance
org.springframework.data.geo.Point
org.springframework.data.geo.Box
org.springframework.data.geo.Circle
org.springframework.data.geo.Polygon

The individual module may provide additional SpringDataJacksonModules.
Please refer to the store specific section for more details.
Web Databinding Support

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

Example 48. 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();
}

You can use the type shown in the preceding example as a Spring MVC handler method argument or by using ParameterizedTypeReference on one of methods of the RestTemplate. 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 that have QueryDSL integration, you can 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 the previous examples, you can resolve a query string to the following value by using the QuerydslPredicateArgumentResolver, as follows:

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 you can 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 example 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.

You can customize those bindings through the bindings attribute of @QuerydslPredicate or by making use of Java 8 default methods and adding the QuerydslBinderCustomizer method to the repository interface, as follows:

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

  @Override
  default 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.
You can register a QuerydslBinderCustomizerDefaults bean holding default Querydsl bindings before applying specific bindings from the repository or @QuerydslPredicate.

6.8.3. Repository Populators

If you work with the Spring JDBC module, you are probably familiar with the support for populating 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 called data.json with the following content:

Example 49. 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 50. 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
    https://www.springframework.org/schema/beans/spring-beans.xsd
    http://www.springframework.org/schema/data/repository
    https://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 unmarshall a repository populator with JAXB:

Example 51. 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
    https://www.springframework.org/schema/beans/spring-beans.xsd
    http://www.springframework.org/schema/data/repository
    https://www.springframework.org/schema/data/repository/spring-repository.xsd
    http://www.springframework.org/schema/oxm
    https://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>

Reference Documentation

7. Introduction

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.

Reactive Cassandra Support explains reactive Cassandra specifics.

Cassandra Repositories introduces repository support for Cassandra.

7.1. Spring CQL and Spring Data for Apache Cassandra Modules

Spring Data for Apache Cassandra allows interaction on both the CQL and the entity level.

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

Table 2. Spring Data for Apache Cassandra (CQL Core)- 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 run 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

The core CQL support takes care of all the low-level details that can make Cassandra and CQL such a tedious API with which to develop. Using mapped entity objects allows schema generation, object mapping, and repository support.

7.1.1. Choosing an Approach for Cassandra Database Access

You can choose among several approaches to use as a 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. The following approaches work well:

  • CqlTemplate and ReactiveCqlTemplate are the classic Spring CQL approach and the most popular. This is the “lowest-level” approach. Note that components like CassandraTemplate use CqlTemplate under-the-hood.

  • 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.

  • ReactiveCassandraTemplate wraps a ReactiveCqlTemplate 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 lets you 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. Upgrading Spring Data

Instructions for how to upgrade from earlier versions of Spring Data are provided on the project wiki. Follow the links in the release notes section to find the version that you want to upgrade to.

Upgrading instructions are always the first item in the release notes. If you are more than one release behind, please make sure that you also review the release notes of the versions that you jumped.

8.1. What to Read Next

Once you’ve decided to upgrade your application, you can find detailed information regarding specific features in the rest of the document. You can find migration guides specific to major version migrations at the end of this document.

Spring Data’s documentation is specific to that version, so any information that you find in here will contain the most up-to-date changes that are in that version.

9. Cassandra Support

Spring Data support for Apache Cassandra contains a wide range of features:

  • Spring configuration support with Java-based @Configuration classes or the XML namespace.

  • The CqlTemplate helper class that increases productivity by properly handling common Cassandra data access operations.

  • The CassandraTemplate helper class that provides 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 that is extensible to support other metadata formats.

  • Java-based query, criteria, and update DSLs.

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

For most data-oriented tasks, you can use the CassandraTemplate or the Repository support, both of which use the rich object-mapping functionality. CqlTemplate is commonly used to increment counters or perform ad-hoc CRUD operations. CqlTemplate also provides callback methods that make it easy to get low-level API objects, such as com.datastax.oss.driver.api.core.CqlSession, which lets you 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 that you can map your existing knowledge onto the Spring APIs.

9.1. Getting Started

Spring Data for Apache Cassandra requires Apache Cassandra 2.1 or later and Datastax Java Driver 4.0 or later. An easy way to quickly set up and bootstrap a working environment is to create a Spring-based project in Spring Tools or use Spring Initializer.

First, you need to set up a running Apache Cassandra server. See the Apache Cassandra Quick Start Guide for an explanation on how to start 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 and press Yes when prompted. Then enter a project and a package name, such as org.spring.data.cassandra.example.

Then you can add the following dependency declaration to your pom.xml file’s dependencies section.

<dependencies>

  <dependency>
    <groupId>org.springframework.data</groupId>
    <artifactId>spring-data-cassandra</artifactId>
    <version>4.1.0-M3</version>
  </dependency>

</dependencies>

Also, you should change the version of Spring in the pom.xml file to be as follows:

<spring.framework.version>6.0.7</spring.framework.version>

If using a milestone release instead of a GA release, you also need to add the location of the Spring Milestone repository for Maven to your pom.xml file so that it is at the same level of your <dependencies/> element, as follows:

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

The repository is also browseable here.

You can also browse all Spring repositories here.

Now you can create a simple Java application that stores and reads a domain object to and from Cassandra.

To do so, first create a simple domain object class to persist, as the following example shows:

package org.springframework.data.cassandra.example;

import org.springframework.data.cassandra.core.mapping.PrimaryKey;
import org.springframework.data.cassandra.core.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;
  }

  private String getName() {
    return name;
  }

  private 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, as the following example shows:

package org.springframework.data.cassandra.example;

import java.util.UUID;

import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.springframework.data.cassandra.core.CassandraOperations;
import org.springframework.data.cassandra.core.CassandraTemplate;
import org.springframework.data.cassandra.core.query.Criteria;
import org.springframework.data.cassandra.core.query.Query;

import com.datastax.oss.driver.api.core.CqlSession;

public class CassandraApplication {

  private static final Log LOG = LogFactory.getLog(CassandraApplication.class);

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

  public static void main(String[] args) {

    CqlSession cqlSession = CqlSession.builder().withKeyspace("mykeyspace").build();

    CassandraOperations template = new CassandraTemplate(cqlSession);

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

    LOG.info(template.selectOne(Query.query(Criteria.where("id").is(jonDoe.getId())), Person.class).getId());

    template.truncate(Person.class);
    cqlSession.close();
  }

}

Even in this simple example, there are a few notable things to point out:

  • You can create an instance of CassandraTemplate with a Cassandra CqlSession.

  • You must annotate your POJO as a Cassandra @Table entity 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 raw CQL or the DataStax QueryBuilder API to construct your queries.

9.2. Examples Repository

To get a feel for how the library works, you can download and play around with several examples. .

9.3. Connecting to Cassandra with Spring

One of the first tasks when using Apache Cassandra with Spring is to create a com.datastax.oss.driver.api.core.CqlSession object by using the Spring IoC container. You can do so either by using Java-based bean metadata or by using XML-based bean metadata. These are discussed in the following sections.

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

9.3.1. Registering a Session Instance by Using Java-based Metadata

The following example shows how to use Java-based bean metadata to register an instance of a com.datastax.oss.driver.api.core.CqlSession:

Example 52. Registering a com.datastax.oss.driver.api.core.CqlSession object by using Java-based bean metadata
@Configuration
public class AppConfig {

  /*
   * Use the standard Cassandra driver API to create a com.datastax.oss.driver.api.core.CqlSession instance.
   */
  public @Bean CqlSession session() {
    return CqlSession.builder().withKeyspace("mykeyspace").build();
  }
}

This approach lets you use the standard com.datastax.oss.driver.api.core.CqlSession API that you may already know.

An alternative is to register an instance of com.datastax.oss.driver.api.core.CqlSession with the container by using Spring’s CqlSessionFactoryBean. As compared to instantiating a com.datastax.oss.driver.api.core.CqlSession 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. This hierarchy and the use of @Repository is described in Spring’s DAO support features.

The following example shows Java-based factory class usage:

Example 53. Registering a com.datastax.oss.driver.api.core.CqlSession object by using Spring’s CqlSessionFactoryBean:
@Configuration
public class FactoryBeanAppConfig {

  /*
   * Factory bean that creates the com.datastax.oss.driver.api.core.CqlSession instance
   */
  @Bean
  public CqlSessionFactoryBean session() {

    CqlSessionFactoryBean session = new CqlSessionFactoryBean();
    session.setContactPoints("localhost");
    session.setKeyspaceName("mykeyspace");

    return session;
  }
}

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

The following example shows how to register components to configure object mapping and repository support:

Example 54. Registering components to configure object mapping and repository support
@Configuration
@EnableCassandraRepositories(basePackages = { "org.springframework.data.cassandra.example" })
public class CassandraConfig {

  @Bean
  public CqlSessionFactoryBean session() {

    CqlSessionFactoryBean session = new CqlSessionFactoryBean();
    session.setContactPoints("localhost");
    session.setKeyspaceName("mykeyspace");

    return session;
  }

  @Bean
  public SessionFactoryFactoryBean sessionFactory(CqlSession session, CassandraConverter converter) {

    SessionFactoryFactoryBean sessionFactory = new SessionFactoryFactoryBean();
    sessionFactory.setSession(session);
    sessionFactory.setConverter(converter);
    sessionFactory.setSchemaAction(SchemaAction.NONE);

    return sessionFactory;
  }

  @Bean
  public CassandraMappingContext mappingContext(CqlSession cqlSession) {

    CassandraMappingContext mappingContext = new CassandraMappingContext();
    mappingContext.setUserTypeResolver(new SimpleUserTypeResolver(cqlSession));

    return mappingContext;
  }

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

  @Bean
  public CassandraOperations cassandraTemplate(SessionFactory sessionFactory, CassandraConverter converter) {
    return new CassandraTemplate(sessionFactory, converter);
  }
}

Creating configuration classes that register Spring Data for Apache Cassandra components can be an exhausting challenge, so Spring Data for Apache Cassandra comes with a pre-built configuration support class. Classes that extend from AbstractCassandraConfiguration 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 many more. AbstractCassandraConfiguration also supports you 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. The following example shows how to register beans by using AbstractCassandraConfiguration:

Example 55. Registering Spring Data for Apache Cassandra beans by using AbstractCassandraConfiguration
@Configuration
public class CassandraConfiguration 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";
  }
}

9.3.2. XML Configuration

This section describes how to configure Spring Data Cassandra with XML.

Externalizing Connection Properties

To externalize connection properties, you should first create a properties file that contains the information needed to connect to Cassandra. contactpoints and keyspace are the required fields.

The following example shows our properties file, called cassandra.properties:

cassandra.contactpoints=10.1.55.80:9042,10.1.55.81:9042
cassandra.keyspace=showcase

In the next two examples, we use Spring to load these properties into the Spring context.

Registering a Session Instance by using XML-based Metadata

While you can use Spring’s traditional <beans/> XML namespace to register an instance of com.datastax.oss.driver.api.core.CqlSession with the container, the XML can be quite verbose, because it is general purpose. XML namespaces are a better alternative to configuring commonly used objects, such as the CqlSession instance. The cassandra namespace let you create a CqlSession instance.

The following example shows how to configure the cassandra namespace:

Example 56. XML schema to configure Cassandra by 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
    https://www.springframework.org/schema/data/cassandra/spring-cassandra.xsd
    http://www.springframework.org/schema/beans
    https://www.springframework.org/schema/beans/spring-beans.xsd">

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

  <cassandra:session-factory>
    <cassandra:script
            location="classpath:/org/springframework/data/cassandra/config/schema.cql"/>
  </cassandra:session-factory>
</beans>

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 the preceding 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 includes but is 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 that mapping any existing driver configuration should be straight forward. The following example shows how to configure Spring Data components by using XML

Example 57. Configuring Spring Data components by using 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 Session -->
<cassandra:session contact-points="${cassandra.contactpoints}" keyspace-name="${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 foundation of all Spring
Data Cassandra -->
<cassandra:template id="cassandraTemplate" />

<!-- OPTIONAL: If you use Spring Data for Apache Cassandra repositories, add
your base packages to scan here -->
<cassandra:repositories base-package="org.spring.cassandra.example.repo" />

9.4. 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 schema creation.

9.4.1. Keyspaces and Lifecycle Scripts

The 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 CqlSession configuration, which has the KeyspaceSpecification and startup and shutdown CQL script execution.

Declaring a keyspace with a specification allows creating and dropping of the Keyspace. It derives CQL from the specification so that you need not write CQL yourself. The following example specifies a Cassadra keyspace by using XML:

Example 58. Specifying a Cassandra keyspace
Java
@Configuration
public class CreateKeyspaceConfiguration extends AbstractCassandraConfiguration implements BeanClassLoaderAware {

  @Override
  protected List<CreateKeyspaceSpecification> getKeyspaceCreations() {

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

    return Arrays.asList(specification);
  }

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

  // ...
}
XML
<?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
    https://www.springframework.org/schema/data/cassandra/spring-cassandra.xsd
    http://www.springframework.org/schema/beans
    https://www.springframework.org/schema/beans/spring-beans.xsd">

    <cassandra:session>

        <cassandra:keyspace action="CREATE_DROP" durable-writes="true" name="my_keyspace">
            <cassandra:replication class="NETWORK_TOPOLOGY_STRATEGY">
              <cassandra:data-center name="foo" replication-factor="1" />
              <cassandra:data-center name="bar" replication-factor="2" />
            </cassandra:replication>
      </cassandra:keyspace>

    </cassandra:session>
</beans>
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 removes the keyspace and all data from the tables in the keyspace.

9.4.2. Initializing a SessionFactory

The org.springframework.data.cassandra.core.cql.session.init package provides support for initializing an existing SessionFactory. You may sometimes need to initialize a keyspace that runs on a server somewhere.

Initializing a Keyspace

You can provide arbitrary CQL that is executed on CqlSession initialization and shutdown in the configured keyspace, as the following Java configuration example shows:

Java
@Configuration
public class KeyspacePopulatorConfiguration extends AbstractCassandraConfiguration {

  @Nullable
  @Override
  protected KeyspacePopulator keyspacePopulator() {
    return new ResourceKeyspacePopulator(new ClassPathResource("com/foo/cql/db-schema.cql"),
        new ClassPathResource("com/foo/cql/db-test-data.cql"));
  }

  @Nullable
  @Override
  protected KeyspacePopulator keyspaceCleaner() {
    return new ResourceKeyspacePopulator(scriptOf("DROP TABLE my_table;"));
  }

  // ...
}
XML
<cassandra:initialize-keyspace session-factory-ref="cassandraSessionFactory">
    <cassandra:script location="classpath:com/foo/cql/db-schema.cql"/>
    <cassandra:script location="classpath:com/foo/cql/db-test-data.cql"/>
</cassandra:initialize-keyspace>

The preceding example runs the two specified scripts against the keyspace. The first script creates a schema, and the second populates tables with a test data set. The script locations can also be patterns with wildcards in the usual Ant style used for resources in Spring (for example, classpath*:/com/foo/**/cql/*-data.cql). If you use a pattern, the scripts are run in the lexical order of their URL or filename.

The default behavior of the keyspace initializer is to unconditionally run the provided scripts. This may not always be what you want — for instance, if you run the scripts against a keyspace that already has test data in it. The likelihood of accidentally deleting data is reduced by following the common pattern (shown earlier) of creating the tables first and then inserting the data. The first step fails if the tables already exist.

However, to gain more control over the creation and deletion of existing data, the XML namespace provides a few additional options. The first is a flag to switch the initialization on and off. You can set this according to the environment (such as pulling a boolean value from system properties or from an environment bean). The following example gets a value from a system property:

<cassandra:initialize-keyspace session-factory-ref="cassandraSessionFactory"
    enabled="#{systemProperties.INITIALIZE_KEYSPACE}">    (1)
    <cassandra:script location="..."/>
</cassandra:initialize-database>
1 Get the value for enabled from a system property called INITIALIZE_KEYSPACE.

The second option to control what happens with existing data is to be more tolerant of failures. To this end, you can control the ability of the initializer to ignore certain errors in the CQL it executes from the scripts, as the following example shows:

Java
@Configuration
public class KeyspacePopulatorFailureConfiguration extends AbstractCassandraConfiguration {

  @Nullable
  @Override
  protected KeyspacePopulator keyspacePopulator() {

    ResourceKeyspacePopulator populator = new ResourceKeyspacePopulator(
        new ClassPathResource("com/foo/cql/db-schema.cql"));

    populator.setIgnoreFailedDrops(true);

    return populator;
  }

  // ...
}
XML
<cassandra:initialize-keyspace session-factory-ref="cassandraSessionFactory" ignore-failures="DROPS">
    <cassandra:script location="..."/>
</cassandra:initialize-database>

In the preceding example, we are saying that we expect that, sometimes, the scripts are run against an empty keyspace, and there are some DROP statements in the scripts that would, therefore, fail. So failed CQL DROP statements will be ignored, but other failures will cause an exception. This is useful if you don’t want tu use support DROP …​ IF EXISTS (or similar) but you want to unconditionally remove all test data before re-creating it. In that case the first script is usually a set of DROP statements, followed by a set of CREATE statements.

The ignore-failures option can be set to NONE (the default), DROPS (ignore failed drops), or ALL (ignore all failures).

Each statement should be separated by ; or a new line if the ; character is not present at all in the script. You can control that globally or script by script, as the following example shows:

Java
@Configuration
public class SessionFactoryInitializerConfiguration extends AbstractCassandraConfiguration {

  @Bean
  SessionFactoryInitializer sessionFactoryInitializer(SessionFactory sessionFactory) {

    SessionFactoryInitializer initializer = new SessionFactoryInitializer();
    initializer.setSessionFactory(sessionFactory);

    ResourceKeyspacePopulator populator1 = new ResourceKeyspacePopulator();
    populator1.setSeparator(";");
    populator1.setScripts(new ClassPathResource("com/myapp/cql/db-schema.cql"));

    ResourceKeyspacePopulator populator2 = new ResourceKeyspacePopulator();
    populator2.setSeparator("@@");
    populator2.setScripts(new ClassPathResource("classpath:com/myapp/cql/db-test-data-1.cql"), //
        new ClassPathResource("classpath:com/myapp/cql/db-test-data-2.cql"));

    initializer.setKeyspacePopulator(new CompositeKeyspacePopulator(populator1, populator2));

    return initializer;
  }

  // ...
}
XML
<cassandra:initialize-keyspace session-factory-ref="cassandraSessionFactory" separator="@@">
    <cassandra:script location="classpath:com/myapp/cql/db-schema.cql" separator=";"/>
    <cassandra:script location="classpath:com/myapp/cql/db-test-data-1.cql"/>
    <cassandra:script location="classpath:com/myapp/cql/db-test-data-2.cql"/>
</cassandra:initialize-keyspace>

In this example, the two test-data scripts use @@ as statement separator and only the db-schema.cql uses ;. This configuration specifies that the default separator is @@ and overrides that default for the db-schema script.

If you need more control than you get from the XML namespace, you can use the SessionFactoryInitializer directly and define it as a component in your application.

Initialization of Other Components that Depend on the Keyspace

A large class of applications (those that do not use the database until after the Spring context has started) can use the database initializer with no further complications. If your application is not one of those, you might need to read the rest of this section.

The database initializer depends on a SessionFactory instance and runs the scripts provided in its initialization callback (analogous to an init-method in an XML bean definition, a @PostConstruct method in a component, or the afterPropertiesSet() method in a component that implements InitializingBean). If other beans depend on the same data source and use the session factory in an initialization callback, there might be a problem because the data has not yet been initialized. A common example of this is a cache that initializes eagerly and loads data from the database on application startup.

To get around this issue, you have two options: change your cache initialization strategy to a later phase or ensure that the keyspace initializer is initialized first.

Changing your cache initialization strategy might be easy if the application is in your control and not otherwise. Some suggestions for how to implement this include:

  • Make the cache initialize lazily on first usage, which improves application startup time.

  • Have your cache or a separate component that initializes the cache implement Lifecycle or SmartLifecycle. When the application context starts, you can automatically start a SmartLifecycle by setting its autoStartup flag, and you can manually start a Lifecycle by calling ConfigurableApplicationContext.start() on the enclosing context.

  • Use a Spring ApplicationEvent or similar custom observer mechanism to trigger the cache initialization. ContextRefreshedEvent is always published by the context when it is ready for use (after all beans have been initialized), so that is often a useful hook (this is how the SmartLifecycle works by default).

Ensuring that the keyspace initializer is initialized first can also be easy. Some suggestions on how to implement this include:

  • Rely on the default behavior of the Spring BeanFactory, which is that beans are initialized in registration order. You can easily arrange that by adopting the common practice of a set of <import/> elements in XML configuration that order your application modules and ensuring that the database and database initialization are listed first.

  • Separate the SessionFactory and the business components that use it and control their startup order by putting them in separate ApplicationContext instances (for example, the parent context contains the SessionFactory, and the child context contains the business components). This structure is common in Spring web applications but can be more generally applied.

  • Use the Schema management for Tables and User-defined Types to initialize the keyspace using Spring Data Cassandra’s built-in schema generator.

9.4.3. Tables and User-defined Types

Spring Data for Apache Cassandra approaches data access with mapped entity classes that fit your data model. You can use these entity classes to create Cassandra table specifications and user type definitions.

Schema creation is tied to CqlSession initialization by SchemaAction. The following actions are supported:

  • SchemaAction.NONE: No tables or types are created or dropped. This is the default setting.

  • SchemaAction.CREATE: Create tables, indexes, and user-defined types from entities annotated with @Table and types annotated with @UserDefinedType. Existing tables or types cause an error if you tried to create the type.

  • SchemaAction.CREATE_IF_NOT_EXISTS: Like SchemaAction.CREATE but with IF NOT EXISTS applied. Existing tables or types do not cause any errors but may remain stale.

  • SchemaAction.RECREATE: Drops and recreates 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: Drops all tables and types and recreates only known tables and types.

SchemaAction.RECREATE and SchemaAction.RECREATE_DROP_UNUSED drop your tables and lose all data. RECREATE_DROP_UNUSED also drops tables and types that are not known to the application.
Enabling Tables and User-Defined Types for Schema Management

Metadata-based Mapping explains object mapping with conventions and annotations. To prevent unwanted classes from being created as a table or a type, schema management is only active for entities annotated with @Table and user-defined types annotated with @UserDefinedType. Entities are discovered by scanning the classpath. Entity scanning requires one or more base packages. Tuple-typed columns that use TupleValue do not provide any typing details. Consequently, you must annotate such column properties with @CassandraType(type = TUPLE, typeArguments = …) to specify the desired column type.

The following example shows how to specify entity base packages in XML configuration:

Example 59. Specifying entity base packages
Java
@Configuration
public class EntityBasePackagesConfiguration extends AbstractCassandraConfiguration {

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

  // ...
}
XML
<?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
    https://www.springframework.org/schema/data/cassandra/spring-cassandra.xsd
    http://www.springframework.org/schema/beans
    https://www.springframework.org/schema/beans/spring-beans.xsd">

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

9.5. CqlTemplate

The CqlTemplate class is the central class in the core CQL package. It handles the creation and release of resources. It performs the basic tasks of the core CQL workflow, such as statement creation and execution, and leaves application code to provide CQL and extract results. The CqlTemplate class executes CQL queries and update statements, performs iteration over ResultSet instances and extraction of returned parameter values. It also catches CQL exceptions and translates them to the generic, more informative, exception hierarchy defined in the org.springframework.dao package.

When you use the CqlTemplate for your code, you need only implement callback interfaces, which have a clearly defined contract. Given a Connection, the PreparedStatementCreator callback interface creates a prepared statement with the provided CQL and any necessary parameter arguments. The RowCallbackHandler interface extracts values from each row of a ResultSet.

The CqlTemplate can be used within a DAO implementation through direct instantiation with a SessionFactory reference or be configured in the Spring container and given to DAOs as a bean reference. CqlTemplate is a foundational building block for CassandraTemplate.

All CQL issued by this class is logged at the DEBUG level under the category corresponding to the fully-qualified class name of the template instance (typically CqlTemplate, but it may be different if you use a custom subclass of the CqlTemplate class).

You can control fetch size, consistency level, and retry policy defaults by configuring these parameters on the CQL API instances: CqlTemplate, AsyncCqlTemplate, and ReactiveCqlTemplate. Defaults apply if the particular query option is not set.

CqlTemplate comes in different execution model flavors. The basic CqlTemplate uses a blocking execution model. You can use AsyncCqlTemplate for asynchronous execution and synchronization with ListenableFuture instances or ReactiveCqlTemplate for reactive execution.

9.5.1. Examples of CqlTemplate Class Usage

This section provides some examples of the CqlTemplate class in action. These examples are not an exhaustive list of all of the functionality exposed by the CqlTemplate. See the Javadoc for that.

Querying (SELECT) with CqlTemplate

The following query gets the number of rows in a table:

int rowCount = cqlTemplate.queryForObject("SELECT COUNT(*) FROM t_actor", Integer.class);

The following query uses a bind variable:

int countOfActorsNamedJoe = cqlTemplate.queryForObject(
    "SELECT COUNT(*) FROM t_actor WHERE first_name = ?", Integer.class, "Joe");

The following example queries for a String:

String lastName = cqlTemplate.queryForObject(
    "SELECT last_name FROM t_actor WHERE id = ?",
    String.class, 1212L);

The following example queries and populates a single domain object:

Actor actor = cqlTemplate.queryForObject("SELECT first_name, last_name FROM t_actor WHERE id = ?",
    new RowMapper<Actor>() {
      public Actor mapRow(Row row, int rowNum) {
        Actor actor = new Actor();
        actor.setFirstName(row.getString("first_name"));
        actor.setLastName(row.getString("last_name"));
        return actor;
      }
    }, 1212L);

The following example queries and populates multiple domain objects:

List<Actor> actors = cqlTemplate.query(
    "SELECT first_name, last_name FROM t_actor",
    new RowMapper<Actor>() {
      public Actor mapRow(Row row, int rowNum) {
        Actor actor = new Actor();
        actor.setFirstName(row.getString("first_name"));
        actor.setLastName(row.getString("last_name"));
        return actor;
      }
    });

If the last two snippets of code actually existed in the same application, it would make sense to remove the duplication present in the two RowMapper anonymous inner classes and extract them out into a single class (typically a static nested class) that can then be referenced by DAO methods.

For example, it might be better to write the last code snippet as follows:

List<Actor> findAllActors() {
  return cqlTemplate.query("SELECT first_name, last_name FROM t_actor", ActorMapper.INSTANCE);
}

enum ActorMapper implements RowMapper<Actor> {

  INSTANCE;

  public Actor mapRow(Row row, int rowNum) {
    Actor actor = new Actor();
    actor.setFirstName(row.getString("first_name"));
    actor.setLastName(row.getString("last_name"));
    return actor;
  }
}
INSERT, UPDATE, and DELETE with CqlTemplate

You can use the execute(…) method to perform INSERT, UPDATE, and DELETE operations. Parameter values are usually provided as variable arguments or, alternatively, as an object array.

The following example shows how to perform an INSERT operation with CqlTemplate:

cqlTemplate.execute(
    "INSERT INTO t_actor (first_name, last_name) VALUES (?, ?)",
    "Leonor", "Watling");

The following example shows how to perform an UPDATE operation with CqlTemplate:

cqlTemplate.execute(
    "UPDATE t_actor SET last_name = ? WHERE id = ?",
    "Banjo", 5276L);

The following example shows how to perform an DELETE operation with CqlTemplate:

cqlTemplate.execute(
    "DELETE FROM t_actor WHERE id = ?",
    5276L);
Other CqlTemplate operations

You can use the execute(..) method to execute any arbitrary CQL. As a result, the method is often used for DDL statements. It is heavily overloaded with variants that take callback interfaces, bind variable arrays, and so on.

The following example shows how to create and drop a table by using different API objects that are all passed to the execute() methods:

    cqlTemplate.execute("CREATE TABLE test_table (id uuid primary key, event text)");

    DropTableSpecification dropper = DropTableSpecification.dropTable("test_table");
    String cql = DropTableCqlGenerator.toCql(dropper);

    cqlTemplate.execute(cql);

9.6. 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. Spring Data 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 to let you write portable and descriptive exception handling code without resorting to coding against and handling specific Cassandra exceptions. All of Spring’s data access exceptions are inherited from the DataAccessException class, so you can be sure that you can catch all database-related exceptions within a single try-catch block.

9.7. Controlling Cassandra Connections

Applications connect to Apache Cassandra by using CqlSession objects. A Cassandra CqlSession keeps track of multiple connections to the individual nodes and is designed to be a thread-safe, long-lived object. Usually, you can use a single CqlSession for the whole application.

Spring acquires a Cassandra CqlSession through a SessionFactory. SessionFactory is part of Spring Data for Apache Cassandra and is a generalized connection factory. It lets the container or framework hide connection handling and routing issues from the application code.

The following example shows how to configure a default SessionFactory:

Session session = … // get a Cassandra Session

CqlTemplate template = new CqlTemplate();

template.setSessionFactory(new DefaultSessionFactory(session));

CqlTemplate and other Template API implementations obtain a CqlSession for each operation. Due to their long-lived nature, sessions are not closed after invoking the desired operation. Responsibility for proper resource disposal lies with the container or framework that uses the session.

You can find various SessionFactory implementations within the org.springframework.data.cassandra.core.cql.session package.

9.8. Introduction to CassandraTemplate

The CassandraTemplate class, located in the org.springframework.data.cassandra package, is the central class in Spring’s Cassandra support and provides 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 rows in Cassandra tables.

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

The mapping between rows in Cassandra and application 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 custom converter. See the section on Cassandra conversion for more detailed information.

The CassandraTemplate class implements the CassandraOperations interface. In as much as possible, the methods on CassandraOperations are named after methods available in Cassandra to make the API familiar to developers who are already familiar with Cassandra.

For example, you can 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 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 through the CassandraOperations interface.

The default converter implementation used by CassandraTemplate is MappingCassandraConverter. While MappingCassandraConverter can use additional metadata to specify the mapping of objects to rows, it can also convert 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, are 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. See the section on exception translation for more information.

The Template API has different execution model flavors. The basic CassandraTemplate uses a blocking (imperative-synchronous) execution model. You can use AsyncCassandraTemplate for asynchronous execution and synchronization with ListenableFuture instances or ReactiveCassandraTemplate for reactive execution.

9.8.1. Instantiating CassandraTemplate

CassandraTemplate should always be configured as a Spring bean, although we show an example earlier where you can instantiate it directly. However, because we are assuming the context of making a Spring module, we assume the presence of the Spring container.

There are two ways to get a CassandraTemplate, depending on how you load you Spring ApplicationContext:

Autowiring

You can autowire a CassandraOperations into your project, as the following example shows:

@Autowired
private CassandraOperations cassandraOperations;

As with all Spring autowiring, this assumes there is only one bean of type CassandraOperations in the ApplicationContext. If you have multiple CassandraTemplate beans (which is the case if you work with multiple keyspaces in the same project), then you can use the @Qualifier annotation to designate the bean you want to autowire.

@Autowired
@Qualifier("keyspaceOneTemplateBeanId")
private CassandraOperations cassandraOperations;
Bean Lookup with ApplicationContext

You can also look up the CassandraTemplate bean from the ApplicationContext, as shown in the following example:

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

9.9. 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.

9.9.1. 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 continues to function without requiring changes. See CQL data types and “Data Mapping and Type Conversion” for the current type mapping matrix.

9.9.2. Methods for Inserting and Updating rows

CassandraTemplate has several convenient methods for saving and inserting your objects. To have more fine-grained control over the conversion process, you can register Spring Converter instances with the MappingCassandraConverter (for example, Converter<Row, Person>).

The difference between insert and update operations is that INSERT operations do not insert null values.

The simple case of using the INSERT operation is to save a POJO. In this case, the table name is determined by the simple class name (not the fully qualified class name). The table to store the object can be overridden by using mapping metadata.

When inserting or updating, the id property must be set. Apache Cassandra has no means to generate an ID.

The following example uses the save operation and retrieves its contents:

Example 60. Inserting and retrieving objects by using the CassandraTemplate
import static org.springframework.data.cassandra.core.query.Criteria.where;
import static org.springframework.data.cassandra.core.query.Query.query;

…

Person bob = new Person("Bob", 33);
cassandraTemplate.insert(bob);

Person queriedBob = cassandraTemplate.selectOneById(query(where("age").is(33)), Person.class);

You can use the following operations to insert and save:

  • void insert (Object objectToSave): Inserts the object in an Apache Cassandra table.

  • WriteResult insert (Object objectToSave, InsertOptions options): Inserts the object in an Apache Cassandra table and applies InsertOptions.

You can use the following update operations:

  • void update (Object objectToSave): Updates the object in an Apache Cassandra table.

  • WriteResult update (Object objectToSave, UpdateOptions options): Updates the object in an Apache Cassandra table and applies UpdateOptions.

You can also use the old fashioned way and write your own CQL statements, as the following example shows:

String cql = "INSERT INTO person (age, name) VALUES (39, 'Bob')";

cassandraTemplate().getCqlOperations().execute(cql);

You can also configure additional options such as TTL, consistency level, and lightweight transactions when using InsertOptions and UpdateOptions.

Which Table Are My Rows Inserted into?

You can manage the table name that is used for operating on the tables in two ways. The default table name is the simple class name changed to start with a lower-case letter. So, an instance of the com.example.Person class would be stored in the person table. The second way is to specify a table name in the @Table annotation.

Inserting, Updating, and Deleting Individual Objects in a Batch

The Cassandra protocol supports inserting a collection of rows in one operation by using a batch.

The following methods in the CassandraTemplate interface support this functionality:

  • batchOps: Creates a new CassandraBatchOperations to populate the batch.

CassandraBatchOperations

  • insert: Takes a single object, an array (var-args), or an Iterable of objects to insert.

  • update: Takes a single object, an array (var-args), or an Iterable of objects to update.

  • delete: Takes a single object, an array (var-args), or an Iterable of objects to delete.

  • withTimestamp: Applies a TTL to the batch.

  • execute: Executes the batch.

9.9.3. Updating Rows in a Table

For updates, you can select to update a number of rows.

The following example shows updating a single account object by adding a one-time $50.00 bonus to the balance with the + assignment:

Example 61. Updating rows using CasandraTemplate
import static org.springframework.data.cassandra.core.query.Criteria.where;
import org.springframework.data.cassandra.core.query.Query;
import org.springframework.data.cassandra.core.query.Update;

…

boolean applied = cassandraTemplate.update(Query.query(where("id").is("foo")),
  Update.create().increment("balance", 50.00), Account.class);

In addition to the Query discussed earlier, we provide the update definition by using an Update object. The Update class has methods that match the update assignments available for Apache Cassandra.

Most methods return the Update object to provide a fluent API for code styling purposes.

Methods for Executing Updates for Rows

The update method can update rows, as follows:

  • boolean update (Query query, Update update, Class<?> entityClass): Updates a selection of objects in the Apache Cassandra table.

Methods for the Update class

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

The Update class has the following methods:

  • AddToBuilder addTo (String columnName) AddToBuilder entry-point:

    • Update prepend(Object value): Prepends a collection value to the existing collection by using the + update assignment.

    • Update prependAll(Object…​ values): Prepends all collection values to the existing collection by using the + update assignment.

    • Update append(Object value): Appends a collection value to the existing collection by using the + update assignment.

    • Update append(Object…​ values): Appends all collection values to the existing collection by using the + update assignment.

    • Update entry(Object key, Object value): Adds a map entry by using the + update assignment.

    • Update addAll(Map<? extends Object, ? extends Object> map): Adds all map entries to the map by using the + update assignment.

  • Update remove (String columnName, Object value): Removes the value from the collection by using the - update assignment.

  • Update clear (String columnName): Clears the collection.

  • Update increment (String columnName, Number delta): Updates by using the + update assignment.

  • Update decrement (String columnName, Number delta): Updates by using the - update assignment.

  • Update set (String columnName, Object value): Updates by using the = update assignment.

  • SetBuilder set (String columnName) SetBuilder entry-point:

    • Update atIndex(int index).to(Object value): Sets a collection at the given index to a value using the = update assignment.

    • Update atKey(String object).to(Object value): Sets a map entry at the given key to a value the = update assignment.

The following listing shows a few update examples:

// UPDATE … SET key = 'Spring Data';
Update.update("key", "Spring Data")

// UPDATE … SET key[5] = 'Spring Data';
Update.empty().set("key").atIndex(5).to("Spring Data");

// UPDATE … SET key = key + ['Spring', 'DATA'];
Update.empty().addTo("key").appendAll("Spring", "Data");

Note that Update is immutable once created. Invoking methods creates new immutable (intermediate) Update objects.

9.9.4. Methods for Removing Rows

You can use the following overloaded methods to remove an object from the database:

  • boolean delete (Query query, Class<?> entityClass): Deletes the objects selected by Query.

  • T delete (T entity): Deletes the given object.

  • T delete (T entity, QueryOptions queryOptions): Deletes the given object applying QueryOptions.

  • boolean deleteById (Object id, Class<?> entityClass): Deletes the object using the given Id.

9.9.5. Optimistic Locking

The @Version annotation provides syntax similar to that of JPA in the context of Cassandra and makes sure updates are only applied to rows with a matching version. Optimistic Locking leverages Cassandra’s lightweight transactions to conditionally insert, update and delete rows. Therefore, INSERT statements are executed with the IF NOT EXISTS condition. For updates and deletes, the actual value of the version property is added to the UPDATE condition in such a way that the modification does not have any effect if another operation altered the row in the meantime. In that case, an OptimisticLockingFailureException is thrown. The following example shows these features:

@Table
class Person {

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

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

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

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

template.save(tmp); // throws OptimisticLockingFailureException                       (4)
1 Intially insert document. version is set to 0.
2 Load the just inserted document. version is still 0.
3 Update the document with version = 0. Set the lastname and bump version to 1.
4 Try to update the previously loaded document that still has version = 0. The operation fails with an OptimisticLockingFailureException, as the current version is 1.
Optimistic Locking is only supported with single-entity operations and not for batch operations.

9.10. Querying Rows

You can express your queries by using the Query and Criteria classes, which have method names that reflect the native Cassandra predicate operator names, such as lt, lte, is, and others.

The Query and Criteria classes follow a fluent API style so that you can easily chain together multiple method criteria and queries while having easy-to-understand code. Static imports are used in Java when creating Query and Criteria instances to improve readability.

9.10.1. Querying Rows in a Table

In earlier sections, we saw how to retrieve a single object by using the selectOneById method on CassandraTemplate. Doing so returns a single domain object. We can also query for a collection of rows to be returned as a list of domain objects. Assuming we have a number of Person objects with name and age values stored as rows in a table and that each person has an account balance, we can now run a query by using the following code:

Example 62. Querying for rows using CassandraTemplate
import static org.springframework.data.cassandra.core.query.Criteria.where;
import static org.springframework.data.cassandra.core.query.Query.query;

…

List<Person> result = cassandraTemplate.select(query(where("age").is(50))
  .and(where("balance").gt(1000.00d)).withAllowFiltering(), Person.class);

The select, selectOne, and stream methods take a Query object as a parameter. This object defines the criteria and options used to perform the query. The criteria is specified by using a Criteria object that has a static factory method named where that instantiates a new Criteria object. We recommend using a static import for org.springframework.data.cassandra.core.query.Criteria.where and Query.query, to make the query more readable.

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

Methods for the Criteria class

  • CriteriaDefinition gt (Object value): Creates a criterion by using the > operator.

  • CriteriaDefinition gte (Object value): Creates a criterion by using the >= operator.

  • CriteriaDefinition in (Object…​ values): Creates a criterion by using the IN operator for a varargs argument.

  • CriteriaDefinition in (Collection<?> collection): Creates a criterion by using the IN operator using a collection.

  • CriteriaDefinition is (Object value): Creates a criterion by using field matching (column = value).

  • CriteriaDefinition lt (Object value): Creates a criterion by using the < operator.

  • CriteriaDefinition lte (Object value): Creates a criterion by using the ⇐ operator.

  • CriteriaDefinition like (Object value): Creates a criterion by using the LIKE operator.

  • CriteriaDefinition contains (Object value): Creates a criterion by using the CONTAINS operator.

  • CriteriaDefinition containsKey (Object key): Creates a criterion by using the CONTAINS KEY operator.

Criteria is immutable once created.

Methods for the Query class

The Query class has some additional methods that you can use to provide options for the query:

  • Query by (CriteriaDefinition…​ criteria): Used to create a Query object.

  • Query and (CriteriaDefinition criteria): Used to add additional criteria to the query.

  • Query columns (Columns columns): Used to define columns to be included in the query results.

  • Query limit (long limit): Used to limit the size of the returned results to the provided limit (used for paging).

  • Query pageRequest (Pageable pageRequest): Used to associate Sort, PagingState, and fetchSize with the query (used for paging).

  • Query pagingState (ByteBuffer pagingState): Used to associate a ByteBuffer with the query (used for paging).

  • Query queryOptions (QueryOptions queryOptions): Used to associate QueryOptions with the query.

  • Query sort (Sort sort): Used to provide a sort definition for the results.

  • Query withAllowFiltering (): Used to render ALLOW FILTERING queries.

Query is immutable once created. Invoking methods creates new immutable (intermediate) Query objects.

9.10.2. Methods for Querying for Rows

The Query class has the following methods that return rows:

  • List<T> select (Query query, Class<T> entityClass): Query for a list of objects of type T from the table.

  • T selectOne (Query query, Class<T> entityClass): Query for a single object of type T from the table.

  • Slice<T> slice (Query query, Class<T> entityClass): Starts or continues paging by querying for a Slice of objects of type T from the table.

  • Stream<T> stream (Query query, Class<T> entityClass): Query for a stream of objects of type T from the table.

  • List<T> select (String cql, Class<T> entityClass): Ad-hoc query for a list of objects of type T from the table by providing a CQL statement.

  • T selectOne (String cql, Class<T> entityClass): Ad-hoc query for a single object of type T from the table by providing a CQL statement.

  • Stream<T> stream (String cql, Class<T> entityClass): Ad-hoc query for a stream of objects of type T from the table by providing a CQL statement.

The query methods must specify the target type T that is returned.

9.10.3. Fluent Template API

The CassandraOperations interface is one of the central components when it comes to more low-level interaction with Apache Cassandra. It offers a wide range of methods. You can find multiple overloads for every method. Most of them cover optional (nullable) parts of the API.

FluentCassandraOperations provide a more narrow interface for common methods of CassandraOperations providing a more readable, fluent API. The entry points (query(…), insert(…), update(…), and delete(…)) follow a natural naming scheme based on the operation to execute. Moving on from the entry point, the API is designed to offer only context-dependent methods that guide the developer towards a terminating method that invokes the actual CassandraOperation. The following example shows the fluent API:

List<SWCharacter> all = ops.query(SWCharacter.class)
  .inTable("star_wars")                        (1)
  .all();
1 Skip this step if SWCharacter defines the table name with @Table or if using the class name as the table name is not a problem.

If a table in Cassandra holds entities of different types, such as a Jedi within a Table of SWCharacters, you can use different types to map the query result. You can use as(Class<?> targetType) to map results to a different target type, while query(Class<?> entityType) still applies to the query and table name. The following example uses the query and as methods:

List<Jedi> all = ops.query(SWCharacter.class)    (1)
  .as(Jedi.class)                                (2)
  .matching(query(where("jedi").is(true)))
  .all();
1 The query fields are mapped against the SWCharacter type.
2 Resulting rows are mapped into Jedi.
You can directly apply Projections to resulting documents by providing only the interface type through as(Class<?>).

The terminating methods (first(), one(), all(), and stream()) handle switching between retrieving a single entity and retrieving multiple entities as List or Stream and similar operations.

The new fluent template API methods (that is, query(..), insert(..), update(..), and delete(..)) use effectively thread-safe supporting objects to compose the CQL statement. However, it comes at the added cost of additional young-gen JVM heap overhead, since the design is based on final fields for the various CQL statement components and construction on mutation. You should be careful when possibly inserting or deleting a large number of objects (such as inside of a loop, for instance).

9.11. Prepared Statements

CQL statements that are executed multiple times can be prepared and stored in a PreparedStatement object to improve query performance. Both, the driver and Cassandra maintain a mapping of PreparedStatement queries to their metadata. You can use prepared statements through the following abstractions:

  • CqlTemplate through the choice of API

  • CassandraTemplate by enabling prepared statements

  • Cassandra repositories as they are built on CassandraTemplate

9.11.1. Using CqlTemplate

The CqlTemplate class (and its asynchronous and reactive variants) offers various methods accepting static CQL, Statement objects and PreparedStatementCreator. Methods accepting static CQL without additional arguments typically run the CQL statement as-is without further processing. Methods accepting static CQL in combination with an arguments array (such as execute(String cql, Object…​ args) and queryForRows(String cql, Object…​ args)) use prepared statements. Internally, these methods create a PreparedStatementCreator and PreparedStatementBinder objects to prepare the statement and later on to bind values to the statement to run it. Spring Data Cassandra generally uses index-based parameter bindings for prepared statements.

Since Cassandra Driver version 4, prepared statements are cached on the driver level which removes the need to keep track of prepared statements in the application.

The following example shows how to issue a query with a parametrized prepared statement:

String lastName = cqlTemplate.queryForObject(
    "SELECT last_name FROM t_actor WHERE id = ?",
    String.class, 1212L);

In cases where you require more control over statement preparation and parameter binding (for example, using named binding parameters), you can fully control prepared statement creation and parameter binding by calling query methods with PreparedStatementCreator and PreparedStatementBinder arguments:

List<String> lastNames = cqlTemplate.query(
    session -> session.prepare("SELECT last_name FROM t_actor WHERE id = ?"),
    ps -> ps.bind(1212L),
    (row, rowNum) -> row.getString(0));

Spring Data Cassandra ships with classes supporting that pattern in the cql package:

  • SimplePreparedStatementCreator - utility class to create a prepared statement.

  • ArgumentPreparedStatementBinder - utility class to bind arguments to a prepared statement.

9.11.2. Using CassandraTemplate

The CassandraTemplate class is built on top of CqlTemplate to provide a higher level of abstraction. The use of prepared statements can be controlled directly on CassandraTemplate (and its asynchronous and reactive variants) by calling setUsePreparedStatements(false) respective setUsePreparedStatements(true). Note that the use of prepared statements by CassandraTemplate is enabled by default.

The following example shows the use of methods that generate and that accept CQL:

template.setUsePreparedStatements(true);

Actor actorByQuery = template.selectOne(query(where("id").is(42)), Actor.class);

Actor actorByStatement = template.selectOne(
    SimpleStatement.newInstance("SELECT id, name FROM actor WHERE id = ?", 42),
    Actor.class);

Calling entity-bound methods such as select(Query, Class<T>) or update(Query, Update, Class<T>) build CQL statements themselves to perform the intended operations. Some CassandraTemplate methods (such as select(Statement<?>, Class<T>)) also accepts CQL Statement objects as part of their API.

It’s possible to participate in prepared statements when calling methods accepting a Statement with a SimpleStatement object. The template API extracts the query string and parameters (positional and named parameters) and uses these to prepare, bind, and run the statement. Non-SimpleStatement objects cannot be used with prepared statements.

9.11.3. Caching Prepared Statements

Since Cassandra driver 4.0, prepared statements are cached by the CqlSession cache so it is okay to prepare the same string twice. Previous versions required caching of prepared statements outside of the driver. See also the Driver documentation on Prepared Statements for further reference.

9.12. Observability

Getting insights from an application component about its operations, timing and relation to application code is crucial to understand latency. Spring Data Cassandra ships with a Micrometer instrumentation through the Cassandra driver to collect observations during Cassandra interaction. Once the integration is set up, Micrometer will create meters and spans (for distributed tracing) for each Cassandra statement.

To enable the instrumentation, apply the following configuration to your application:

@Configuration
class ObservabilityConfiguration {

  @Bean
  public ObservableCqlSessionFactoryBean observableCqlSession(CqlSessionBuilder builder,
                                                              ObservationRegistry registry) {
    return new ObservableCqlSessionFactoryBean(builder, registry); (1)
  }

  @Bean
  public ObservableReactiveSessionFactoryBean observableReactiveSession(CqlSession session,
                                                              ObservationRegistry registry) {
    return new ObservableReactiveSessionFactoryBean(session, registry); (2)
  }
}
1 Wraps the CQL session object to observe Cassandra statement execution. Also, registers ObservationRequestTracker.INSTANCE with the CqlSessionBuilder.
2 Wraps a CQL session object to observe reactive Cassandra statement execution.

9.12.1. Observability - Conventions

Below you can find a list of all GlobalObservabilityConventions and ObservabilityConventions declared by this project.

Table 3. ObservationConvention implementations

ObservationConvention Class Name

Applicable ObservationContext Class Name

org.springframework.data.cassandra.observability.DefaultCassandraObservationConvention

n/a

9.12.2. Observability - Metrics

Below you can find a list of all metrics declared by this project.

Cassandra Query Observation

Create an io.micrometer.observation.Observation for Cassandra-based queries.

Metric name spring.data.cassandra.query. Type timer and base unit seconds.

Fully qualified name of the enclosing class org.springframework.data.cassandra.observability.CassandraObservation.

Table 4. Low cardinality Keys

Name

Description

db.cassandra.coordinator.dc

db.cassandra.coordinator.id

db.name

Name of the Cassandra keyspace.

db.operation

The database operation.

db.system

Database system.

net.peer.name

Name of the database host.

net.peer.port

Logical remote port number.

net.sock.peer.addr

Cassandra peer address.

net.sock.peer.port

Cassandra peer port.

net.transport

Network transport.

spring.data.cassandra.methodName

The method name

spring.data.cassandra.sessionName

Cassandra session
Table 5. High cardinality Keys

Name

Description

db.cassandra.consistency_level

db.cassandra.idempotence

db.cassandra.page_size

db.statement

A key-value containing Cassandra CQL.

spring.data.cassandra.node[%s].error

A tag containing error that occurred for the given node. (since the name contains %s the final value will be resolved at runtime)

9.12.3. Observability - Spans

Below you can find a list of all spans declared by this project.

Cassandra Query Observation Span

Create an io.micrometer.observation.Observation for Cassandra-based queries.

Span name spring.data.cassandra.query.

Fully qualified name of the enclosing class org.springframework.data.cassandra.observability.CassandraObservation.

Table 6. Tag Keys

Name

Description

db.cassandra.consistency_level

db.cassandra.coordinator.dc

db.cassandra.coordinator.id

db.cassandra.idempotence

db.cassandra.page_size

db.name

Name of the Cassandra keyspace.

db.operation

The database operation.

db.statement

A key-value containing Cassandra CQL.

db.system

Database system.

net.peer.name

Name of the database host.

net.peer.port

Logical remote port number.

net.sock.peer.addr

Cassandra peer address.

net.sock.peer.port

Cassandra peer port.

net.transport

Network transport.

spring.data.cassandra.methodName

The method name

spring.data.cassandra.node[%s].error

A tag containing error that occurred for the given node. (since the name contains %s the final value will be resolved at runtime)

spring.data.cassandra.sessionName

Cassandra session

See also OpenTelemetry Semantic Conventions for further reference.

10. Reactive Cassandra Support

The reactive Cassandra support contains a wide range of features:

  • Spring configuration support using Java-based @Configuration classes.

  • ReactiveCqlTemplate helper class that increases productivity by properly handling common Cassandra data access operations.

  • ReactiveCassandraTemplate helper class that increases productivity by using ReactiveCassandraOperations in a reactive manner. It includes integrated object mapping between tables and POJOs.

  • Exception translation into Spring’s portable Data Access Exception Hierarchy.

  • Feature rich object mapping integrated with Spring’s Conversion Service.

  • Java-based Query, Criteria, and Update DSLs.

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

For most data-oriented tasks, you can use the ReactiveCassandraTemplate or the repository support, which use the rich object mapping functionality. ReactiveCqlTemplate is commonly used to increment counters or perform ad-hoc CRUD operations. ReactiveCqlTemplate also provides callback methods that make it easy to get low-level API objects, such as com.datastax.oss.driver.api.core.CqlSession, which let you 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 immediately familiar and so that you can map your existing knowledge onto the Spring APIs.

10.1. Getting Started

Spring Data for Apache Cassandra requires Apache Cassandra 2.1 or later and Datastax Java Driver 4.0 or later. An easy way to quickly set up and bootstrap a working environment is to create a Spring-based project in Spring Tools or use Spring Initializer.

First, you need to set up a running Apache Cassandra server. See the Apache Cassandra Quick Start Guide for an explanation on how to start Apache Cassandra. Once installed, starting Cassandra is typically a matter of running 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 and press Yes when prompted. Then enter a project and a package name, such as org.spring.data.cassandra.example.

Then you can add the following dependency declaration to your pom.xml file’s dependencies section.

<dependencies>

  <dependency>
    <groupId>org.springframework.data</groupId>
    <artifactId>spring-data-cassandra</artifactId>
    <version>4.1.0-M3</version>
  </dependency>

</dependencies>

Also, you should change the version of Spring in the pom.xml file to be as follows:

<spring.framework.version>6.0.7</spring.framework.version>

If using a milestone release instead of a GA release, you also need to add the location of the Spring Milestone repository for Maven to your pom.xml file so that it is at the same level of your <dependencies/> element, as follows:

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

The repository is also browseable here.

You can also browse all Spring repositories here.

Now you can create a simple Java application that stores and reads a domain object to and from Cassandra.

To do so, first create a simple domain object class to persist, as the following example shows:

package org.springframework.data.cassandra.example;

import org.springframework.data.cassandra.core.mapping.PrimaryKey;
import org.springframework.data.cassandra.core.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;
  }

  private String getName() {
    return name;
  }

  private 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, as the following example shows:

package org.springframework.data.cassandra.example;

import reactor.core.publisher.Mono;

import java.util.UUID;

import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.springframework.data.cassandra.core.ReactiveCassandraOperations;
import org.springframework.data.cassandra.core.ReactiveCassandraTemplate;
import org.springframework.data.cassandra.core.cql.session.DefaultBridgedReactiveSession;
import org.springframework.data.cassandra.core.query.Criteria;
import org.springframework.data.cassandra.core.query.Query;

import com.datastax.oss.driver.api.core.CqlSession;

public class ReactiveCassandraApplication {

  private static final Log LOG = LogFactory.getLog(ReactiveCassandraApplication.class);

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

  public static void main(String[] args) {

    CqlSession cqlSession = CqlSession.builder().withKeyspace("mykeyspace").build();

     ReactiveCassandraOperations template = new ReactiveCassandraTemplate(new DefaultBridgedReactiveSession(cqlSession));

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

    jonDoe.flatMap(it -> template.selectOne(Query.query(Criteria.where("id").is(it.getId())), Person.class))
        .doOnNext(it -> LOG.info(it.toString()))
        .then(template.truncate(Person.class))
        .block();

    cqlSession.close();
  }

}

Even in this simple example, there are a few notable things to point out:

  • A fully synchronous flow does not benefit from a reactive infrastructure, because a reactive programming model requires synchronization.

  • You can create an instance of ReactiveCassandraTemplate with a Cassandra CqlSession.

  • You must annotate your POJO as a Cassandra @Table and annotate the @PrimaryKey. Optionally, you can override these mapping names to match your Cassandra database table and column names.

  • You can either use raw CQL or the DataStax QueryBuilder API to construct your queries.

10.2. Examples Repository

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

10.3. Connecting to Cassandra with Spring

One of the first tasks when using Apache Cassandra with Spring is to create a com.datastax.oss.driver.api.core.CqlSession object by using the Spring IoC container. You can do so either by using Java-based bean metadata or by using 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.

10.3.1. Registering a Session instance using Java-based metadata

You can configure Reactive Cassandra support by using Java Configuration classes. Reactive Cassandra support adapts a CqlSession to provide a reactive processing model on top of an asynchronous driver.

A reactive CqlSession is configured similarly to an imperative CqlSession. We provide supporting configuration classes that come with predefined defaults and require only environment-specific information to configure Spring Data for Apache Cassandra. The base class for reactive support is AbstractReactiveCassandraConfiguration. This configuration class extends the imperative AbstractCassandraConfiguration, so the reactive support also configures the imperative API support. The following example shows how to register Apache Cassandra beans in a configuration class: ReactiveAppCassandraConfiguration .Registering Spring Data for Apache Cassandra beans using AbstractReactiveCassandraConfiguration

@Configuration
public class ReactiveCassandraConfiguration extends AbstractReactiveCassandraConfiguration {

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

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

The configuration class in the preceding example is schema-management-enabled to create CQL objects during startup. See Schema Management for further details.

10.4. ReactiveCqlTemplate

The ReactiveCqlTemplate class is the central class in the core CQL package. It handles the creation and release of resources. It performs the basic tasks of the core CQL workflow, such as creating and running statements, leaving application code to provide CQL and extract results. The ReactiveCqlTemplate class runs CQL queries and update statements and performs iteration over ResultSet instances and extraction of returned parameter values. It also catches CQL exceptions and translates them into the generic, more informative, exception hierarchy defined in the org.springframework.dao package.

When you use the ReactiveCqlTemplate in your code, you need only implement callback interfaces, which have a clearly defined contract. Given a Connection, the ReactivePreparedStatementCreator callback interface creates a prepared statement with the provided CQL and any necessary parameter arguments. The RowCallbackHandler interface extracts values from each row of a ReactiveResultSet.

The ReactiveCqlTemplate can be used within a DAO implementation through direct instantiation with a ReactiveSessionFactory reference or be configured in the Spring container and given to DAOs as a bean reference. ReactiveCqlTemplate is a foundational building block for ReactiveCassandraTemplate.

All CQL issued by this class is logged at the DEBUG level under the category corresponding to the fully-qualified class name of the template instance (typically ReactiveCqlTemplate, but it may be different if you use a custom subclass of the ReactiveCqlTemplate class).

10.4.1. Examples of ReactiveCqlTemplate Class Usage

This section provides some examples of ReactiveCqlTemplate class usage. These examples are not an exhaustive list of all of the functionality exposed by the ReactiveCqlTemplate. See the attendant Javadocs for that.

Querying (SELECT) with ReactiveCqlTemplate

The following query gets the number of rows in a relation:

Mono<Integer> rowCount = reactiveCqlTemplate.queryForObject("SELECT COUNT(*) FROM t_actor", Integer.class);

The following query uses a bind variable:

Mono<Integer> countOfActorsNamedJoe = reactiveCqlTemplate.queryForObject(
  "SELECT COUNT(*) FROM t_actor WHERE first_name = ?", Integer.class, "Joe");

The following example queries for a String:

Mono<String> lastName = reactiveCqlTemplate.queryForObject(
  "SELECT last_name FROM t_actor WHERE id = ?",
  String.class, 1212L);

The following example queries and populates a single domain object:

Mono<Actor> actor = reactiveCqlTemplate.queryForObject(
  "SELECT first_name, last_name FROM t_actor WHERE id = ?",
  new RowMapper<Actor>() {
    public Actor mapRow(Row row, int rowNum) {
      Actor actor = new Actor();
      actor.setFirstName(row.getString("first_name"));
      actor.setLastName(row.getString("last_name"));
      return actor;
    }},
  1212L);

The following example queries and populates a number of domain objects:

Flux<Actor> actors = reactiveCqlTemplate.query(
"SELECT first_name, last_name FROM t_actor",
  new RowMapper<Actor>() {
    public Actor mapRow(Row row, int rowNum) {
      Actor actor = new Actor();
      actor.setFirstName(row.getString("first_name"));
      actor.setLastName(row.getString("last_name"));
      return actor;
    }
});

If the last two snippets of code actually existed in the same application, it would make sense to remove the duplication present in the two RowMapper anonymous inner classes and extract them into a single class (typically a static nested class) that can then be referenced by DAO methods as needed.

For example, it might be better to write the last code snippet as follows:

Flux<Actor> findAllActors() {
  return reactiveCqlTemplate.query("SELECT first_name, last_name FROM t_actor", ActorMapper.INSTANCE);
}

enum ActorMapper implements RowMapper<Actor> {

  INSTANCE;

  public Actor mapRow(Row row, int rowNum) {
    Actor actor = new Actor();
    actor.setFirstName(row.getString("first_name"));
    actor.setLastName(row.getString("last_name"));
    return actor;
  }
}
INSERT, UPDATE, and DELETE with ReactiveCqlTemplate

You can use the execute(…) method to perform INSERT, UPDATE, and DELETE operations. Parameter values are usually provided as variable arguments or, alternatively, as an object array.

The following example shows how to perform an INSERT operation with ReactiveCqlTemplate:

Mono<Boolean> applied = reactiveCqlTemplate.execute(
  "INSERT INTO t_actor (first_name, last_name) VALUES (?, ?)",
  "Leonor", "Watling");

The following example shows how to perform an UPDATE operation with ReactiveCqlTemplate:

Mono<Boolean> applied = reactiveCqlTemplate.execute(
  "UPDATE t_actor SET last_name = ? WHERE id = ?",
  "Banjo", 5276L);

The following example shows how to perform an DELETE operation with ReactiveCqlTemplate:

Mono<Boolean> applied = reactiveCqlTemplate.execute(
  "DELETE FROM actor WHERE id = ?",
  actorId);

10.5. 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. Spring Data 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 to let you write portable and descriptive exception handling code without resorting to coding against and handling specific Cassandra exceptions. All of Spring’s data access exceptions are inherited from the DataAccessException class, so you can be sure that you can catch all database-related exceptions within a single try-catch block.

ReactiveCqlTemplate and ReactiveCassandraTemplate propagate exceptions as early as possible. Exceptions that occur during the processing of the reactive sequence are emitted as error signals.

10.6. Introduction to ReactiveCassandraTemplate

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

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

The mapping between rows in a Cassandra table 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 custom converter. See “Mapping” for more detailed information.

The ReactiveCassandraTemplate class implements the ReactiveCassandraOperations interface. As often as possible, the methods names ReactiveCassandraOperations match names in Cassandra to make the API familiar to developers who are familiar with Cassandra.

For example, you can 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 ReactiveCassandraOperations. A major difference between the two APIs is that ReactiveCassandraOperations can be passed domain objects instead of CQL and query objects.

The preferred way to reference operations on a ReactiveCassandraTemplate instance is through its interface, ReactiveCassandraOperations.

The default converter implementation for ReactiveCassandraTemplate is MappingCassandraConverter. While the MappingCassandraConverter can make use of additional metadata to specify the mapping of objects to rows, it can also convert objects that contain no additional metadata by using conventions for the mapping of fields and table names. These conventions, as well as the use of mapping annotations, are explained in “Mapping”.

Another central feature of CassandraTemplate is exception translation. Exceptions thrown by the Cassandra Java driver are translated into Spring’s portable Data Access Exception hierarchy. See “Exception Translation” for more information.

10.6.1. Instantiating ReactiveCassandraTemplate

ReactiveCassandraTemplate should always be configured as a Spring bean, although an earlier example showed how to instantiate it directly. However, this section assumes that the template is used in a Spring module, so it also assumes that the Spring container is being used.

There are two ways to get a ReactiveCassandraTemplate, depending on how you load you Spring ApplicationContext:

Autowiring

You can autowire a ReactiveCassandraTemplate into your project, as the following example shows:

@Autowired
private ReactiveCassandraOperations reactiveCassandraOperations;

Like all Spring autowiring, this assumes there is only one bean of type ReactiveCassandraOperations in the ApplicationContext. If you have multiple ReactiveCassandraTemplate beans (which can be the case if you are working with multiple keyspaces in the same project), then you can use the @Qualifier annotation to designate which bean you want to autowire.

@Autowired
@Qualifier("keyspaceTwoTemplateBeanId")
private ReactiveCassandraOperations reactiveCassandraOperations;
Bean Lookup with ApplicationContext

You can also look up the ReactiveCassandraTemplate bean from the ApplicationContext, as shown in the following example:

ReactiveCassandraOperations reactiveCassandraOperations = applicationContext.getBean("reactiveCassandraOperations", ReactiveCassandraOperations.class);

10.7. Saving, Updating, and Removing Rows

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

10.7.1. Methods for Inserting and Updating rows

CassandraTemplate has several convenient methods for saving and inserting your objects. To have more fine-grained control over the conversion process, you can register Spring Converter instances with the MappingCassandraConverter (for example, Converter<Row, Person>).

The difference between insert and update operations is that INSERT operations do not insert null values.

The simple case of using the INSERT operation is to save a POJO. In this case, the table name is determined by the simple class name (not the fully qualified class name). The table to store the object can be overridden by using mapping metadata.

When inserting or updating, the id property must be set. Apache Cassandra has no means to generate an ID.

The following example uses the save operation and retrieves its contents:

Example 63. Inserting and retrieving objects by using the CassandraTemplate
import static org.springframework.data.cassandra.core.query.Criteria.where;
import static org.springframework.data.cassandra.core.query.Query.query;

…

Person bob = new Person("Bob", 33);
cassandraTemplate.insert(bob);

Mono<Person> queriedBob = reactiveCassandraTemplate.selectOneById(query(where("age").is(33)), Person.class);

You can use the following operations to insert and save:

  • void insert (Object objectToSave): Inserts the object in an Apache Cassandra table.

  • WriteResult insert (Object objectToSave, InsertOptions options): Inserts the object in an Apache Cassandra table and applies InsertOptions.

You can use the following update operations:

  • void update (Object objectToSave): Updates the object in an Apache Cassandra table.

  • WriteResult update (Object objectToSave, UpdateOptions options): Updates the object in an Apache Cassandra table and applies UpdateOptions.

You can also use the old fashioned way and write your own CQL statements, as the following example shows:

String cql = "INSERT INTO person (age, name) VALUES (39, 'Bob')";

Mono<Boolean> applied = reactiveCassandraTemplate.getReactiveCqlOperations().execute(cql);

You can also configure additional options such as TTL, consistency level, and lightweight transactions when using InsertOptions and UpdateOptions.

Which Table Are My Rows Inserted into?

You can manage the table name that is used for operating on the tables in two ways. The default table name is the simple class name changed to start with a lower-case letter. So, an instance of the com.example.Person class would be stored in the person table. The second way is to specify a table name in the @Table annotation.

10.7.2. Updating Rows in a Table

For updates, you can select to update a number of rows.

The following example shows updating a single account object by adding a one-time $50.00 bonus to the balance with the + assignment:

Example 64. Updating rows using ReactiveCasandraTemplate
import static org.springframework.data.cassandra.core.query.Criteria.where;
import org.springframework.data.cassandra.core.query.Query;
import org.springframework.data.cassandra.core.query.Update;

…

Mono<Boolean> wasApplied = reactiveCassandraTemplate.update(Query.query(where("id").is("foo")),
  Update.create().increment("balance", 50.00), Account.class);

In addition to the Query discussed earlier, we provide the update definition by using an Update object. The Update class has methods that match the update assignments available for Apache Cassandra.

Most methods return the Update object to provide a fluent API for code styling purposes.

For more detail, see “Methods for Executing Updates for Rows”.

11. Cassandra Repositories

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”. Cassandra repositories use CassandraTemplate and its wired CqlTemplate as infrastructure beans. You should understand the basic concepts explained there before proceeding.

11.1. Usage

To access domain entities stored in Apache Cassandra, you can use Spring Data’s sophisticated repository support, which significantly eases implementing DAOs. To do so, create an interface for your repository, as the following example shows:

Example 65. Sample Person entity
@Table
public class Person {

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

  // … getters and setters omitted
}

Note that the entity has a property named id of type String. The default serialization mechanism used in CassandraTemplate (which backs the repository support) regards properties named id as being the row ID.

The following example shows a repository definition to persist Person entities:

Example 66. Basic repository interface to persist Person entities
public interface PersonRepository extends CrudRepository<Person, String> {

  // additional custom finder methods go here
}

Right now, the interface in the preceding example serves only typing purposes, but we add additional methods to it later.

Next, in your Spring configuration, add the following (if you use Java for configuration):

If you want to use Java configuration, use the @EnableCassandraRepositories annotation. The annotation carries the same attributes as the namespace element. If no base package is configured, the infrastructure scans the package of the annotated configuration class. The following example shows how to use the @EnableCassandraRepositories annotation:

Example 67. Configuration for repositories
Java
@Configuration
@EnableCassandraRepositories
class ApplicationConfig extends AbstractCassandraConfiguration {

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

  public String[] getEntityBasePackages() {
    return new String[] { "com.oreilly.springdata.cassandra" };
  }
}
XML
<?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
    https://www.springframework.org/schema/data/cassandra/spring-cassandra.xsd
    http://www.springframework.org/schema/beans
    https://www.springframework.org/schema/beans/spring-beans.xsd">

    <cassandra:session port="9042" 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 causes the base packages to be scanned for interfaces that extend CrudRepository and create Spring beans for each one found. By default, the repositories are wired with a CassandraTemplate Spring bean called cassandraTemplate, so you only need to configure cassandra-template-ref explicitly if you deviate from this convention.

Because our domain repository extends CrudRepository, it provides you with basic CRUD operations. Working with the repository instance is a matter of injecting the repository as a dependency into a client, as the following example does by autowiring PersonRepository:

Example 68. Basic access to Person entities
@RunWith(SpringRunner.class)
@ContextConfiguration
public class PersonRepositoryTests {

    @Autowired PersonRepository repository;

    @Test
    public void readsPersonTableCorrectly() {

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

Cassandra repositories support paging and sorting for paginated and sorted access to the entities. Cassandra paging requires a paging state to forward-only navigate through pages. A Slice keeps track of the current paging state and allows for creation of a Pageable to request the next page. The following example shows how to set up paging access to Person entities:

Example 69. Paging access to Person entities
@RunWith(SpringRunner.class)
@ContextConfiguration
public class PersonRepositoryTests {

    @Autowired PersonRepository repository;

    @Test
    public void readsPagesCorrectly() {

      Slice<Person> firstBatch = repository.findAll(CassandraPageRequest.first(10));

      assertThat(firstBatch).hasSize(10);

      Page<Person> nextBatch = repository.findAll(firstBatch.nextPageable());

      // …
    }
}
Cassandra repositories do not extend PagingAndSortingRepository, because classic paging patterns using limit/offset are not applicable to Cassandra.

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

11.2. 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 a matter of declaring a method on the repository interface. The following example shows a number of such method declarations:

Example 70. PersonRepository with query methods
public interface PersonRepository extends CrudRepository<Person, String> {

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

    Slice<Person> findByFirstname(String firstname, Pageable pageRequest);  (2)

    List<Person> findByFirstname(String firstname, QueryOptions opts);      (3)

    List<Person> findByFirstname(String firstname, Sort sort);              (4)

    Person findByShippingAddress(Address address);                          (5)

    Person findFirstByShippingAddress(Address address);                     (6)

    Stream<Person> findAllBy();                                             (7)

    @AllowFiltering
    List<Person> findAllByAge(int age);                                     (8)
}
1 The method shows a query for all people with the given lastname. The query is derived from parsing the method name for constraints, which can be concatenated with And. Thus, the method name results in a query expression of SELECT * FROM person WHERE lastname = 'lastname'.
2 Applies pagination to a query. You can equip your method signature with a Pageable parameter and let the method return a Slice instance, and we automatically page the query accordingly.
3 Passing a QueryOptions object applies the query options to the resulting query before its execution.
4 Applies dynamic sorting to a query. You can add a Sort parameter to your method signature, and Spring Data automatically applies ordering to the query.
5 Shows that you can query based on properties that are not a primitive type by using Converter instances registered in CustomConversions. Throws IncorrectResultSizeDataAccessException if more than one match is found.
6 Uses the First keyword to restrict the query to only the first result. Unlike the preceding method, this method does not throw an exception if more than one match is found.
7 Uses a Java 8 Stream to read and convert individual elements while iterating the stream.
8 Shows a query method annotated with @AllowFiltering, to allow server-side filtering.
Querying non-primary key properties requires secondary indexes.

The following table shows short examples of the keywords that you can use in query methods:

Table 7. 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

Between

findByAgeBetween(int from, int to) and findByAgeBetween(Range<Integer> range)

age > from AND age < to and lower / upper bounds (> / >= & < / ⇐) according to Range

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

11.3. Repository Delete Queries

The keywords in the preceding table can be used in conjunction with delete…By to create queries that delete matching documents.

interface PersonRepository extends Repository<Person, String> {

  void deleteWithoutResultByLastname(String lastname);

  boolean deleteByLastname(String lastname);
}

Delete queries return whether the query was applied or terminate without returning a value using void.

11.3.1. 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 71. 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 72. 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 73. 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.

Declaring a method in your Repository that overrides a base method (e.g. declared in CrudRepository, a store-specific repository interface, or the Simple…Repository) results in a call to the base method regardless of the declared return type. Make sure to use a compatible return type as base methods cannot be used for projections. Some store modules support @Query annotations to turn an overridden base method into a query method that then can be used to return projections.

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 74. 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 75. 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 76. 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 77. 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 78. 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 79. 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.

Nullable Wrappers

Getters in projection interfaces can make use of nullable wrappers for improved null-safety. Currently supported wrapper types are:

  • java.util.Optional

  • com.google.common.base.Optional

  • scala.Option

  • io.vavr.control.Option

Example 80. A projection interface using nullable wrappers
interface NamesOnly {

  Optional<String> getFirstname();
}

If the underlying projection value is not null, then values are returned using the present-representation of the wrapper type. In case the backing value is null, then the getter method returns the empty representation of the used wrapper type.

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 81. A projecting DTO
record NamesOnly(String firstname, String lastname) {
}

Java Records are ideal to define DTO types since they adhere to value semantics: All fields are private final and equals(…)/hashCode()/toString() methods are created automatically. Alternatively, you can use any class that defines the properties you want to project.

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 82. 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 83. 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);
}
Query parameters of type Class are inspected whether they qualify as dynamic projection parameter. If the actual return type of the query equals the generic parameter type of the Class parameter, then the matching Class parameter is not available for usage within the query or SpEL expressions. If you want to use a Class parameter as query argument then make sure to use a different generic parameter, for example Class<?>.

11.3.2. Query Options

You can specify query options for query methods by passing a QueryOptions object. The options apply to the query before the actual query execution. QueryOptions is treated as a non-query parameter and is not considered to be a query parameter value. Query options apply to derived and string @Query repository methods.

To statically set the consistency level, use the @Consistency annotation on query methods. The declared consistency level is applied to the query each time it is executed. The following example sets the consistency level to ConsistencyLevel.LOCAL_ONE:

public interface PersonRepository extends CrudRepository<Person, String> {

    @Consistency(ConsistencyLevel.LOCAL_ONE)
    List<Person> findByLastname(String lastname);

    List<Person> findByFirstname(String firstname, QueryOptions options);
}

The DataStax Cassandra documentation includes a good discussion of the available consistency levels.

You can control fetch size, consistency level, and retry policy defaults by configuring the following parameters on the CQL API instances: CqlTemplate, AsyncCqlTemplate, and ReactiveCqlTemplate. Defaults apply if the particular query option is not set.

11.3.3. 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.To activate it, drop 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, as the following examlpe shows:

class CassandraTemplateProducer {

  @Produces
  @Singleton
  public CqlSession createSession() {
    return CqlSession.builder().withKeyspace("my-keyspace").build();
  }

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

    CassandraMappingContext mappingContext = new CassandraMappingContext();
    mappingContext.setUserTypeResolver(new SimpleUserTypeResolver(session));
    mappingContext.afterPropertiesSet();

    MappingCassandraConverter cassandraConverter = new MappingCassandraConverter(mappingContext);
    cassandraConverter.afterPropertiesSet();

    return new CassandraAdminTemplate(session, cassandraConverter);
  }

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

The Spring Data for Apache Cassandra CDI extension picks up CassandraOperations as a CDI bean and creates a proxy for a Spring Data repository whenever a bean of a repository type is requested by the container. Thus, obtaining an instance of a Spring Data repository is a matter of declaring an injected property, as the following example shows:

class RepositoryClient {

  @Inject PersonRepository repository;

  public void businessMethod() {
    List<Person> people = repository.findAll();
  }
}

12. Reactive Cassandra Repositories

This chapter outlines the specialties handled by the reactive repository support for Apache Cassandra. It builds on the core repository infrastructure explained in Cassandra Repositories, so you should have a good understanding of the basic concepts explained there.

Cassandra repositories use ReactiveCassandraTemplate and its wired ReactiveCqlTemplate as infrastructure beans.

Reactive usage is broken up into two phases: Composition and Execution.

Calling repository methods lets you compose a reactive sequence by obtaining Publisher instances and applying operators. No I/O happens until you subscribe. Passing the reactive sequence to a reactive execution infrastructure, such as Spring WebFlux or Vert.x), subscribes to the publisher and initiate the actual execution. See the Project reactor documentation for more detail.

12.1. Reactive Composition Libraries

The reactive space offers various reactive composition libraries. The most common libraries are RxJava and Project Reactor.

Spring Data for Apache Cassandra is built on top of the DataStax Cassandra Driver. The driver is not reactive but the asynchronous capabilities allow us to adopt and expose the Publisher APIs to provide maximum interoperability by relying on the Reactive Streams initiative. Static APIs, such as ReactiveCassandraOperations, are provided by using Project Reactor’s Flux and Mono types. Project Reactor offers various adapters to convert reactive wrapper types (Flux to Observable and back), but conversion can easily clutter your code.

Spring Data’s repository abstraction is a dynamic API that is mostly defined by you and your requirements as you declare query methods. Reactive Cassandra repositories can be implemented by using either RxJava or Project Reactor wrapper types by extending from one of the library-specific repository interfaces:

  • ReactiveCrudRepository

  • ReactiveSortingRepository

  • RxJava2CrudRepository

  • RxJava2SortingRepository

Spring Data converts reactive wrapper types behind the scenes so that you can stick to your favorite composition library.

12.2. Usage

To access domain entities stored in Apache Cassandra, you can use Spring Data’s sophisticated repository support, which significantly eases implementing DAOs. To do so, create an interface for your repository, as the following example shows:

Example 84. Sample Person entity
@Table
public class Person {

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

  // … getters and setters omitted
}

Note that the entity has a property named id of type String. The default serialization mechanism used in CassandraTemplate (which backs the repository support) regards properties named id as being the row ID.

The following example shows a repository definition to persist Person entities:

Example 85. Basic repository interface to persist Person entities
public interface ReactivePersonRepository extends ReactiveSortingRepository<Person, Long> {

  Flux<Person> findByFirstname(String firstname);                                (1)

  Flux<Person> findByFirstname(Publisher<String> firstname);                     (2)

  Mono<Person> findByFirstnameAndLastname(String firstname, String lastname);    (3)

  Mono<Person> findFirstByFirstname(String firstname);                           (4)

  @AllowFiltering
  Flux<Person> findByAge(int age);                                               (5)
}
1 A query for all people with the given firstname. The query is derived by parsing the method name for constraints, which can be concatenated with And and Or. Thus, the method name results in a query expression of SELECT * FROM person WHERE firstname = :firstname.
2 A query for all people with the given firstname once the firstname is emitted from the given Publisher.
3 Find a single entity for the given criteria. Completes with IncorrectResultSizeDataAccessException on non-unique results.
4 Unlike the preceding query, the first entity is always emitted even if the query yields more result rows.
5 A query method annotated with @AllowFiltering, which allows server-side filtering.

For Java configuration, use the @EnableReactiveCassandraRepositories annotation. The annotation carries the same attributes as the corresponding XML namespace element. If no base package is configured, the infrastructure scans the package of the annotated configuration class. The following example uses the @EnableReactiveCassandraRepositories annotation:

Example 86. Java configuration for repositories
@Configuration
@EnableReactiveCassandraRepositories
class ApplicationConfig extends AbstractReactiveCassandraConfiguration {

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

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

Since our domain repository extends ReactiveSortingRepository, it provides you with CRUD operations as well as methods for sorted access to the entities. Working with the repository instance is a matter of dependency injecting it into a client, as the following example shows:

Example 87. Sorted access to Person entities
public class PersonRepositoryTests {

    @Autowired ReactivePersonRepository repository;

    @Test
    public void sortsElementsCorrectly() {
        Flux<Person> people = repository.findAll(Sort.by(new Order(ASC, "lastname")));
    }
}

Cassandra repositories support paging and sorting for paginated and sorted access to the entities. Cassandra paging requires a paging state to forward-only navigate through pages. A Slice keeps track of the current paging state and allows for creation of a Pageable to request the next page. The following example shows how to set up paging access to Person entities:

Example 88. Paging access to Person entities
@RunWith(SpringRunner.class)
@ContextConfiguration
public class PersonRepositoryTests {

    @Autowired PersonRepository repository;

    @Test
    public void readsPagesCorrectly() {

      Mono<Slice<Person>> firstBatch = repository.findAll(CassandraPageRequest.first(10));

      Mono<Slice<Person>> nextBatch = firstBatch.flatMap(it -> repository.findAll(it.nextPageable()));

      // …
    }
}

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

12.3. Features

Spring Data’s Reactive Cassandra support comes with the same set of features as the support for imperative repositories.

It supports the following features:

Query methods must return a reactive type. Resolved types (User versus Mono<User>) are not supported.

13. Auditing

13.1. Basics

Spring Data provides sophisticated support to transparently keep track of who created or changed an entity and when the change happened.To benefit from that functionality, you have to equip your entity classes with auditing metadata that can be defined either using annotations or by implementing an interface. Additionally, auditing has to be enabled either through Annotation configuration or XML configuration to register the required infrastructure components. Please refer to the store-specific section for configuration samples.

Applications that only track creation and modification dates are not required do make their entities implement AuditorAware.

13.1.1. Annotation-based Auditing Metadata

We provide @CreatedBy and @LastModifiedBy to capture the user who created or modified the entity as well as @CreatedDate and @LastModifiedDate to capture when the change happened.

Example 89. An audited entity
class Customer {

  @CreatedBy
  private User user;

  @CreatedDate
  private Instant createdDate;

  // … further properties omitted
}

As you can see, the annotations can be applied selectively, depending on which information you want to capture. The annotations, indicating to capture when changes are made, can be used on properties of type JDK8 date and time types, long, Long, and legacy Java Date and Calendar.

Auditing metadata does not necessarily need to live in the root level entity but can be added to an embedded one (depending on the actual store in use), as shown in the snippet below.

Example 90. Audit metadata in embedded entity
class Customer {

  private AuditMetadata auditingMetadata;

  // … further properties omitted
}

class AuditMetadata {

  @CreatedBy
  private User user;

  @CreatedDate
  private Instant createdDate;

}

13.1.2. Interface-based Auditing Metadata

In case you do not want to use annotations to define auditing metadata, you can let your domain class implement the Auditable interface. It exposes setter methods for all of the auditing properties.

13.1.3. AuditorAware

In case you use either @CreatedBy or @LastModifiedBy, the auditing infrastructure somehow needs to become aware of the current principal. To do so, we provide an AuditorAware<T> SPI interface that you have to implement to tell the infrastructure who the current user or system interacting with the application is. The generic type T defines what type the properties annotated with @CreatedBy or @LastModifiedBy have to be.

The following example shows an implementation of the interface that uses Spring Security’s Authentication object:

Example 91. Implementation of AuditorAware based on Spring Security
class SpringSecurityAuditorAware implements AuditorAware<User> {

  @Override
  public Optional<User> getCurrentAuditor() {

    return Optional.ofNullable(SecurityContextHolder.getContext())
            .map(SecurityContext::getAuthentication)
            .filter(Authentication::isAuthenticated)
            .map(Authentication::getPrincipal)
            .map(User.class::cast);
  }
}

The implementation accesses the Authentication object provided by Spring Security and looks up the custom UserDetails instance that you have created in your UserDetailsService implementation. We assume here that you are exposing the domain user through the UserDetails implementation but that, based on the Authentication found, you could also look it up from anywhere.

13.1.4. ReactiveAuditorAware

When using reactive infrastructure you might want to make use of contextual information to provide @CreatedBy or @LastModifiedBy information. We provide an ReactiveAuditorAware<T> SPI interface that you have to implement to tell the infrastructure who the current user or system interacting with the application is. The generic type T defines what type the properties annotated with @CreatedBy or @LastModifiedBy have to be.

The following example shows an implementation of the interface that uses reactive Spring Security’s Authentication object:

Example 92. Implementation of ReactiveAuditorAware based on Spring Security
class SpringSecurityAuditorAware implements ReactiveAuditorAware<User> {

  @Override
  public Mono<User> getCurrentAuditor() {

    return ReactiveSecurityContextHolder.getContext()
                .map(SecurityContext::getAuthentication)
                .filter(Authentication::isAuthenticated)
                .map(Authentication::getPrincipal)
                .map(User.class::cast);
  }
}

The implementation accesses the Authentication object provided by Spring Security and looks up the custom UserDetails instance that you have created in your UserDetailsService implementation. We assume here that you are exposing the domain user through the UserDetails implementation but that, based on the Authentication found, you could also look it up from anywhere.

13.2. General Auditing Configuration for Cassandra

To activate auditing functionality, create a configuration as the following example shows:

Example 93. Activating auditing by using XML configuration
Java
@Configuration
@EnableCassandraAuditing
class Config {

  @Bean
  public AuditorAware<AuditableUser> myAuditorProvider() {
      return new AuditorAwareImpl();
  }
}
XML
<?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
    https://www.springframework.org/schema/data/cassandra/spring-cassandra.xsd
    http://www.springframework.org/schema/beans
    https://www.springframework.org/schema/beans/spring-beans.xsd">

    <cassandra:auditing mapping-context-ref="customMappingContext" auditor-aware-ref="yourAuditorAwareImpl"/>
</beans>

If you expose a bean of type AuditorAware to the ApplicationContext, the auditing infrastructure picks it up automatically and uses it to determine the current user to be set on domain types. If you have multiple implementations registered in the ApplicationContext, you can select the one to be used by explicitly setting the auditorAwareRef attribute of @EnableCassandraAuditing.

To enable auditing, leveraging a reactive programming model, use the @EnableReactiveCassandraAuditing annotation.
If you expose a bean of type ReactiveAuditorAware to the ApplicationContext, the auditing infrastructure picks it up automatically and uses it to determine the current user to be set on domain types. If you have multiple implementations registered in the ApplicationContext, you can select the one to be used by explicitly setting the auditorAwareRef attribute of @EnableReactiveCassandraAuditing.

Example 94. Activating reactive auditing using JavaConfig
@Configuration
@EnableReactiveCassandraAuditing
class Config {

  @Bean
  public ReactiveAuditorAware<AuditableUser> myAuditorProvider() {
      return new AuditorAwareImpl();
  }
}

14. Mapping

Rich object 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 by using annotations on your domain objects. However, the infrastructure is not limited to using annotations as the only source of metadata. The MappingCassandraConverter also lets you map domain objects to tables without providing any additional metadata, by following a set of conventions.

In this chapter, we 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.

14.1. Object Mapping Fundamentals

This section covers the fundamentals of Spring Data object mapping, object creation, field and property access, mutability and immutability. Note, that this section only applies to Spring Data modules that do not use the object mapping of the underlying data store (like JPA). Also be sure to consult the store-specific sections for store-specific object mapping, like indexes, customizing column or field names or the like.

Core responsibility of the Spring Data object mapping is to create instances of domain objects and map the store-native data structures onto those. This means we need two fundamental steps:

  1. Instance creation by using one of the constructors exposed.

  2. Instance population to materialize all exposed properties.

14.1.1. Object creation

Spring Data automatically tries to detect a persistent entity’s constructor to be used to materialize objects of that type. The resolution algorithm works as follows:

  1. If there is a single static factory method annotated with @PersistenceCreator then it is used.

  2. If there is a single constructor, it is used.

  3. If there are multiple constructors and exactly one is annotated with @PersistenceCreator, it is used.

  4. If the type is a Java Record the canonical constructor is used.

  5. If there’s a no-argument constructor, it is used. Other constructors will be ignored.

The value resolution assumes constructor/factory method argument names to match the property names of the entity, i.e. the resolution will be performed as if the property was to be populated, including all customizations in mapping (different datastore column or field name etc.). This also requires either parameter names information available in the class file or an @ConstructorProperties annotation being present on the constructor.

The value resolution can be customized by using Spring Framework’s @Value value annotation using a store-specific SpEL expression. Please consult the section on store specific mappings for further details.

Object creation internals

To avoid the overhead of reflection, Spring Data object creation uses a factory class generated at runtime by default, which will call the domain classes constructor directly. I.e. for this example type:

class Person {
  Person(String firstname, String lastname) { … }
}

we will create a factory class semantically equivalent to this one at runtime:

class PersonObjectInstantiator implements ObjectInstantiator {

  Object newInstance(Object... args) {
    return new Person((String) args[0], (String) args[1]);
  }
}

This gives us a roundabout 10% performance boost over reflection. For the domain class to be eligible for such optimization, it needs to adhere to a set of constraints:

  • it must not be a private class

  • it must not be a non-static inner class

  • it must not be a CGLib proxy class

  • the constructor to be used by Spring Data must not be private

If any of these criteria match, Spring Data will fall back to entity instantiation via reflection.

14.1.2. Property population

Once an instance of the entity has been created, Spring Data populates all remaining persistent properties of that class. Unless already populated by the entity’s constructor (i.e. consumed through its constructor argument list), the identifier property will be populated first to allow the resolution of cyclic object references. After that, all non-transient properties that have not already been populated by the constructor are set on the entity instance. For that we use the following algorithm:

  1. If the property is immutable but exposes a with… method (see below), we use the with… method to create a new entity instance with the new property value.

  2. If property access (i.e. access through getters and setters) is defined, we’re invoking the setter method.

  3. If the property is mutable we set the field directly.

  4. If the property is immutable we’re using the constructor to be used by persistence operations (see Object creation) to create a copy of the instance.

  5. By default, we set the field value directly.

Property population internals

Similarly to our optimizations in object construction we also use Spring Data runtime generated accessor classes to interact with the entity instance.

class Person {

  private final Long id;
  private String firstname;
  private @AccessType(Type.PROPERTY) String lastname;

  Person() {
    this.id = null;
  }

  Person(Long id, String firstname, String lastname) {
    // Field assignments
  }

  Person withId(Long id) {
    return new Person(id, this.firstname, this.lastame);
  }

  void setLastname(String lastname) {
    this.lastname = lastname;
  }
}
Example 95. A generated Property Accessor
class PersonPropertyAccessor implements PersistentPropertyAccessor {

  private static final MethodHandle firstname;              (2)

  private Person person;                                    (1)

  public void setProperty(PersistentProperty property, Object value) {

    String name = property.getName();

    if ("firstname".equals(name)) {
      firstname.invoke(person, (String) value);             (2)
    } else if ("id".equals(name)) {
      this.person = person.withId((Long) value);            (3)
    } else if ("lastname".equals(name)) {
      this.person.setLastname((String) value);              (4)
    }
  }
}
1 PropertyAccessor’s hold a mutable instance of the underlying object. This is, to enable mutations of otherwise immutable properties.
2 By default, Spring Data uses field-access to read and write property values. As per visibility rules of private fields, MethodHandles are used to interact with fields.
3 The class exposes a withId(…) method that’s used to set the identifier, e.g. when an instance is inserted into the datastore and an identifier has been generated. Calling withId(…) creates a new Person object. All subsequent mutations will take place in the new instance leaving the previous untouched.
4 Using property-access allows direct method invocations without using MethodHandles.

This gives us a roundabout 25% performance boost over reflection. For the domain class to be eligible for such optimization, it needs to adhere to a set of constraints:

  • Types must not reside in the default or under the java package.

  • Types and their constructors must be public

  • Types that are inner classes must be static.

  • The used Java Runtime must allow for declaring classes in the originating ClassLoader. Java 9 and newer impose certain limitations.

By default, Spring Data attempts to use generated property accessors and falls back to reflection-based ones if a limitation is detected.

Let’s have a look at the following entity:

Example 96. A sample entity
class Person {

  private final @Id Long id;                                                (1)
  private final String firstname, lastname;                                 (2)
  private final LocalDate birthday;
  private final int age;                                                    (3)

  private String comment;                                                   (4)
  private @AccessType(Type.PROPERTY) String remarks;                        (5)

  static Person of(String firstname, String lastname, LocalDate birthday) { (6)

    return new Person(null, firstname, lastname, birthday,
      Period.between(birthday, LocalDate.now()).getYears());
  }

  Person(Long id, String firstname, String lastname, LocalDate birthday, int age) { (6)

    this.id = id;
    this.firstname = firstname;
    this.lastname = lastname;
    this.birthday = birthday;
    this.age = age;
  }

  Person withId(Long id) {                                                  (1)
    return new Person(id, this.firstname, this.lastname, this.birthday, this.age);
  }

  void setRemarks(String remarks) {                                         (5)
    this.remarks = remarks;
  }
}
1 The identifier property is final but set to null in the constructor. The class exposes a withId(…) method that’s used to set the identifier, e.g. when an instance is inserted into the datastore and an identifier has been generated. The original Person instance stays unchanged as a new one is created. The same pattern is usually applied for other properties that are store managed but might have to be changed for persistence operations. The wither method is optional as the persistence constructor (see 6) is effectively a copy constructor and setting the property will be translated into creating a fresh instance with the new identifier value applied.
2 The firstname and lastname properties are ordinary immutable properties potentially exposed through getters.
3 The age property is an immutable but derived one from the birthday property. With the design shown, the database value will trump the defaulting as Spring Data uses the only declared constructor. Even if the intent is that the calculation should be preferred, it’s important that this constructor also takes age as parameter (to potentially ignore it) as otherwise the property population step will attempt to set the age field and fail due to it being immutable and no with… method being present.
4 The comment property is mutable and is populated by setting its field directly.
5 The remarks property is mutable and is populated by invoking the setter method.
6 The class exposes a factory method and a constructor for object creation. The core idea here is to use factory methods instead of additional constructors to avoid the need for constructor disambiguation through @PersistenceCreator. Instead, defaulting of properties is handled within the factory method. If you want Spring Data to use the factory method for object instantiation, annotate it with @PersistenceCreator.

14.1.3. General recommendations

  • Try to stick to immutable objects — Immutable objects are straightforward to create as materializing an object is then a matter of calling its constructor only. Also, this avoids your domain objects to be littered with setter methods that allow client code to manipulate the objects state. If you need those, prefer to make them package protected so that they can only be invoked by a limited amount of co-located types. Constructor-only materialization is up to 30% faster than properties population.

  • Provide an all-args constructor — Even if you cannot or don’t want to model your entities as immutable values, there’s still value in providing a constructor that takes all properties of the entity as arguments, including the mutable ones, as this allows the object mapping to skip the property population for optimal performance.

  • Use factory methods instead of overloaded constructors to avoid @PersistenceCreator — With an all-argument constructor needed for optimal performance, we usually want to expose more application use case specific constructors that omit things like auto-generated identifiers etc. It’s an established pattern to rather use static factory methods to expose these variants of the all-args constructor.

  • Make sure you adhere to the constraints that allow the generated instantiator and property accessor classes to be used — 

  • For identifiers to be generated, still use a final field in combination with an all-arguments persistence constructor (preferred) or a with… method — 

  • Use Lombok to avoid boilerplate code — As persistence operations usually require a constructor taking all arguments, their declaration becomes a tedious repetition of boilerplate parameter to field assignments that can best be avoided by using Lombok’s @AllArgsConstructor.

Overriding Properties

Java’s allows a flexible design of domain classes where a subclass could define a property that is already declared with the same name in its superclass. Consider the following example:

public class SuperType {

   private CharSequence field;

   public SuperType(CharSequence field) {
      this.field = field;
   }

   public CharSequence getField() {
      return this.field;
   }

   public void setField(CharSequence field) {
      this.field = field;
   }
}

public class SubType extends SuperType {

   private String field;

   public SubType(String field) {
      super(field);
      this.field = field;
   }

   @Override
   public String getField() {
      return this.field;
   }

   public void setField(String field) {
      this.field = field;

      // optional
      super.setField(field);
   }
}

Both classes define a field using assignable types. SubType however shadows SuperType.field. Depending on the class design, using the constructor could be the only default approach to set SuperType.field. Alternatively, calling super.setField(…) in the setter could set the field in SuperType. All these mechanisms create conflicts to some degree because the properties share the same name yet might represent two distinct values. Spring Data skips super-type properties if types are not assignable. That is, the type of the overridden property must be assignable to its super-type property type to be registered as override, otherwise the super-type property is considered transient. We generally recommend using distinct property names.

Spring Data modules generally support overridden properties holding different values. From a programming model perspective there are a few things to consider:

  1. Which property should be persisted (default to all declared properties)? You can exclude properties by annotating these with @Transient.

  2. How to represent properties in your data store? Using the same field/column name for different values typically leads to corrupt data so you should annotate least one of the properties using an explicit field/column name.

  3. Using @AccessType(PROPERTY) cannot be used as the super-property cannot be generally set without making any further assumptions of the setter implementation.

14.1.4. Kotlin support

Spring Data adapts specifics of Kotlin to allow object creation and mutation.

Kotlin object creation

Kotlin classes are supported to be instantiated, all classes are immutable by default and require explicit property declarations to define mutable properties.

Spring Data automatically tries to detect a persistent entity’s constructor to be used to materialize objects of that type. The resolution algorithm works as follows:

  1. If there is a constructor that is annotated with @PersistenceCreator, it is used.

  2. If the type is a Kotlin data cass the primary constructor is used.

  3. If there is a single static factory method annotated with @PersistenceCreator then it is used.

  4. If there is a single constructor, it is used.

  5. If there are multiple constructors and exactly one is annotated with @PersistenceCreator, it is used.

  6. If the type is a Java Record the canonical constructor is used.

  7. If there’s a no-argument constructor, it is used. Other constructors will be ignored.

Consider the following data class Person:

data class Person(val id: String, val name: String)

The class above compiles to a typical class with an explicit constructor.We can customize this class by adding another constructor and annotate it with @PersistenceCreator to indicate a constructor preference:

data class Person(var id: String, val name: String) {

    @PersistenceCreator
    constructor(id: String) : this(id, "unknown")
}

Kotlin supports parameter optionality by allowing default values to be used if a parameter is not provided. When Spring Data detects a constructor with parameter defaulting, then it leaves these parameters absent if the data store does not provide a value (or simply returns null) so Kotlin can apply parameter defaulting.Consider the following class that applies parameter defaulting for name

data class Person(var id: String, val name: String = "unknown")

Every time the name parameter is either not part of the result or its value is null, then the name defaults to unknown.

Property population of Kotlin data classes

In Kotlin, all classes are immutable by default and require explicit property declarations to define mutable properties. Consider the following data class Person:

data class Person(val id: String, val name: String)

This class is effectively immutable. It allows creating new instances as Kotlin generates a copy(…) method that creates new object instances copying all property values from the existing object and applying property values provided as arguments to the method.

Kotlin Overriding Properties

Kotlin allows declaring property overrides to alter properties in subclasses.

open class SuperType(open var field: Int)

class SubType(override var field: Int = 1) :
  SuperType(field) {
}

Such an arrangement renders two properties with the name field. Kotlin generates property accessors (getters and setters) for each property in each class. Effectively, the code looks like as follows:

public class SuperType {

   private int field;

   public SuperType(int field) {
      this.field = field;
   }

   public int getField() {
      return this.field;
   }

   public void setField(int field) {
      this.field = field;
   }
}

public final class SubType extends SuperType {

   private int field;

   public SubType(int field) {
      super(field);
      this.field = field;
   }

   public int getField() {
      return this.field;
   }

   public void setField(int field) {
      this.field = field;
   }
}

Getters and setters on SubType set only SubType.field and not SuperType.field. In such an arrangement, using the constructor is the only default approach to set SuperType.field. Adding a method to SubType to set SuperType.field via this.SuperType.field = … is possible but falls outside of supported conventions. Property overrides create conflicts to some degree because the properties share the same name yet might represent two distinct values. We generally recommend using distinct property names.

Spring Data modules generally support overridden properties holding different values. From a programming model perspective there are a few things to consider:

  1. Which property should be persisted (default to all declared properties)? You can exclude properties by annotating these with @Transient.

  2. How to represent properties in your data store? Using the same field/column name for different values typically leads to corrupt data so you should annotate least one of the properties using an explicit field/column name.

  3. Using @AccessType(PROPERTY) cannot be used as the super-property cannot be set.

14.2. Data Mapping and Type Conversion

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

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 custom converters to adjust type conversion. See “[cassandra.mapping.explicit-converters]” for further details. The following table maps Spring Data types to Cassandra types:

Table 8. 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

uuid

TupleValue, mapped Tuple Types

tuple<…>

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

LocalTime+ (Joda, Java 8, JSR310-BackPort)

time

LocalDateTime, LocalTime, Instant
(Joda, Java 8, JSR310-BackPort)

timestamp

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, as the following example shows:

Example 97. Enum mapping to numeric types
@Table
public class EnumToOrdinalMapping {

  @PrimaryKey String id;

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

public enum Condition {
  NEW, USED
}

14.3. 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 simple (short) Java class name is mapped to the table name by being changed to lower case. For example, com.bigbank.SavingsAccount maps to a table named savingsaccount.

  • The converter uses any registered Spring Converter instances to override the default mapping of object properties to tables columns.

  • The properties of an object are used to convert to and from columns in the table.

You can adjust conventions by configuring a NamingStrategy on CassandraMappingContext. Naming strategy objects implement the convention by which a table, column or user-defined type is derived from an entity class and from an actual property.

The following example shows how to configure a NamingStrategy:

Example 98. Configuring NamingStrategy on CassandraMappingContext
    CassandraMappingContext context = new CassandraMappingContext();

    // default naming strategy
    context.setNamingStrategy(NamingStrategy.INSTANCE);

    // snake_case converted to upper case (SNAKE_CASE)
    context.setNamingStrategy(NamingStrategy.SNAKE_CASE.transform(String::toUpperCase));

14.3.1. 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 to tell it where to scan the classpath at startup for your domain classes to extract metadata and construct indexes.

Also, by creating your own instance, you can register Spring Converter instances to use for mapping specific classes to and from the database. The following example configuration class sets up Cassandra mapping support:

Example 99. @Configuration class to configure Cassandra mapping support
@Configuration
public class SchemaConfiguration extends AbstractCassandraConfiguration {

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

  // the following are optional

  @Override
  public CassandraCustomConversions customConversions() {

    List<Converter<?, ?>> converters = new ArrayList<>();

    converters.add(new PersonReadConverter());
    converters.add(new PersonWriteConverter());

    return new CassandraCustomConversions(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 named getEntityBasePackages(…). You can override it to tell the converter where to scan for classes annotated with the @Table annotation.

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

AbstractCassandraConfiguration creates a CassandraTemplate instance and registers it with the container under the name of cassandraTemplate.

14.4. 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 domain objects with the @Table annotation. Doing so lets the classpath scanner find and pre-process your domain objects to extract the necessary metadata. Only annotated entities are used to perform schema actions. In the worst case, a SchemaAction.RECREATE_DROP_UNUSED operation drops your tables and you lose your data. The following example shows a simple domain object:

Example 100. 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.

14.4.1. Working with Primary Keys

Cassandra requires at least one partition key field for a CQL table. A table can additionally declare 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 Keys

A simple primary key consists of one partition key field within an entity class. Since it is one field only, we safely can assume it is a partition key. The following listing shows a CQL table defined in Cassandra with a primary key of user_id:

Example 101. CQL Table defined in Cassandra
CREATE TABLE user (
  user_id text,
  firstname text,
  lastname text,
  PRIMARY KEY (user_id))
;

The following example shows a Java class annotated such that it corresponds to the Cassandra defined in the previous listing:

Example 102. 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

}
Composite Keys

Composite primary keys (or compound keys) consist of more than one primary key field. 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.

The following example shows a CQL statement to represent the table and its composite key:

Example 103. 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 Keys

Flat composite primary keys are embedded inside the entity as flat fields. Primary key fields are annotated with @PrimaryKeyColumn. Selection requires either a query to contain predicates for the individual fields or the use of MapId. The following example shows a class with a flat composite primary key:

Example 104. Using a flat composite primary key
@Table(value = "login_event")
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 LocalDateTime eventTime;

  @Column("ip_address")
  private String ipAddress;

  // getters and setters omitted
}
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 is annotated with @PrimaryKeyClass and should define 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 entity’s identity in a single complex object. The following example shows a composite primary key class:

Example 105. Composite primary key class
@PrimaryKeyClass
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 LocalDateTime eventTime;

  // other methods omitted
}

The following example shows how to use a composite primary key:

Example 106. 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
}

14.4.2. Embedded Entity Support

Embedded entities are used to design value objects in your Java domain model whose properties are flattened out into the table. In the following example you see, that User.name is annotated with @Embedded. The consequence of this is that all properties of UserName are folded into the user table which consists of 3 columns (user_id, firstname, lastname).

Embedded entities may only contain simple property types. It is not possible to nest an embedded entity into another embedded one.

However, if the firstname and lastname column values are actually null within the result set, the entire property name will be set to null according to the onEmpty of @Embedded, which nulls objects when all nested properties are null.
Opposite to this behavior USE_EMPTY tries to create a new instance using either a default constructor or one that accepts nullable parameter values from the result set.

Example 107. Sample Code of embedding objects
public class User {

  @PrimaryKey("user_id")
    private String userId;

    @Embedded(onEmpty = USE_NULL) (1)
    UserName name;
}

public class UserName {
    private String firstname;
    private String lastname;
}
1 Property is null if firstname and lastname are null. Use onEmpty=USE_EMPTY to instantiate UserName with a potential null value for its properties.

You can embed a value object multiple times in an entity by using the optional prefix element of the @Embedded annotation. This element represents a prefix and is prepended to each column name in the embedded object. Note that properties will overwrite each other if multiple properties render to the same column name.

Make use of the shortcuts @Embedded.Nullable and @Embedded.Empty for @Embedded(onEmpty = USE_NULL) and @Embedded(onEmpty = USE_EMPTY) to reduce verbosity and simultaneously set JSR-305 @javax.annotation.Nonnull accordingly.

public class MyEntity {

    @Id
    Integer id;

    @Embedded.Nullable (1)
    EmbeddedEntity embeddedEntity;
}
1 Shortcut for @Embedded(onEmpty = USE_NULL).

14.4.3. Mapping Annotation Overview

The MappingCassandraConverter can use metadata to drive the mapping of objects to rows in a Cassandra table. An overview of the annotations follows:

  • @Id: Applied at the field or property level to mark the property used for identity purposes.

  • @Table: Applied at the class level to indicate that this class is a candidate for mapping to the database. You can specify the name of the table where the object is stored.

  • @PrimaryKey: Similar to @Id but lets you specify the column name.

  • @PrimaryKeyColumn: Cassandra-specific annotation for primary key columns that lets you specify primary key column attributes, such as for clustered or partitioned. Can be used on single and multiple attributes to indicate either a single or a composite (compound) primary key. If used on a property within the entity, make sure to apply the @Id annotation as well.

  • @PrimaryKeyClass: Applied at the class level to indicate that this class is a compound primary key class. Must be referenced with @PrimaryKey in the entity class.

  • @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. Transient properties cannot be used within a persistence constructor as the converter cannot materialize a value for the constructor argument.

  • @PersistenceConstructor: Marks a given constructor — even a package protected one — to use when instantiating the object from the database. Constructor arguments are mapped by name to the key values in the retrieved row.

  • @Value: This annotation is part of the Spring Framework . Within the mapping framework it can be applied to constructor arguments. This lets you use a Spring Expression Language statement to transform a key’s value retrieved in the database before it is used to construct a domain object. In order to reference a property of a given Row/UdtValue/TupleValue one has to use expressions like: @Value("#root.getString(0)") where root refers to the root of the given document.

  • @ReadOnlyProperty: Applies at the field level to mark a property as read-only. Entity-bound insert and update statements do not include this property.

  • @Column: Applied at the field level. Describes the column name as it is represented in the Cassandra table, thus letting the name differ from the field name of the class. Can be used on constructor arguments to customize the column name during constructor creation.

  • @Embedded: Applied at the field level. Enables embedded object usage for types mapped to a table or a user-defined type. Properties of the embedded object are flattened into the structure of its parent.

  • @Indexed: Applied at the field level. Describes the index to be created at session initialization.

  • @SASI: Applied at the field level. Allows SASI index creation during session initialization.

  • @CassandraType: Applied at the field level to specify a Cassandra data type. Types are derived from the property declaration by default.

  • @Frozen: Applied at the field level to class-types and parametrized types. Declares a frozen UDT column or frozen collection like List<@Frozen UserDefinedPersonType>.

  • @UserDefinedType: Applied at the type level to specify a Cassandra User-defined Data Type (UDT). Types are derived from the declaration by default.

  • @Tuple: Applied at the type level to use a type as a mapped tuple.

  • @Element: Applied at the field level to specify element or field ordinals within a mapped tuple. Types are derived from the property declaration by default. Can be used on constructor arguments to customize tuple element ordinals during constructor creation.

  • @Version: Applied at field level is used for optimistic locking and checked for modification on save operations. The initial value is zero which is bumped automatically on every update.

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

The following example shows a more complex mapping:

Example 108. 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 omitted
  }

  @PrimaryKey
  private Person.Key key;

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

  @Column("f_name")
  private String firstName;

  @Column
  @Indexed
  private String lastName;

  private Address address;

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

  private Coordinates coordinates;

  @Transient
  private Integer accountTotal;

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

  private Map<@Indexed String, InetAddress> sessions;

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

  public Person.Key getKey() {
    return key;
  }

  // no setter for Id.  (getter is only exposed for some unit testing)

  public Integer getSsn() {
    return ssn;
  }

  public void setFirstName(String firstName) {
    this.firstName = firstName;
  }

  // other getters/setters omitted
}

The following example shows how to map a UDT Address:

Example 109. Mapped User-Defined Type Address
@UserDefinedType("address")
public class Address {

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

  private String city;

  private Set<String> zipcodes;

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

  // other getters/setters omitted
}
Working with User-Defined Types requires a UserTypeResolver that is configured with the mapping context. See the configuration chapter for how to configure a UserTypeResolver.

The following example shows how map a tuple:

Example 110. Mapped Tuple
@Tuple
class Coordinates {

  @Element(0)
  @CassandraType(type = CassandraType.Name.VARCHAR)
  private String description;

  @Element(1)
  private long longitude;

  @Element(2)
  private long latitude;

  // other getters/setters omitted
}
Index Creation

You can annotate particular entity properties with @Indexed or @SASI if you wish to create secondary indexes on application startup. Index creation creates simple secondary indexes for scalar types, user-defined types, and collection types.

You can configure a SASI Index to apply an analyzer, such as StandardAnalyzer or NonTokenizingAnalyzer (by using @StandardAnalyzed and @NonTokenizingAnalyzed, respectively).

Map types distinguish between ENTRY, KEYS, and VALUES indexes. Index creation derives the index type from the annotated element. The following example shows a number of ways to create an index:

Example 111. Variants of map indexing
@Table
class PersonWithIndexes {

  @Id
  private String key;

  @SASI
  @StandardAnalyzed
  private String names;

  @Indexed("indexed_map")
  private Map<String, String> entries;

  private Map<@Indexed String, String> keys;

  private Map<String, @Indexed String> values;

  // …
}

The @Indexed annotation can be applied to single properties of embedded entities or along side with the @Embedded annotation, in which case all properties of the embedded are indexed.
Index creation on session initialization may have a severe performance impact on application startup.

14.5. Overriding Default Mapping with Custom Converters

To have more fine-grained control over the mapping process, you can register Spring Converters with CassandraConverter implementations, such as MappingCassandraConverter.

MappingCassandraConverter first checks to see whether any Spring Converters 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 need to create an implementation of the Spring Converter interface and register it with the MappingCassandraConverter.

14.5.1. Saving by Using a Registered Spring Converter

You can combine converting and saving in a single process, basically using the converter to do the saving.

The following example uses a Converter to convert a Person object to a java.lang.String with Jackson 2:

class PersonWriteConverter implements Converter<Person, String> {

  public String convert(Person source) {

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

14.5.2. Reading by Using a Spring Converter

Similar to how you can combine saving and converting, you can also combine reading and converting.

The following example uses a Converter that converts a java.lang.String into a Person object with Jackson 2:

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;
  }
}

14.5.3. Registering Spring Converters with CassandraConverter

Spring Data for Apache Cassandra Java configuration provides a convenient way to register Spring Converter instances: MappingCassandraConverter. The following configuration snippet shows how to manually register converters as well as configure CustomConversions:

@Configuration
public class ConverterConfiguration extends AbstractCassandraConfiguration {

  @Override
  public CassandraCustomConversions customConversions() {

    List<Converter<?, ?>> converters = new ArrayList<>();

    converters.add(new PersonReadConverter());
    converters.add(new PersonWriteConverter());

    return new CassandraCustomConversions(converters);
  }

  // other methods omitted...

}

The following example of a Spring Converter implementation converts from a String to a custom Email value object:

@ReadingConverter
public class EmailReadConverter implements Converter<String, Email> {

  public Email convert(String source) {
    return Email.valueOf(source);
  }
}

If you write a Converter whose source and target type are native types, we cannot determine whether we should consider it as a reading or a writing converter. Registering the converter instance as both might lead to unwanted results. For example, 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 let you force the infrastructure to register a converter for only one way, we provide @ReadingConverter and @WritingConverter annotations to be used in the converter implementation.

Converters are subject to explicit registration as instances are not picked up from a classpath or container scan to avoid unwanted registration with a conversion service and the side effects resulting from such a registration. Converters are registered with CustomConversions as the central facility that allows registration and querying for registered converters based on source- and target type.

CustomConversions ships with a pre-defined set of converter registrations:

  • JSR-310 Converters for conversion between java.time, java.util.Date and String types.

Default converters for local temporal types (e.g. LocalDateTime to java.util.Date) rely on system-default timezone settings to convert between those types. You can override the default converter, by registering your own converter.
Converter Disambiguation

Generally, we inspect the Converter implementations for the source and target types they convert from and to. Depending on whether one of those is a type the underlying data access API can handle natively, we register the converter instance as a reading or a writing converter. The following examples show a writing- and a read converter (note the difference is in the order of the qualifiers on Converter):

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

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

14.6. Entity State Detection Strategies

The following table describes the strategies that Spring Data offers for detecting whether an entity is new:

Table 9. Options for detection whether an entity is new in Spring Data

@Id-Property inspection (the default)

By default, Spring Data inspects the identifier property of the given entity. If the identifier property is null or 0 in case of primitive types, then the entity is assumed to be new. Otherwise, it is assumed to not be new.

@Version-Property inspection

If a property annotated with @Version is present and null, or in case of a version property of primitive type 0 the entity is considered new. If the version property is present but has a different value, the entity is considered to not be new. If no version property is present Spring Data falls back to inspection of the identifier property.

Implementing Persistable

If an entity implements Persistable, Spring Data delegates the new detection to the isNew(…) method of the entity. See the Javadoc for details.

Note: Properties of Persistable will get detected and persisted if you use AccessType.PROPERTY. To avoid that, use @Transient.

Providing a custom EntityInformation implementation

You can customize the EntityInformation abstraction used in the repository base implementation by creating a subclass of the module specific repository factory and overriding the getEntityInformation(…) method. You then have to register the custom implementation of module specific repository factory as a Spring bean. Note that this should rarely be necessary.
Cassandra provides no means to generate identifiers upon inserting data. As consequence, entities must be associated with identifier values. Spring Data defaults to identifier inspection to determine whether an entity is new. If you want to use auditing make sure to either use Optimistic Locking or implement Persistable for proper entity state detection.

14.7. Lifecycle Events

The Cassandra mapping framework has several built-in org.springframework.context.ApplicationEvent events that your application can respond to by registering special beans in the ApplicationContext. Being based on Spring’s application context event infrastructure lets other products, such as Spring Integration, easily receive these events as they are a well known eventing mechanism in Spring-based applications.

To intercept an object before it goes into the database, you can register a subclass of org.springframework.data.cassandra.core.mapping.event.AbstractCassandraEventListener that overrides the onBeforeSave(…) method. When the event is dispatched, your listener is called and passed the domain object (which is a Java entity). Entity lifecycle events can be costly and you may notice a change in the performance profile when loading large result sets. You can disable lifecycle events on the Template API. The following example uses the onBeforeSave method:

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

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

The AbstractCassandraEventListener has the following callback methods:

  • onBeforeSave: Called in CassandraTemplate.insert(…) and .update(…) operations before inserting or updating a row in the database.

  • onAfterSave: Called in CassandraTemplate…insert(…) and .update(…) operations after inserting or updating a row in the database.

  • onBeforeDelete: Called in CassandraTemplate.delete(…) operations before deleting row from the database.

  • onAfterDelete: Called in CassandraTemplate.delete(…) operations after deleting row from the database.

  • onAfterLoad: Called in the CassandraTemplate.select(…), .slice(…), and .stream(…) methods after each row is retrieved from the database.

  • onAfterConvert: Called in the CassandraTemplate.select(…), .slice(…), and .stream(…) methods after converting a row retrieved from the database to a POJO.

Lifecycle events are emitted only for root-level types. Complex types used as properties within an aggregate root are not subject to event publication.

14.8. Entity Callbacks

The Spring Data infrastructure provides hooks for modifying an entity before and after certain methods are invoked. Those so called EntityCallback instances provide a convenient way to check and potentially modify an entity in a callback fashioned style.
An EntityCallback looks pretty much like a specialized ApplicationListener. Some Spring Data modules publish store specific events (such as BeforeSaveEvent) that allow modifying the given entity. In some cases, such as when working with immutable types, these events can cause trouble. Also, event publishing relies on ApplicationEventMulticaster. If configuring that with an asynchronous TaskExecutor it can lead to unpredictable outcomes, as event processing can be forked onto a Thread.

Entity callbacks provide integration points with both synchronous and reactive APIs to guarantee in-order execution at well-defined checkpoints within the processing chain, returning a potentially modified entity or an reactive wrapper type.

Entity callbacks are typically separated by API type. This separation means that a synchronous API considers only synchronous entity callbacks and a reactive implementation considers only reactive entity callbacks.

The Entity Callback API has been introduced with Spring Data Commons 2.2. It is the recommended way of applying entity modifications. Existing store specific ApplicationEvents are still published before the invoking potentially registered EntityCallback instances.

14.8.1. Implementing Entity Callbacks

An EntityCallback is directly associated with its domain type through its generic type argument. Each Spring Data module typically ships with a set of predefined EntityCallback interfaces covering the entity lifecycle.

Example 112. Anatomy of an EntityCallback
@FunctionalInterface
public interface BeforeSaveCallback<T> extends EntityCallback<T> {

  /**
   * Entity callback method invoked before a domain object is saved.
   * Can return either the same or a modified instance.
   *
   * @return the domain object to be persisted.
   */
  T onBeforeSave(T entity <2>, String collection <3>); (1)
}
1 BeforeSaveCallback specific method to be called before an entity is saved. Returns a potentially modifed instance.
2 The entity right before persisting.
3 A number of store specific arguments like the collection the entity is persisted to.
Example 113. Anatomy of a reactive EntityCallback
@FunctionalInterface
public interface ReactiveBeforeSaveCallback<T> extends EntityCallback<T> {

  /**
   * Entity callback method invoked on subscription, before a domain object is saved.
   * The returned Publisher can emit either the same or a modified instance.
   *
   * @return Publisher emitting the domain object to be persisted.
   */
  Publisher<T> onBeforeSave(T entity <2>, String collection <3>); (1)
}
1 BeforeSaveCallback specific method to be called on subscription, before an entity is saved. Emits a potentially modifed instance.
2 The entity right before persisting.
3 A number of store specific arguments like the collection the entity is persisted to.
Optional entity callback parameters are defined by the implementing Spring Data module and inferred from call site of EntityCallback.callback().

Implement the interface suiting your application needs like shown in the example below:

Example 114. Example BeforeSaveCallback
class DefaultingEntityCallback implements BeforeSaveCallback<Person>, Ordered {      (2)

  @Override
  public Object onBeforeSave(Person entity, String collection) {                   (1)

    if(collection == "user") {
        return // ...
    }

    return // ...
  }

  @Override
  public int getOrder() {
    return 100;                                                                  (2)
  }
}
1 Callback implementation according to your requirements.
2 Potentially order the entity callback if multiple ones for the same domain type exist. Ordering follows lowest precedence.

14.8.2. Registering Entity Callbacks

EntityCallback beans are picked up by the store specific implementations in case they are registered in the ApplicationContext. Most template APIs already implement ApplicationContextAware and therefore have access to the ApplicationContext

The following example explains a collection of valid entity callback registrations:

Example 115. Example EntityCallback Bean registration
@Order(1)                                                           (1)
@Component
class First implements BeforeSaveCallback<Person> {

  @Override
  public Person onBeforeSave(Person person) {
    return // ...
  }
}

@Component
class DefaultingEntityCallback implements BeforeSaveCallback<Person>,
                                                           Ordered { (2)

  @Override
  public Object onBeforeSave(Person entity, String collection) {
    // ...
  }

  @Override
  public int getOrder() {
    return 100;                                                  (2)
  }
}

@Configuration
public class EntityCallbackConfiguration {

    @Bean
    BeforeSaveCallback<Person> unorderedLambdaReceiverCallback() {   (3)
        return (BeforeSaveCallback<Person>) it -> // ...
    }
}

@Component
class UserCallbacks implements BeforeConvertCallback<User>,
                                        BeforeSaveCallback<User> {   (4)

  @Override
  public Person onBeforeConvert(User user) {
    return // ...
  }

  @Override
  public Person onBeforeSave(User user) {
    return // ...
  }
}
1 BeforeSaveCallback receiving its order from the @Order annotation.
2 BeforeSaveCallback receiving its order via the Ordered interface implementation.
3 BeforeSaveCallback using a lambda expression. Unordered by default and invoked last. Note that callbacks implemented by a lambda expression do not expose typing information hence invoking these with a non-assignable entity affects the callback throughput. Use a class or enum to enable type filtering for the callback bean.
4 Combine multiple entity callback interfaces in a single implementation class.

14.8.3. Store specific EntityCallbacks

Spring Data for Apache Cassandra uses the EntityCallback API for its auditing support and reacts on the following callbacks.

Table 10. Supported Entity Callbacks
Callback Method Description Order

Reactive/BeforeConvertCallback

onBeforeConvert(T entity, CqlIdentifier tableName)

Invoked before a domain object is converted to com.datastax.driver.core.Statement.

Ordered.LOWEST_PRECEDENCE

Reactive/AuditingEntityCallback

onBeforeConvert(Object entity, CqlIdentifier tableName)

Marks an auditable entity created or modified

100

Reactive/BeforeSaveCallback

onBeforeSave(T entity, CqlIdentifier tableName, Statement statement)

Invoked before a domain object is saved.
Can modify the target, to be persisted, com.datastax.driver.core.Statement containing all mapped entity information.

Ordered.LOWEST_PRECEDENCE

15. Kotlin Support

Kotlin is a statically typed language that targets the JVM (and other platforms) which allows writing concise and elegant code while providing excellent interoperability with existing libraries written in Java.

Spring Data provides first-class support for Kotlin and lets developers write Kotlin applications almost as if Spring Data was a Kotlin native framework.

The easiest way to build a Spring application with Kotlin is to leverage Spring Boot and its dedicated Kotlin support. This comprehensive tutorial will teach you how to build Spring Boot applications with Kotlin using start.spring.io.

15.1. Requirements

Spring Data supports Kotlin 1.3 and requires kotlin-stdlib (or one of its variants, such as kotlin-stdlib-jdk8) and kotlin-reflect to be present on the classpath. Those are provided by default if you bootstrap a Kotlin project via start.spring.io.

15.2. Null Safety

One of Kotlin’s key features is null safety, which cleanly deals with null values at compile time. This makes applications safer through nullability declarations and the expression of “value or no value” semantics without paying the cost of wrappers, such as Optional. (Kotlin allows using functional constructs with nullable values. See this comprehensive guide to Kotlin null safety.)

Although Java does not let you express null safety in its type system, Spring Data API is annotated with JSR-305 tooling friendly annotations declared in the org.springframework.lang package. By default, types from Java APIs used in Kotlin are recognized as platform types, for which null checks are relaxed. Kotlin support for JSR-305 annotations and Spring nullability annotations provide null safety for the whole Spring Data API to Kotlin developers, with the advantage of dealing with null related issues at compile time.

See Null Handling of Repository Methods how null safety applies to Spring Data Repositories.

You can configure JSR-305 checks by adding the -Xjsr305 compiler flag with the following options: -Xjsr305={strict|warn|ignore}.

For Kotlin versions 1.1+, the default behavior is the same as -Xjsr305=warn. The strict value is required take Spring Data API null-safety into account. Kotlin types inferred from Spring API but should be used with the knowledge that Spring API nullability declaration could evolve, even between minor releases and that more checks may be added in the future.
Generic type arguments, varargs, and array elements nullability are not supported yet, but should be in an upcoming release.

15.3. Object Mapping

See Kotlin support for details on how Kotlin objects are materialized.

15.4. Extensions

Kotlin extensions provide the ability to extend existing classes with additional functionality. Spring Data Kotlin APIs use these extensions to add new Kotlin-specific conveniences to existing Spring APIs.

Keep in mind that Kotlin extensions need to be imported to be used. Similar to static imports, an IDE should automatically suggest the import in most cases.

For example, Kotlin reified type parameters provide a workaround for JVM generics type erasure, and Spring Data provides some extensions to take advantage of this feature. This allows for a better Kotlin API.

To retrieve a list of SWCharacter objects in Java, you would normally write the following:

Flux<SWCharacter> characters = template.query(SWCharacter.class).inTable("star-wars").all()

With Kotlin and the Spring Data extensions, you can instead write the following:

val characters = template.query<SWCharacter>().inTable("star-wars").all()
// or (both are equivalent)
val characters : Flux<SWCharacter> = template.query().inTable("star-wars").all()

As in Java, characters in Kotlin is strongly typed, but Kotlin’s clever type inference allows for shorter syntax.

Spring Data for Apache Cassandra provides the following extensions:

  • Reified generics support for CassandraOperations (including async and reactive variants), CqlOperations (including async and reactive variants)FluentCassandraOperations, ReactiveFluentCassandraOperations, Criteria, and Query.

  • Coroutines extensions for ReactiveFluentCassandraOperations.

15.5. Coroutines

Kotlin Coroutines are lightweight threads allowing to write non-blocking code imperatively. On language side, suspend functions provides an abstraction for asynchronous operations while on library side kotlinx.coroutines provides functions like async { } and types like Flow.

Spring Data modules provide support for Coroutines on the following scope:

  • Deferred and Flow return values support in Kotlin extensions

15.5.1. Dependencies

Coroutines support is enabled when kotlinx-coroutines-core, kotlinx-coroutines-reactive and kotlinx-coroutines-reactor dependencies are in the classpath:

Example 116. Dependencies to add in Maven pom.xml
<dependency>
  <groupId>org.jetbrains.kotlinx</groupId>
  <artifactId>kotlinx-coroutines-core</artifactId>
</dependency>

<dependency>
  <groupId>org.jetbrains.kotlinx</groupId>
  <artifactId>kotlinx-coroutines-reactive</artifactId>
</dependency>

<dependency>
  <groupId>org.jetbrains.kotlinx</groupId>
  <artifactId>kotlinx-coroutines-reactor</artifactId>
</dependency>
Supported versions 1.3.0 and above.

15.5.2. How Reactive translates to Coroutines?

For return values, the translation from Reactive to Coroutines APIs is the following:

  • fun handler(): Mono<Void> becomes suspend fun handler()

  • fun handler(): Mono<T> becomes suspend fun handler(): T or suspend fun handler(): T? depending on if the Mono can be empty or not (with the advantage of being more statically typed)

  • fun handler(): Flux<T> becomes fun handler(): Flow<T>

Flow is Flux equivalent in Coroutines world, suitable for hot or cold stream, finite or infinite streams, with the following main differences:

  • Flow is push-based while Flux is push-pull hybrid

  • Backpressure is implemented via suspending functions

  • Flow has only a single suspending collect method and operators are implemented as extensions

  • Operators are easy to implement thanks to Coroutines

  • Extensions allow adding custom operators to Flow

  • Collect operations are suspending functions

  • map operator supports asynchronous operation (no need for flatMap) since it takes a suspending function parameter

Read this blog post about Going Reactive with Spring, Coroutines and Kotlin Flow for more details, including how to run code concurrently with Coroutines.

15.5.3. Repositories

Here is an example of a Coroutines repository:

interface CoroutineRepository : CoroutineCrudRepository<User, String> {

    suspend fun findOne(id: String): User

    fun findByFirstname(firstname: String): Flow<User>

    suspend fun findAllByFirstname(id: String): List<User>
}

Coroutines repositories are built on reactive repositories to expose the non-blocking nature of data access through Kotlin’s Coroutines. Methods on a Coroutines repository can be backed either by a query method or a custom implementation. Invoking a custom implementation method propagates the Coroutines invocation to the actual implementation method if the custom method is suspend-able without requiring the implementation method to return a reactive type such as Mono or Flux.

Note that depending on the method declaration the coroutine context may or may not be available. To retain access to the context, either declare your method using suspend or return a type that enables context propagation such as Flow.

  • suspend fun findOne(id: String): User: Retrieve the data once and synchronously by suspending.

  • fun findByFirstname(firstname: String): Flow<User>: Retrieve a stream of data. The Flow is created eagerly while data is fetched upon Flow interaction (Flow.collect(…)).

  • fun getUser(): User: Retrieve data once blocking the thread and without context propagation. This should be avoided.

Coroutines repositories are only discovered when the repository extends the CoroutineCrudRepository interface.

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 11. 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 a data store via the Spring Data repository infrastructure.[1]

Table 12. 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 method subject keywords

The following table lists the subject keywords generally supported by the Spring Data repository query derivation mechanism to express the predicate. 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 13. Query subject keywords
Keyword Description

find…By, read…By, get…By, query…By, search…By, stream…By

General query method returning typically the repository type, a Collection or Streamable subtype or a result wrapper such as Page, GeoResults or any other store-specific result wrapper. Can be used as findBy…, findMyDomainTypeBy… or in combination with additional keywords.

exists…By

Exists projection, returning typically a boolean result.

count…By

Count projection returning a numeric result.

delete…By, remove…By

Delete query method returning either no result (void) or the delete count.

…First<number>…, …Top<number>…

Limit the query results to the first <number> of results. This keyword can occur in any place of the subject between find (and the other keywords) and by.

…Distinct…

Use a distinct query to return only unique results. Consult the store-specific documentation whether that feature is supported. This keyword can occur in any place of the subject between find (and the other keywords) and by.

Supported query method predicate keywords and modifiers

The following table lists the predicate 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 14. Query predicate 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_EMPTY

IsEmpty, Empty

IS_NOT_EMPTY

IsNotEmpty, NotEmpty

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

In addition to filter predicates, the following list of modifiers is supported:

Table 15. Query predicate modifier keywords
Keyword Description

IgnoreCase, IgnoringCase

Used with a predicate keyword for case-insensitive comparison.

AllIgnoreCase, AllIgnoringCase

Ignore case for all suitable properties. Used somewhere in the query method predicate.

OrderBy…

Specify a static sorting order followed by the property path and direction (e. g. OrderByFirstnameAscLastnameDesc).

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. Some store modules may define their own result wrapper types.
Table 16. Query return types
Return type Description

void

Denotes no return value.

Primitives

Java primitives.

Wrapper types

Java wrapper types.

T

A 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 Vavr Option type. Semantically the same behavior as Java 8’s Optional, described earlier.

Stream<T>

A Java 8 Stream.

Streamable<T>

A convenience extension of Iterable that directy exposes methods to stream, map and filter results, concatenate them etc.

Types that implement Streamable and take a Streamable constructor or factory method argument

Types that expose a constructor or ….of(…)/….valueOf(…) factory method taking a Streamable as argument. See Returning Custom Streamable Wrapper Types for details.

Vavr Seq, List, Map, Set

Vavr collection types. See Support for Vavr Collections for details.

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.

Slice<T>

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.

Appendix E: Migration Guides

Migration Guide from Spring Data Cassandra 1.x to 2.x

Spring Data for Apache Cassandra 2.0 introduces a set of breaking changes when upgrading from earlier versions:

  • Merged the spring-cql and spring-data-cassandra modules into a single module.

  • Separated asynchronous and synchronous operations in CqlOperations and CassandraOperations into dedicated interfaces and templates.

  • Revised the CqlTemplate API to align with JdbcTemplate.

  • Removed the CassandraOperations.selectBySimpleIds method.

  • Used better names for CassandraRepository.

  • Removed SD Cassandra ConsistencyLevel and RetryPolicy types in favor of DataStax ConsistencyLevel and RetryPolicy types.

  • Refactored CQL specifications to value objects and configurators.

  • Refactored QueryOptions to be immutable objects.

  • Refactored CassandraPersistentProperty to single-column.

Deprecations

  • Deprecated QueryOptionsBuilder.readTimeout(long, TimeUnit) in favor of QueryOptionsBuilder.readTimeout(Duration).

  • Deprecated CustomConversions in favor of CassandraCustomConversions.

  • Deprecated BasicCassandraMappingContext in favor of CassandraMappingContext.

  • Deprecated o.s.d.c.core.cql.CachedPreparedStatementCreator in favor of o.s.d.c.core.cql.support.CachedPreparedStatementCreator.

  • Deprecated CqlTemplate.getSession() in favor of getSessionFactory().

  • Deprecated CqlIdentifier.cqlId(…) and KeyspaceIdentifier.ksId(…) in favor of the .of(…) methods.

  • Deprecated constructors of QueryOptions in favor of their builders.

  • Deprecated TypedIdCassandraRepository in favor of CassandraRepository

Merged Spring CQL and Spring Data Cassandra Modules

Spring CQL and Spring Data Cassandra are now merged into a single module. The standalone spring-cql module is no longer available. You can find all types merged into spring-data-cassandra. The following listing shows how to include spring-data-cassandra in your maven dependencies:

<dependencies>

  <dependency>
    <groupId>org.springframework.data</groupId>
    <artifactId>spring-data-cassandra</artifactId>
    <version>4.1.0-M3</version>
  </dependency>

</dependencies>

With the merge, we merged all CQL packages into Spring Data Cassandra:

  • Moved o.s.d.cql into o.s.d.cassandra.core.cql.

  • Merged o.s.d.cql with o.s.d.cassandra.config and flattened the XML and Java subpackages.

  • Moved CassandraExceptionTranslator and CqlExceptionTranslator to o.s.d.c.core.cql.

  • Moved Cassandra exceptions o.s.d.c.support.exception to o.s.d.cassandra.

  • Moved o.s.d.c.convert to o.s.d.c.core.convert (affects converters).

  • Moved o.s.d.c.mapping to o.s.d.c.core.mapping (affects mapping annotations).

  • Moved MapId from o.s.d.c.repository to o.s.d.c.core.mapping.

Revised CqlTemplate/CassandraTemplate

We split CqlTemplate and CassandraTemplate in three ways:

  • CassandraTemplate is no longer a CqlTemplate but uses an instance that allows reuse and fine-grained control over fetch size, consistency levels, and retry policies. You can obtain the CqlOperations through CassandraTemplate.getCqlOperations(). Because of the change, dependency injection of CqlTemplate requires additional bean setup.

  • CqlTemplate now reflects basic CQL operations instead of mixing high-level and low-level API calls (such as count(…) versus execute(…)) and the reduced method set is aligned with Spring Frameworks’s JdbcTemplate with its convenient callback interfaces.

  • Asynchronous methods are re-implemented on AsyncCqlTemplate and AsyncCassandraTemplate by using ListenableFuture. We removed Cancellable and the various async callback listeners. ListenableFuture is a flexible approach and allows transition into a CompletableFuture.

Removed CassandraOperations.selectBySimpleIds()

The method was removed because it did not support complex IDs. The newly introduced query DSL allows mapped and complex id’s for single column Id’s, as the following example shows:

cassandraTemplate.select(Query.query(Criteria.where("id").in(…)), Person.class)

Better names for CassandraRepository

We renamed CassandraRepository and TypedIdCassandraRepository to align Spring Data Cassandra naming with other Spring Data modules:

  • Renamed CassandraRepository to MapIdCassandraRepository

  • Renamed TypedIdCassandraRepository to CassandraRepository

  • Introduced TypedIdCassandraRepository, extending CassandraRepository as a deprecated type to ease migration

Removed SD Cassandra ConsistencyLevel and RetryPolicy types in favor of DataStax ConsistencyLevel and RetryPolicy types

Spring Data Cassandra ConsistencyLevel and RetryPolicy have been removed. Please use the types provided by the DataStax driver.

The Spring Data Cassandra types restricted usage of available features provided in and allowed by the Cassandra native driver. As a result, the Spring Data Cassandra’s types required an update each time newer functionality was introduced by the driver.

Refactored CQL Specifications to Value Objects and Configurators

As much as possible, CQL specification types are now value types (such as FieldSpecification, AlterColumnSpecification), and objects are constructed by static factory methods. This allows immutability for simple value objects. Configurator objects (such as AlterTableSpecification) that operate on mandatory properties (such as a table name or keyspace name) are initially constructed through a a static factory method and allow further configuration until the desired state is created.

Refactored QueryOptions to be Immutable Objects

QueryOptions and WriteOptions are now immutable and can be created through builders. Methods accepting QueryOptions enforce non-null objects, which are available from static empty() factory methods. The following example shows how to use QueryOptions.builder():

QueryOptions queryOptions = QueryOptions.builder()
    .consistencyLevel(ConsistencyLevel.ANY)
    .retryPolicy(FallthroughRetryPolicy.INSTANCE)
    .readTimeout(Duration.ofSeconds(10))
    .fetchSize(10)
    .tracing(true)
    .build();

Refactored CassandraPersistentProperty to Single-column

This change affects You only if you operate directly on the mapping model.

CassandraPersistentProperty allowed previously multiple column names to be bound for composite primary key use. Columns of a CassandraPersistentProperty are now reduced to a single column. Resolved composite primary keys map to a class through MappingContext.getRequiredPersistentEntity(…).

Migration Guide from Spring Data Cassandra 2.x to 3.x

Spring Data for Apache Cassandra 3.0 introduces a set of breaking changes when upgrading from earlier versions.

Review dependencies

Upgrading to Spring Data Cassandra requires an upgrade to the DataStax Driver version 4. Upgrading to the new driver comes with transitive dependency changes, most notably, Google Guava is bundled and shaded by the driver. Check out the DataStax Java Driver for Apache Cassandra 4 Upgrade Guide for details on the Driver-related changes.

Adapt Configuration

DataStax Java Driver 4 merges Cluster and Session objects into a single CqlSession object, therefore, all Cluster-related API was removed. The configuration was revised in large parts by removing most configuration items that were moved into DriverConfigLoader that is mostly file-based. This means that SocketOptions, AddressTranslator and many more options are configured now through other means.

If you’re using XML-based configuration, make sure to migrate all configuration files from the cql namespace (http://www.springframework.org/schema/cql https://www.springframework.org/schema/cql/spring-cql.xsd) to the cassandra namespace (http://www.springframework.org/schema/data/cassandra https://www.springframework.org/schema/data/cassandra/spring-cassandra.xsd).

To reflect the change in configuration builders, ClusterBuilderConfigurer was renamed to SessionBuilderConfigurer accepting now CqlSessionBuilder instead of the Cluster.Builder. Make sure to also provide the local data center in your configuration as it is required to properly configure load balancing.

Connectivity

The configuration elements for Cluster (cassandra:cluster) and Session (cassandra:session) were merged into a single CqlSession (cassandra:session) element that configures both, the keyspace and endpoints.

With the upgrade, schema support was moved to a new namespace element: cassandra:session-factory that provides a SessionFactory bean.

Example 117. Cluster, Session and Schema Configuration in version 2:
<cassandra:cluster contact-points="localhost" port="9042">
  <cassandra:keyspace action="CREATE_DROP" name="mykeyspace" />
</cassandra:cluster>

<cassandra:session keyspace-name="mykeyspace" schema-action="CREATE">
  <cassandra:startup-cql>CREATE TABLE …</cassandra:startup-cql>
</cassandra:session>
Example 118. Session and Schema Configuration in version 3:
<cassandra:session contact-points="localhost" port="9042" keyspace="mykeyspace" local-datacenter="datacenter1">
  <cassandra:keyspace action="CREATE_DROP" name="mykeyspace" />
</cassandra:session>

<cassandra:session-factory schema-action="CREATE">
  <cassandra:script location="classpath:/schema.cql"/>
</cassandra:session-factory>
Spring Data Cassandra 3.0 no longer registers default Mapping Context, Context and Template API beans when using XML namespace configuration. The defaulting should be applied on application or Spring Boot level.

Template API

Spring Data for Apache Cassandra encapsulates most of the changes that come with the driver upgrade as the Template API and repository support if your application mainly interacts with mapped entities or primitive Java types.

We generally recommend to create CqlTemplate and CassandraTemplate objects by using SessionFactory as the factory usage allows synchronization for schema creation and introduces a level of flexibility when working with multiple databases.

Example 119. Template API configuration in version 2:
<cql:template session-ref="…" />

<cassandra:template session-ref="…" cassandra-converter-ref="…"/>
Example 120. Template API configuration in version 3:
<cassandra:session-factory />

<cassandra:cql-template session-factory-ref="…" />

<cassandra:template session-factory-ref="…" cassandra-converter-ref="…"/>

You will have to adapt your code in all places, where you use DataStax driver API directly. Typical cases include:

  • Implementations of ResultSetExtractor

  • Implementations of RowCallbackHandler

  • Implementations of RowMapper

  • Implementations of PreparedStatementCreator including async and reactive variants

  • Calls to CqlTemplate.queryForResultSet(…)

  • Calling methods that accept Statement

Changes in AsyncCqlTemplate

DataStax driver 4 has changed the result type of queries that are run asynchronously. To reflect these changes, you need to adapt your code that provides:

  • Implementations of AsyncSessionCallback

  • Implementations of AsyncPreparedStatementCreator

Result set extraction requires a new interface for DataStax' AsyncResultSet. AsyncCqlTemplate now uses AsyncResultSetExtractor in places where it used previously ResultSetExtractor. Note that AsyncResultSetExtractor.extractData(…) returns a Future instead of a scalar object so a migration of code comes with the possibility to use fully non-blocking code in the extractor.

Data model migrations

Your data model may require updates if you use the following features:

  • @CassandraType

  • forceQuote in @Table, @Column, @PrimaryKeyColumn, @PrimaryKey and @UserDefinedType

  • Properties using java.lang.Date

  • Properties using UDTValue or TupleValue

@CassandraType

DataStax driver 4 no longer ships with a Name enumeration to describe the Cassandra type. We decided to re-introduce the enumeration with CassandraType.Name. Make sure to update your imports to use the newly introduced replacement type.

Force Quote

This flag is now deprecated, and we recommend not to use it any longer. Spring Data for Apache Cassandra internally uses the driver’s CqlIdentifier that ensures quoting where it’s required.

Property Types

DataStax driver 4 no longer uses java.lang.Date. Please upgrade your data model to use java.time.LocalDateTime. Please also migrate raw UDT and tuple types to the new driver types UdtValue respective TupleValue.

Other changes

  • Driver’s ConsistencyLevel constant class was removed and reintroduced as DefaultConsistencyLevel. @Consistency was adapted to DefaultConsistencyLevel.

  • RetryPolicy on QueryOptions and …CqlTemplate types was removed without replacement.

  • Drivers’s PagingState type was removed. Paging state now uses ByteBuffer.

  • SimpleUserTypeResolver accepts CqlSession instead of Cluster.

  • SimpleTupleTypeFactory was migrated to enum. SimpleTupleTypeFactory.INSTANCE no longer requires a Cluster/CqlSession context.

  • Introduction of StatementBuilder to functionally build statements as the QueryBuilder API uses immutable statement types.

  • Session bean renamed from session to cassandraSession and SessionFactory bean renamed from sessionFactory to cassandraSessionFactory.

  • ReactiveSession bean renamed from reactiveSession to reactiveCassandraSession and ReactiveSessionFactory bean renamed from reactiveSessionFactory to reactiveCassandraSessionFactory.

  • ReactiveSessionFactory.getSession() now returns a Mono<ReactiveSession>. Previously it returned just ReactiveSession.

  • Data type resolution was moved into ColumnTypeResolver so all DataType-related methods were moved from CassandraPersistentEntity/CassandraPersistentProperty into ColumnTypeResolver (affected methods are MappingContext.getDataType(…), CassandraPersistentProperty.getDataType(), CassandraPersistentEntity.getUserType(), and CassandraPersistentEntity.getTupleType()).

  • Schema creation was moved from MappingContext to SchemaFactory (affected methods are CassandraMappingContext.getCreateTableSpecificationFor(…), CassandraMappingContext.getCreateIndexSpecificationsFor(…), and CassandraMappingContext.getCreateUserTypeSpecificationFor(…)).

Deprecations

  • CassandraCqlSessionFactoryBean, use CqlSessionFactoryBean instead.

  • KeyspaceIdentifier and CqlIdentifier, use com.datastax.oss.driver.api.core.CqlIdentifier instead.

  • CassandraSessionFactoryBean, use CqlSessionFactoryBean instead.

  • AbstractCqlTemplateConfiguration, use AbstractSessionConfiguration instead.

  • AbstractSessionConfiguration.getClusterName(), use AbstractSessionConfiguration.getSessionName() instead.

  • CodecRegistryTupleTypeFactory, use SimpleTupleTypeFactory instead.

  • Spring Data’s CqlIdentifier, use the driver CqlIdentifier instead.

  • forceQuote attributes as quoting is no longer required. CqlIdentifier properly escapes reserved keywords and takes care of case-sensitivity.

  • fetchSize on QueryOptions and …CqlTemplate types was deprecated, use pageSize instead

  • CassandraMappingContext.setUserTypeResolver(…), CassandraMappingContext.setCodecRegistry(…), and CassandraMappingContext.setCustomConversions(…): Configure these properties on CassandraConverter.

  • TupleTypeFactory and CassandraMappingContext.setTupleTypeFactory(…): TupleTypeFactory is no longer used as the Cassandra driver ships with a DataTypes.tupleOf(…) factory method.

  • Schema creation via CqlSessionFactoryBean (cassandra:session) is deprecated. Keyspace creation via CqlSessionFactoryBean (cassandra:session) is not affected.

Removals

Configuration API

  • PoolingOptionsFactoryBean

  • SocketOptionsFactoryBean

  • CassandraClusterFactoryBean

  • CassandraClusterParser

  • CassandraCqlClusterFactoryBean

  • CassandraCqlClusterParser

  • CassandraCqlSessionParser

  • AbstractClusterConfiguration

  • ClusterBuilderConfigurer (use SessionBuilderConfigurer instead

Utilities

  • GuavaListenableFutureAdapter

  • QueryOptions and WriteOptions constructor taking ConsistencyLevel and RetryPolicy arguments. Use the builder in conjunction of execution profiles as replacement.

  • CassandraAccessor.setRetryPolicy(…) and ReactiveCqlTemplate.setRetryPolicy(…) methods. Use execution profiles as replacement.

Namespace support

Additions

Configuration API

  • CqlSessionFactoryBean

  • InitializeKeyspaceBeanDefinitionParser

  • SessionFactoryFactoryBean including schema creation via KeyspacePopulator

  • KeyspacePopulator and SessionFactoryInitializer to initialize a keyspace

Namespace support

  • cassandra:cluster (endpoint properties merged to cassandra:session)

  • cassandra:initialize-keyspace namespace support

  • cassandra:session-factory with cassandra:script support

Migration Guide from Spring Data Cassandra 3.x to 4.x

Spring Data for Apache Cassandra 4.0 introduces a set of breaking changes when upgrading from earlier versions.

Asynchronous Template API

With the deprecation of ListenableFuture, AsyncCqlOperations and AsyncCassandraOperations and their dependant classes were migrated to CompletableFuture. If your application heavily depends on ListenableFuture and you cannot easily migrate to CompletableFuture then we suggest switching to the legacy Async…Operations types in the legacy subpackage. That is org.springframework.data.cassandra.core.cql.legacy for AsyncCqlOperations and org.springframework.data.cassandra.core.legacy for AsyncCassandraOperations.