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Table of Contents


This reference documentation describes the general usage of the Spring Data Couchbase library.

1. Project Information

2. Migrating from Spring Data Couchbase 1.x to 2.x

This chapter is a quick reference of what major changes have been introduced in 2.0.x and gives a high-level overview of things to consider when migrating.

2.1. Configuration

The configuration, xml schema, etc…​ has changed to take the evolution of the 2.x SDK API into account.

Where a single CouchbaseClient bean was previously the only bean declarable, you can now declare a Cluster bean (<couchbase:cluster>), one or more Bucket beans (<couchbase:bucket>) and even tune the SDK via a CouchbaseEnvironment bean (<couchbase:env>). All of these can also be created via Java Config method by extending AbstractCouchbaseConfig.

The cluster bean lists the nodes to connect through (and references the environment bean if tuning is necessary) while the bucket beans map to bucket names and passwords and actually opens the connections internally.

You can define more beans that are used for internal configuration of the Spring Data Couchbase module (MappingContext, CouchbaseConverter, TranslationService, …​).

For more information, see Installation & Configuration.

2.2. Repository queries

The view-backed query method has evolved and support for N1QL has been introduced. As a result, there are now 4 ways of doing repository queries:

  • Simple View query (to return all elements emitted by a view) - @View annotated without viewName

  • Intermediate View query by query derivation (to provide some criteria for the view) @View annotated with viewName

  • N1QL with explicit statements inline - @Query annotated with value

  • N1QL query derivation - @Query annotated without value / no annotation (default)

View backed queries are associated with the @View annotation, while N1QL backed queries are associated with the @Query annotation.

N1QL query derivation is now the default query method (and there the @Query annotation is optional).

See N1QL based querying and Backing Views for more information.

2.3. Backing views and view query changes

The all view is still backing most CRUD operations, but custom repository methods are now by default backed by N1QL.

To instead back them with views, use the @View annotation explicitly.

Without a viewName specified, the view will be guessed from method name (stripping count or find prefix). Otherwise, query derivation will be used to parameterize the view query from the method name and parameters.

2.3.1. Passing a ViewQuery object as a parameter to a custom repository method

This behavior has been removed and the recommended approach is now to either use query derivation (if the query parameters are simple enough) or Adding custom behavior to single repositories.

For instance, for a view emitting user lastNames, the following:

List<User> findByLastname(ViewQuery.from("","").key("test").limit(3));

is to be replaced by the (more flexible):

List<User> findFirst3ByLastnameEquals(String lastName);

2.3.2. Reduce in views

Reduce is now supported in view-based querying.

It can be triggered by prefixing the method name with count instead of find. For example: countByLastnameContains(String word) instead of findByLastnameContains(String word).

Alternatively, it can be explicitly be activated by setting reduce = true on the @View annotation.

Be sure to construct your view correctly:

  • specify a reduce function that matches the method return type, which can be anything, eg. long or JSON object

  • emit a simple key (not null nor a compound key).

  • emit a value suitable for the reduce to work (typically _count doesn’t need any particular value, but _stats will need a numerical value, in addition to the key).

Reference Documentation

3. Installation & Configuration

This chapter describes the common installation and configuration steps needed when working with the library.

3.1. Installation

All versions intended for production use are distributed across Maven Central and the Spring release repository. As a result, the library can be included like any other maven dependency:

Example 1. Including the dependency through maven

This will pull in several dependencies, including the underlying Couchbase Java SDK, common Spring dependencies and also Jackson as the JSON mapping infrastructure.

You can also grab snapshots from the spring snapshot repository and milestone releases from the milestone repository. Here is an example on how to use the current SNAPSHOT dependency:

Example 2. Using a snapshot version

  <name>Spring Snapshot Repository</name>

Once you have all needed dependencies on the classpath, you can start configuring it. Both Java and XML config are supported. The next sections describe both approaches in detail.

3.2. Annotation-based Configuration ("JavaConfig")

The annotation based configuration approach is getting more and more popular. It allows you to get rid of XML configuration and treat configuration as part of your code directly. To get started, all you need to do is subclcass the AbstractCouchbaseConfiguration and implement the abstract methods.

Please make sure to have cglib support in the classpath so that the annotation based configuration works.

Example 3. Extending the AbstractCouchbaseConfiguration
public class Config extends AbstractCouchbaseConfiguration {

    protected List<String> getBootstrapHosts() {
        return Collections.singletonList("");

    protected String getBucketName() {
        return "beer-sample";

    protected String getBucketPassword() {
        return "";

All you need to provide is a list of Couchbase nodes to bootstrap into (without any ports, just the IP address or hostname). Please note that while one host is sufficient in development, it is recommended to add 3 to 5 bootstrap nodes here. Couchbase will pick up all nodes from the cluster automatically, but it could be the case that the only node you’ve provided is experiencing issues while you are starting the application.

The bucketName and password should be the same as configured in Couchbase Server itself. In the example given, we are connecting to the beer-sample bucket which is one of the sample buckets shipped with Couchbase Server and has no password set by default.

Depending on how your environment is set up, the configuration will be automatically picked up by the context or you need to instantiate your own one. How to manage configurations is not in scope of this manual, please refer to the spring documentation for more information on that topic.

Additionally, the SDK environment can be tuned by overriding the getEnvironment() method to return a properly tuned CouchbaseEnvironment.

While not immediately obvious, much more things can be customized and overridden as custom beans from this configuration (for example repositories, query consistency, validation and custom converters).

If you use SyncGateway and CouchbaseMobile, you may run into problem with fields prefixed by _. Since Spring Data Couchbase by default stores the type information as a _class attribute this can be problematic. Override typeKey() (for example to return MappingCouchbaseConverter.TYPEKEY_SYNCGATEWAY_COMPATIBLE) to change the name of said attribute.
For generated queries, if you want strong consistency (at the expense of performance), you can override getDefaultConsistency() and return Consistency.READ_YOUR_OWN_WRITES.

3.3. XML-based Configuration

The library provides a custom namespace that you can use in your XML configuration:

Example 4. Basic XML configuration
<?xml version="1.0" encoding="UTF-8"?>
<beans:beans xmlns:beans="http://www.springframework.org/schema/beans"


    <!-- This is needed to probe the server for N1QL support -->
    <!-- Can be either cluster credentials or a bucket credentials -->
    <couchbase:clusterInfo login="beer-sample" password=""/>

    <couchbase:bucket bucketName="beer-sample" bucketPassword=""/>

This code is equivalent to the java configuration approach shown above. You can customize the SDK CouchbaseEnvironment via the <couchbase:env/> tag, that supports most tuning parameters as attributes. It is also possible to configure templates and repositories, which is shown in the appropriate sections.

The XML configuration must include the clusterInfo credentials, in order to be able to detect N1QL feature.

If you start your application, you should see Couchbase INFO level logging in the logs, indicating that the underlying Couchbase Java SDK is connecting to the database. If any errors are reported, make sure that the given credentials and host information are correct.

4. Modeling Entities

This chapter describes how to model Entities and explains their counterpart representation in Couchbase Server itself.

4.1. Documents and Fields

All entities should be annotated with the @Document annotation.

Also, every field in the entity should be annotated with the @Field annotation from the Couchbase SDK. While this is - strictly speaking - optional, it helps to reduce edge cases and clearly shows the intent and design of the entity. It can also be used to store the field under a different name.

There is also a special @Id annotation which needs to be always in place. Best practice is to also name the property id.

Both the Couchbase SDK and Spring Data define their own @Id annotation. Either can be used (the Spring Data one will get priority if both are found on different fields).

Here is a very simple User entity:

Example 5. A simple Document with Fields
import com.couchbase.client.java.repository.annotation.Id;
import com.couchbase.client.java.repository.annotation.Field;
import org.springframework.data.couchbase.core.mapping.Document;

public class User {

    private String id;

    private String firstname;

    private String lastname;

    public User(String id, String firstname, String lastname) {
        this.id = id;
        this.firstname = firstname;
        this.lastname = lastname;

    public String getId() {
        return id;

    public String getFirstname() {
        return firstname;

    public String getLastname() {
        return lastname;

Couchbase Server supports automatic expiration for documents. The library implements support for it through the @Document annotation. You can set a expiry value which translates to the number of seconds until the document gets removed automatically. If you want to make it expire in 10 seconds after mutation, set it like @Document(expiry = 10).

If you want a different representation of the field name inside the document in contrast to the field name used in your entity, you can set a different name on the @Field annotation. For example if you want to keep your documents small you can set the firstname field to @Field("fname"). In the JSON document, you’ll see {"fname": ".."} instead of {"firstname": ".."}.

The @Id annotation needs to be present because every document in Couchbase needs a unique key. This key needs to be any string with a length of maximum 250 characters. Feel free to use whatever fits your use case, be it a UUID, an email address or anything else.

4.2. Datatypes and Converters

The storage format of choice is JSON. It is great, but like many data representations it allows less datatypes than you could express in Java directly. Therefore, for all non-primitive types some form of conversion to and from supported types needs to happen.

For the following entity field types, you don’t need to add special handling:

Table 1. Primitive Types
Java Type JSON Representation


















Ignored on write

Since JSON supports objects ("maps") and lists, Map and List types can be converted naturally. If they only contain primitive field types from the last paragraph, you don’t need to add special handling too. Here is an example:

Example 6. A Document with Map and List
public class User {

    private String id;

    private List<String> firstnames;

    private Map<String, Integer> childrenAges;

    public User(String id, List<String> firstnames, Map<String, Integer> childrenAges) {
        this.id = id;
        this.firstnames = firstnames;
        this.childrenAges = childrenAges;


Storing a user with some sample data could look like this as a JSON representation:

Example 7. A Document with Map and List - JSON
    "_class": "foo.User",
    "childrenAges": {
        "Alice": 10,
        "Bob": 5
    "firstnames": [

You don’t need to break everything down to primitive types and Lists/Maps all the time. Of course, you can also compose other objects out of those primitive values. Let’s modify the last example so that we want to store a List of Children:

Example 8. A Document with composed objects
public class User {

    private String id;

    private List<String> firstnames;

    private List<Child> children;

    public User(String id, List<String> firstnames, List<Child> children) {
        this.id = id;
        this.firstnames = firstnames;
        this.children = children;

    static class Child {
        private String name;
        private int age;

        Child(String name, int age) {
            this.name = name;
            this.age = age;



A populated object can look like:

Example 9. A Document with composed objects - JSON
  "_class": "foo.User",
  "children": [
      "age": 4,
      "name": "Alice"
      "age": 3,
      "name": "Bob"
  "firstnames": [

Most of the time, you also need to store a temporal value like a Date. Since it can’t be stored directly in JSON, a conversion needs to happen. The library implements default converters for Date, Calendar and JodaTime types (if on the classpath). All of those are represented by default in the document as a unix timestamp (number). You can always override the default behavior with custom converters as shown later. Here is an example:

Example 10. A Document with Date and Calendar
public class BlogPost {

    private String id;

    private Date created;

    private Calendar updated;

    private String title;

    public BlogPost(String id, Date created, Calendar updated, String title) {
        this.id = id;
        this.created = created;
        this.updated = updated;
        this.title = title;


A populated object can look like:

Example 11. A Document with Date and Calendar - JSON
  "title": "a blog post title",
  "_class": "foo.BlogPost",
  "updated": 1394610843,
  "created": 1394610843897

If you want to override a converter or implement your own one, this is also possible. The library implements the general Spring Converter pattern. You can plug in custom converters on bean creation time in your configuration. Here’s how you can configure it (in your overridden AbstractCouchbaseConfiguration):

Example 12. Custom Converters
public CustomConversions customConversions() {
    return new CustomConversions(Arrays.asList(FooToBarConverter.INSTANCE, BarToFooConverter.INSTANCE));

public static enum FooToBarConverter implements Converter<Foo, Bar> {

    public Bar convert(Foo source) {
        return /* do your conversion here */;


public static enum BarToFooConverter implements Converter<Bar, Foo> {

    public Foo convert(Bar source) {
        return /* do your conversion here */;


There are a few things to keep in mind with custom conversions:

  • To make it unambiguous, always use the @WritingConverter and @ReadingConverter annotations on your converters. Especially if you are dealing with primitive type conversions, this will help to reduce possible wrong conversions.

  • If you implement a writing converter, make sure to decode into primitive types, maps and lists only. If you need more complex object types, use the CouchbaseDocument and CouchbaseList types, which are also understood by the underlying translation engine. Your best bet is to stick with as simple as possible conversions.

  • Always put more special converters before generic converters to avoid the case where the wrong converter gets executed.

  • For dates, reading converters should be able to read from any Number (not just Long). This is required for N1QL support.

4.3. Optimistic Locking

Couchbase Server does not support multi-document transactions or rollback. To implement optimistic locking, Couchbase uses a CAS (compare and swap) approach. When a document is mutated, the CAS value also changes. The CAS is opaque to the client, the only thing you need to know is that it changes when the content or a meta information changes too.

In other datastores, similar behavior can be achieved through an arbitrary version field with a incrementing counter. Since Couchbase supports this in a much better fashion, it is easy to implement. If you want automatic optimistic locking support, all you need to do is add a @Version annotation on a long field like this:

Example 13. A Document with optimistic locking.
public class User {

        private long version;

        // constructor, getters, setters...

If you load a document through the template or repository, the version field will be automatically populated with the current CAS value. It is important to note that you shouldn’t access the field or even change it on your own. Once you save the document back, it will either succeed or fail with a OptimisticLockingFailureException. If you get such an exception, the further approach depends on what you want to achieve application wise. You should either retry the complete load-update-write cycle or propagate the error to the upper layers for proper handling.

4.4. Validation

The library supports JSR 303 validation, which is based on annotations directly in your entities. Of course you can add all kinds of validation in your service layer, but this way its nicely coupled to your actual entities.

To make it work, you need to include two additional dependencies. JSR 303 and a library that implements it, like the one supported by hibernate:

Example 14. Validation dependencies

Now you need to add two beans to your configuration:

Example 15. Validation beans
public LocalValidatorFactoryBean validator() {
    return new LocalValidatorFactoryBean();

public ValidatingCouchbaseEventListener validationEventListener() {
    return new ValidatingCouchbaseEventListener(validator());

Now you can annotate your fields with JSR303 annotations. If a validation on save() fails, a ConstraintViolationException is thrown.

Example 16. Sample Validation Annotation
@Size(min = 10)
private String name;

4.5. Auditing

Entities can be automatically audited (tracing which user created the object, updated the object, and at what times) through Spring Data auditing mechanisms.

First, note that only entities that have a @Version annotated field can be audited for creation (otherwise the framework will interpret a creation as an update).

Auditing works by annotating fields with @CreatedBy, @CreatedDate, @LastModifiedBy and @LastModifiedDate. The framework will automatically inject the correct values on those fields when persisting the entity. The xxxDate annotations must be put on a Date field (or compatible, eg. jodatime classes) while the xxxBy annotations can be put on fields of any class T (albeit both fields must be of the same type).

To configure auditing, first you need to have an auditor aware bean in the context. Said bean must be of type AuditorAware<T> (allowing to produce a value that can be stored in the xxxBy fields of type T we saw earlier). Secondly, you must activate auditing in your @Configuration class by using the @EnableCouchbaseAuditing annotation.

Here is an example:

Example 17. Sample Auditing Entity
public class AuditedItem {

  private final String id;

  private String value;

  private String creator;

  private String lastModifiedBy;

  private Date lastModification;

  private Date creationDate;

  private long version;

  //..omitted constructor/getters/setters/...

Notice both @CreatedBy and @LastModifiedBy are both put on a String field, so our AuditorAware must work with String.

Example 18. Sample AuditorAware implementation
public class NaiveAuditorAware implements AuditorAware<String> {

  private String auditor = "auditor";

  public String getCurrentAuditor() {
    return auditor;

  public void setAuditor(String auditor) {
    this.auditor = auditor;

To tie all that together, we use the java configuration both to declare an AuditorAware bean and to activate auditing:

Example 19. Sample Auditing Configuration
@EnableCouchbaseAuditing //this activates auditing
public class AuditConfiguration extends AbstractCouchbaseConfiguration {

    //... a few abstract methods omitted here

    // this creates the auditor aware bean that will feed the annotations
    public NaiveAuditorAware testAuditorAware() {
      return new NaiveAuditorAware();

5. Auto generating keys

This chapter describes how couchbase document keys can be auto-generated using builtin mechanisms. There are two types of auto-generation strategies supported.

The maximum key length supported by couchbase is 250 bytes.

5.1. Configuration

Keys to be auto-generated should be annotated with @GeneratedValue. The default strategy is USE_ATTRIBUTES. Prefix and suffix for the key can be provided as part of the entity itself, these values are not persisted, they are only used for key generation. The prefixes and suffixes are ordered using the order value. The default order is 0, multiple prefixes without order will overwrite the previous. If a value for id is already available, auto-generation will be skipped. The delimiter for concatenation can be provided using delimiter, the default delimiter is ..

Example 20. Annotation for GeneratedValue
public class User {
     @Id @GeneratedValue(strategy = USE_ATTRIBUTES, delimiter = ".")
     private String id;
     private String userPrefix;
     private String userSuffix;

Common prefix and suffix for all entities keys can be added to CouchbaseTemplate directly. Once added to the CouchbaseTemplate, they become immutable. These settings are always applied irrespective of the GeneratedValue annotation.

Example 21. Common key settings in CouchbaseTemplate
CouchbaseTemplate couchbaseTemplate;

Key will be auto-generated only for operations with direct entity input like insert, update, save, delete using entity. For other operations requiring just the key, it can be generated using CouchbaseTemplate.

Example 22. Standalone key generation in CouchbaseTemplate
CouchbaseTemplate couchbaseTemplate;
String id = couchbaseTemplate.getGeneratedId(entity);

5.2. Key generation using attributes

It is a common practice to generate keys using a combination of the document attributes. Key generation using attributes concatenates all the attribute values annotated with IdAttribute, based on the ordering provided similar to prefixes and suffixes.

Example 23. Annotation for IdAttribute
public class User {
     @Id @GeneratedValue(strategy = USE_ATTRIBUTES)
     private String id;
     private String userid;

5.3. Key generation using uuid

This auto-generation uses UUID random generator to generate document keys consuming 16 bytes of key space. This mechanism is only recommended for test scaffolding.

Example 24. Annotation for Unique key generation
public class User {
     @Id @GeneratedValue(strategy = UNIQUE)
     private String id;

6. Working with Spring Data Repositories

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

Spring Data repository documentation and your module

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

6.1. Core concepts

The central interface in Spring Data repository abstraction is Repository (probably not that much of a surprise). It takes the domain class to manage as well as the id type of the domain class as type arguments. This interface acts primarily as a marker interface to capture the types to work with and to help you to discover interfaces that extend this one. The CrudRepository provides sophisticated CRUD functionality for the entity class that is being managed.

Example 25. CrudRepository interface
public interface CrudRepository<T, ID extends Serializable>
    extends Repository<T, ID> {

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

    T findOne(ID primaryKey);       (2)

    Iterable<T> findAll();          (3)

    Long count();                   (4)

    void delete(T entity);          (5)

    boolean exists(ID primaryKey);  (6)

    // … more functionality omitted.
1 Saves the given entity.
2 Returns the entity identified by the given id.
3 Returns all entities.
4 Returns the number of entities.
5 Deletes the given entity.
6 Indicates whether an entity with the given id exists.
We also provide persistence technology-specific abstractions like e.g. 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 like e.g. CrudRepository.

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

Example 26. PagingAndSortingRepository
public interface PagingAndSortingRepository<T, ID extends Serializable>
  extends CrudRepository<T, ID> {

  Iterable<T> findAll(Sort sort);

  Page<T> findAll(Pageable pageable);

Accessing the second page of User by a page size of 20 you could simply do something like this:

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

In addition to query methods, query derivation for both count and delete queries, is available.

Example 27. Derived Count Query
public interface UserRepository extends CrudRepository<User, Long> {

  Long countByLastname(String lastname);
Example 28. Derived Delete Query
public 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 will handle.

    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 via JavaConfig:

    import org.springframework.data.jpa.repository.config.EnableJpaRepositories;
    class Config {}
    <?xml version="1.0" encoding="UTF-8"?>
    <beans xmlns="http://www.springframework.org/schema/beans"
       <jpa:repositories base-package="com.acme.repositories"/>

    The JPA namespace is used in this example. If you are using the repository abstraction for any other store, you need to change this to the appropriate namespace declaration of your store module which should be exchanging jpa in favor of, for example, mongodb.

    Also, note that the JavaConfig variant doesn’t configure a package explictly as the package of the annotated class is used by default. To customize the package to scan use one of the basePackage… attribute of the data-store specific repository @Enable…-annotation.

  4. Get the repository instance injected and use it.

    public class SomeClient {
      private PersonRepository repository;
      public void doSomething() {
        List<Person> persons = repository.findByLastname("Matthews");

The sections that follow explain each step in detail.

6.3. Defining repository interfaces

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

6.3.1. Fine-tuning repository definition

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

This allows you to define your own abstractions on top of the provided Spring Data Repositories functionality.
Example 29. Selectively exposing CRUD methods
interface MyBaseRepository<T, ID extends Serializable> extends Repository<T, ID> {

  T findOne(ID id);

  T save(T entity);

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

In this first step you defined a common base interface for all your domain repositories and exposed findOne(…) as well as save(…).These methods will be routed into the base repository implementation of the store of your choice provided by Spring Data ,e.g. in the case if JPA SimpleJpaRepository, because they are matching the method signatures in CrudRepository. So the UserRepository will now be able to save users, and find single ones by id, as well as triggering a query to find Users by their email address.

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

6.3.2. Using Repositories with multiple Spring Data modules

Using a unique Spring Data module in your application makes things simple hence, 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 case, it’s required for a repository definition to distinguish between persistence technologies. Spring Data enters strict repository configuration mode because it detects multiple repository factories on the class path. Strict configuration requires 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, then it’s a valid candidate for the particular Spring Data module.

  2. If the domain class is annotated with the module-specific type annotation, then it’s a valid candidate for the particular Spring Data module. Spring Data modules accept either 3rd party annotations (such as JPA’s @Entity) or provide own annotations such as @Document for Spring Data MongoDB/Spring Data Elasticsearch.

Example 30. Repository definitions using Module-specific Interfaces
interface MyRepository extends JpaRepository<User, Long> { }

interface MyBaseRepository<T, ID extends Serializable> extends JpaRepository<T, ID> {

interface UserRepository extends MyBaseRepository<User, Long> {

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

Example 31. Repository definitions using generic Interfaces
interface AmbiguousRepository extends Repository<User, Long> {

interface MyBaseRepository<T, ID extends Serializable> extends CrudRepository<T, ID> {

interface AmbiguousUserRepository extends MyBaseRepository<User, Long> {

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

Example 32. Repository definitions using Domain Classes with Annotations
interface PersonRepository extends Repository<Person, Long> {

public class Person {

interface UserRepository extends Repository<User, Long> {

public class User {

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

Example 33. Repository definitions using Domain Classes with mixed Annotations
interface JpaPersonRepository extends Repository<Person, Long> {

interface MongoDBPersonRepository extends Repository<Person, Long> {

public class Person {

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

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

The last way to distinguish repositories is scoping repository base packages. Base packages define the starting points for scanning for repository interface definitions which implies to have 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.

Example 34. Annotation-driven configuration of base packages
@EnableJpaRepositories(basePackages = "com.acme.repositories.jpa")
@EnableMongoRepositories(basePackages = "com.acme.repositories.mongo")
interface Configuration { }

6.4. Defining query methods

The repository proxy has two ways to derive a store-specific query from the method name. It can derive the query from the method name directly, or by using a manually defined query. Available options depend on the actual store. However, there’s got to be a strategy that decides what actual query is created. Let’s have a look at the available options.

6.4.1. Query lookup strategies

The following strategies are available for the repository infrastructure to resolve the query. You can configure the strategy at the namespace through the query-lookup-strategy attribute in case of XML configuration or via the queryLookupStrategy attribute of the Enable${store}Repositories annotation in case of Java config. Some strategies may not be supported for particular datastores.

  • CREATE attempts to construct a store-specific query from the query method name. The general approach is to remove a given set of well-known prefixes from the method name and parse the rest of the method. Read more about query construction in Query creation.

  • USE_DECLARED_QUERY tries to find a declared query and will throw an exception in case it can’t find one. The query can be defined by an annotation somewhere or declared by other means. Consult the documentation of the specific store to find available options for that store. If the repository infrastructure does not find a declared query for the method at bootstrap time, it fails.

  • CREATE_IF_NOT_FOUND (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 will be used if you do not configure anything explicitly. It allows quick query definition by method names but also custom-tuning of these queries by introducing declared queries as needed.

6.4.2. Query creation

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

Example 35. Query creation from method names
public interface PersonRepository extends Repository<User, Long> {

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

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

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

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

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

  • The expressions are usually property traversals combined with operators that can be concatenated. You can combine property expressions with AND and OR. You also get support for operators such as Between, LessThan, GreaterThan, Like for the property expressions. The supported operators can vary by datastore, so consult the appropriate part of your reference documentation.

  • The method parser supports setting an IgnoreCase flag for individual properties (for example, findByLastnameIgnoreCase(…)) or for all properties of a type that support ignoring case (usually String 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. Assume a Person has an Address with a ZipCode. In that case a method name of

List<Person> findByAddressZipCode(ZipCode zipCode);

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

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

To resolve this ambiguity you can use _ inside your method name to manually define traversal points. So our method name would end up like so:

List<Person> findByAddress_ZipCode(ZipCode zipCode);

As we treat underscore as a reserved character we strongly advise to follow standard Java naming conventions (i.e. not using underscores in property names but camel case instead).

6.4.4. Special parameter handling

To handle parameters in your query you simply define method parameters as already seen in the examples above. Besides that the infrastructure will recognize certain specific types like Pageable and Sort to apply pagination and sorting to your queries dynamically.

Example 36. Using Pageable, Slice and Sort in query methods
Page<User> findByLastname(String lastname, Pageable pageable);

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

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

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

The first method allows you to 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, Slice can be used as return instead. A Slice only knows about whether there’s a next Slice available which might be just sufficient when walking through a larger result set.

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

To find out how many pages you get for a query entirely you have to trigger an additional count query. By default this query will be derived from the query you actually trigger.

6.4.5. Limiting query results

The results of query methods can be limited via the keywords first or top, which can be used interchangeably. An optional numeric value can be appended to top/first to specify the maximum result size to be returned. If the number is left out, a result size of 1 is assumed.

Example 37. Limiting the result size of a query with Top and First
User findFirstByOrderByLastnameAsc();

User findTopByOrderByAgeDesc();

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

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

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

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

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

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

Note that limiting the results in combination with dynamic sorting via a Sort parameter allows to express query methods for the 'K' smallest as well as for the 'K' biggest elements.

6.4.6. Streaming query results

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

Example 38. 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 using the close() method or by using a Java 7 try-with-resources block.
Example 39. Working with a Stream<T> result in a try-with-resources block
try (Stream<User> stream = repository.findAllByCustomQueryAndStream()) {
Not all Spring Data modules currently support Stream<T> as a return type.

6.4.7. Async query results

Repository queries can be executed asynchronously using Spring’s asynchronous method execution capability. This means the method will return immediately upon invocation and the actual query execution will occur in a task that has been submitted to a Spring TaskExecutor.

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

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

ListenableFuture<User> findOneByLastname(String lastname);    (3)
1 Use java.util.concurrent.Future as return type.
2 Use a Java 8 java.util.concurrent.CompletableFuture as return type.
3 Use a org.springframework.util.concurrent.ListenableFuture as return type.

6.5. Creating repository instances

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

6.5.1. XML configuration

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

Example 40. Enabling Spring Data repositories via XML
<?xml version="1.0" encoding="UTF-8"?>
<beans:beans xmlns:beans="http://www.springframework.org/schema/beans"

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


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

Using filters

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

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

Example 41. Using exclude-filter element
<repositories base-package="com.acme.repositories">
  <context:exclude-filter type="regex" expression=".*SomeRepository" />

This example excludes all interfaces ending in SomeRepository from being instantiated.

6.5.2. JavaConfig

The repository infrastructure can also be triggered using a store-specific @Enable${store}Repositories annotation on a JavaConfig class. For an introduction into Java-based configuration of the Spring container, see the reference documentation.[1]

A sample configuration to enable Spring Data repositories looks something like this.

Example 42. Sample annotation based repository configuration
class ApplicationConfiguration {

  public EntityManagerFactory entityManagerFactory() {
    // …
The sample uses the JPA-specific annotation, which you would change according to the store module you actually use. The same applies to the definition of the EntityManagerFactory bean. Consult the sections covering the store-specific configuration.

6.5.3. Standalone usage

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

Example 43. Standalone usage of repository factory
RepositoryFactorySupport factory = … // Instantiate factory here
UserRepository repository = factory.getRepository(UserRepository.class);

6.6. Custom implementations for Spring Data repositories

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

6.6.1. Adding custom behavior to single repositories

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

Example 44. Interface for custom repository functionality
interface UserRepositoryCustom {
  public void someCustomMethod(User user);
Example 45. Implementation of custom repository functionality
class UserRepositoryImpl implements UserRepositoryCustom {

  public void someCustomMethod(User user) {
    // Your custom implementation
The most important bit for the class to be found is the Impl postfix of the name on it compared to the core repository interface (see below).

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

Example 46. Changes to the your basic repository interface
interface UserRepository extends CrudRepository<User, Long>, UserRepositoryCustom {

  // Declare query methods here

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


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

Example 47. Configuration example
<repositories base-package="com.acme.repository" />

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

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

Manual wiring

The approach just shown works well if your custom implementation uses annotation-based configuration and autowiring only, as it will be treated as any other Spring bean. If your custom implementation bean needs special wiring, you simply declare the bean and name it after the conventions just described. The infrastructure will then refer to the manually defined bean definition by name instead of creating one itself.

Example 48. Manual wiring of custom implementations
<repositories base-package="com.acme.repository" />

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

6.6.2. Adding custom behavior to all repositories

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

Example 49. An interface declaring custom shared behavior
public interface MyRepository<T, ID extends Serializable>
  extends PagingAndSortingRepository<T, ID> {

  void sharedCustomMethod(ID id);

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

Example 50. Custom repository base class
public class MyRepositoryImpl<T, ID extends Serializable>
  extends SimpleJpaRepository<T, ID> implements MyRepository<T, ID> {

  private final EntityManager entityManager;

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

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

  public void sharedCustomMethod(ID id) {
    // implementation goes here
The class needs to have a constructor of the super class which the store-specific repository factory implementation is using. In case the repository base class has multiple constructors, override the one taking an EntityInformation plus a store specific infrastructure object (e.g. an EntityManager or a template class).

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

The final step is to make the Spring Data infrastructure aware of the customized repository base class. In JavaConfig this is achieved by using the repositoryBaseClass attribute of the @Enable…Repositories annotation:

Example 51. Configuring a custom repository base class using JavaConfig
@EnableJpaRepositories(repositoryBaseClass = MyRepositoryImpl.class)
class ApplicationConfiguration { … }

A corresponding attribute is available in the XML namespace.

Example 52. Configuring a custom repository base class using XML
<repositories base-package="com.acme.repository"
     base-class="….MyRepositoryImpl" />

6.7. 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.

6.7.1. Querydsl Extension

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

Several Spring Data modules offer integration with Querydsl via QueryDslPredicateExecutor.

Example 53. QueryDslPredicateExecutor interface
public interface QueryDslPredicateExecutor<T> {

    T findOne(Predicate predicate);             (1)

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

    long count(Predicate predicate);            (3)

    boolean exists(Predicate predicate);        (4)

    // … more functionality omitted.
1 Finds and returns a single entity matching the Predicate.
2 Finds and returns all entities matching the Predicate.
3 Returns the number of entities matching the Predicate.
4 Returns if an entity that matches the Predicate exists.

To make use of Querydsl support simply extend QueryDslPredicateExecutor on your repository interface.

Example 54. Querydsl integration on repositories
interface UserRepository extends CrudRepository<User, Long>, QueryDslPredicateExecutor<User> {


The above enables to write typesafe queries using Querydsl Predicate s.

Predicate predicate = user.firstname.equalsIgnoreCase("dave")


6.7.2. Web support

This section contains the documentation for the Spring Data web support as it is implemented as of Spring Data Commons in the 1.6 range. As it the newly introduced support changes quite a lot of things we kept the documentation of the former behavior in Legacy web support.

Spring Data modules ships with a variety of web support if the module supports the repository programming model. The web related stuff requires Spring MVC JARs on the classpath, some of them even provide integration with Spring HATEOAS [2]. In general, the integration support is enabled by using the @EnableSpringDataWebSupport annotation in your JavaConfig configuration class.

Example 55. Enabling Spring Data web support
class WebConfiguration { }

The @EnableSpringDataWebSupport annotation registers a few components we will discuss in a bit. It will also detect Spring HATEOAS on the classpath and register integration components for it as well if present.

Alternatively, if you are using XML configuration, register either SpringDataWebSupport or HateoasAwareSpringDataWebSupport as Spring beans:

Example 56. Enabling Spring Data web support in XML
<bean class="org.springframework.data.web.config.SpringDataWebConfiguration" />

<!-- If you're using Spring HATEOAS as well register this one *instead* of the former -->
<bean class="org.springframework.data.web.config.HateoasAwareSpringDataWebConfiguration" />
Basic web support

The configuration setup shown above will register a few basic components:

  • A DomainClassConverter to enable Spring MVC to resolve instances of repository managed domain classes from request parameters or path variables.

  • HandlerMethodArgumentResolver implementations to let Spring MVC resolve Pageable and Sort instances from request parameters.


The DomainClassConverter allows you to use domain types in your Spring MVC controller method signatures directly, so that you don’t have to manually lookup the instances via the repository:

Example 57. A Spring MVC controller using domain types in method signatures
public class UserController {

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

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

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

Currently the repository has to implement CrudRepository to be eligible to be discovered for conversion.
HandlerMethodArgumentResolvers for Pageable and Sort

The configuration snippet above also registers a PageableHandlerMethodArgumentResolver as well as an instance of SortHandlerMethodArgumentResolver. The registration enables Pageable and Sort being valid controller method arguments

Example 58. Using Pageable as controller method argument
public class UserController {

  @Autowired UserRepository repository;

  public String showUsers(Model model, Pageable pageable) {

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

This method signature will cause Spring MVC try to derive a Pageable instance from the request parameters using the following default configuration:

Table 2. Request parameters evaluated for Pageable instances


Page you want to retrieve, 0 indexed and defaults to 0.


Size of the page you want to retrieve, defaults to 20.


Properties that should be sorted by in the format property,property(,ASC|DESC). Default sort direction is ascending. Use multiple sort parameters if you want to switch directions, e.g. ?sort=firstname&sort=lastname,asc.

To customize this behavior extend either SpringDataWebConfiguration or the HATEOAS-enabled equivalent and override the pageableResolver() or sortResolver() methods and import your customized configuration file instead of using the @Enable-annotation.

In case you need multiple Pageable 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}_. So for a method signature like this:

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

you have to populate foo_page and bar_page etc.

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

Hypermedia support for Pageables

Spring HATEOAS ships with a representation model class PagedResources that allows enriching the content of a Page instance with the necessary Page metadata as well as links to let the clients easily navigate the pages. The conversion of a Page to a PagedResources is done by an implementation of the Spring HATEOAS ResourceAssembler interface, the PagedResourcesAssembler.

Example 59. Using a PagedResourcesAssembler as controller method argument
class PersonController {

  @Autowired PersonRepository repository;

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

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

Enabling the configuration as shown above allows the PagedResourcesAssembler to be used as controller method argument. Calling toResources(…) on it will cause the following:

  • The content of the Page will become the content of the PagedResources instance.

  • The PagedResources will get a PageMetadata instance attached populated with information form the Page and the underlying PageRequest.

  • The PagedResources gets prev and next links attached depending on the page’s state. The links will point to the URI the method invoked is mapped to. The pagination parameters added to the method will match the setup of the PageableHandlerMethodArgumentResolver to make sure the links can be resolved later on.

Assume we have 30 Person instances in the database. You can now trigger a request GET http://localhost:8080/persons and you’ll see something similar to this:

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

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

Querydsl web support

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

This means that given the User object from previous samples a query string


can be resolved to


using the QuerydslPredicateArgumentResolver.

The feature will be automatically enabled along @EnableSpringDataWebSupport when Querydsl is found on the classpath.

Adding a @QuerydslPredicate to the method signature will provide a ready to use Predicate which can be executed via the QueryDslPredicateExecutor.

Type information is typically resolved from the methods return type. Since those information does not necessarily match the domain type it might be a good idea to use the root attribute of QuerydslPredicate.
class UserController {

  @Autowired UserRepository repository;

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

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

    return "index";
1 Resolve query string arguments to matching Predicate for User.

The default binding is as follows:

  • Object on simple properties as eq.

  • Object on collection like properties as contains.

  • Collection on simple properties as in.

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

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

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

    bindings.bind(user.username).first((path, value) -> path.contains(value))    (3)
      .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 will be 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.

6.7.3. Repository populators

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

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

Example 60. Data defined in JSON
[ { "_class" : "com.acme.Person",
 "firstname" : "Dave",
  "lastname" : "Matthews" },
  { "_class" : "com.acme.Person",
 "firstname" : "Carter",
  "lastname" : "Beauford" } ]

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

Example 61. Declaring a Jackson repository populator
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"

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


This declaration causes the data.json file to be read and deserialized via a Jackson ObjectMapper.

The type to which the JSON object will be unmarshalled to will be determined by inspecting the _class attribute of the JSON document. The infrastructure will eventually select the appropriate repository to handle the object just deserialized.

To rather use XML to define the data the repositories shall be populated with, you can use the unmarshaller-populator element. You configure it to use one of the XML marshaller options Spring OXM provides you with. See the Spring reference documentation for details.

Example 62. Declaring an unmarshalling repository populator (using JAXB)
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"

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

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


6.7.4. Legacy web support

Domain class web binding for Spring MVC

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

public class UserController {

  private final UserRepository userRepository;

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

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

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

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

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


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

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

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

public class UserController {

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

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

7. Couchbase repositories

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

There are three backing mechanisms in Couchbase for repositories, described in the sections of this chapter:

CRUD operations are still mostly backed by Couchbase views (see Backing Views). Such views (and, for N1QL, equivalent indexes) can be automatically built, but note this is discouraged in production and can be an expensive operation (see Automatic Index Management).

Note that you can tune the consistency you want for your queries (see Querying with consistency) and have different repositories backed by different buckets (see Working with multiple buckets)

7.1. Configuration

While support for repositories is always present, you need to enable them in general or for a specific namespace. If you extend AbstractCouchbaseConfiguration, just use the @EnableCouchbaseRepositories annotation. It provides lots of possible options to narrow or customize the search path, one of the most common ones is basePackages.

Example 63. Annotation-Based Repository Setup
@EnableCouchbaseRepositories(basePackages = {"com.couchbase.example.repos"})
public class Config extends AbstractCouchbaseConfiguration {

An advanced usage is described in Working with multiple buckets.

XML-based configuration is also available:

Example 64. XML-Based Repository Setup
<couchbase:repositories base-package="com.couchbase.example.repos" />

7.2. Usage

In the simplest case, your repository will extend the CrudRepository<T, String>, where T is the entity that you want to expose. Let’s look at a repository for a UserInfo:

Example 65. A UserInfo repository
import org.springframework.data.repository.CrudRepository;

public interface UserRepository extends CrudRepository<UserInfo, String> {

Please note that this is just an interface and not an actual class. In the background, when your context gets initialized, actual implementations for your repository descriptions get created and you can access them through regular beans. This means you will save lots of boilerplate code while still exposing full CRUD semantics to your service layer and application.

Now, let’s imagine we @Autowire the UserRepository to a class that makes use of it. What methods do we have available?

Table 3. Exposed methods on the UserRepository
Method Description

UserInfo save(UserInfo entity)

Save the given entity.

Iterable<UserInfo> save(Iterable<UserInfo> entity)

Save the list of entities.

UserInfo findOne(String id)

Find a entity by its unique id.

boolean exists(String id)

Check if a given entity exists by its unique id.

Iterable<UserInfo> findAll() (*)

Find all entities by this type in the bucket.

Iterable<UserInfo> findAll(Iterable<String> ids)

Find all entities by this type and the given list of ids.

long count() (*)

Count the number of entities in the bucket.

void delete(String id)

Delete the entity by its id.

void delete(UserInfo entity)

Delete the entity.

void delete(Iterable<UserInfo> entities)

Delete all given entities.

void deleteAll() (*)

Delete all entities by type in the bucket.

Now that’s awesome! Just by defining an interface we get full CRUD functionality on top of our managed entity. All methods suffixed with (*) in the table are backed by Views, which is explained later.

While the exposed methods provide you with a great variety of access patterns, very often you need to define custom ones. You can do this by adding method declarations to your interface, which will be automatically resolved to requests in the background, as we’ll see in the next sections.

7.3. Repositories and Querying

7.3.1. N1QL based querying

As of version 4.0, Couchbase Server ships with a new query language called N1QL. In Spring-Data-Couchbase 2.0, N1QL is the default way of doing queries and will allow you to fully derive queries from a method name.

Prerequisite is to have a N1QL-compatible cluster and to have created a PRIMARY INDEX on the bucket where the entities will be stored.

If it is detected at configuration time that the cluster doesn’t support N1QL while there are @Query annotated methods or non-annotated methods in your repository interface, a UnsupportedCouchbaseFeatureException will be thrown.

Here is an example:

Example 66. An extended UserInfo repository with N1QL queries
public interface UserRepository extends CrudRepository<UserInfo, String> {

    @Query("#{#n1ql.selectEntity} WHERE role = 'admin' AND #{#n1ql.filter}")
    List<UserInfo> findAllAdmins();

    List<UserInfo> findByFirstname(String fname);

Here we see two N1QL-backed ways of querying.

The first method uses the Query annotation to provide a N1QL statement inline. SpEL (Spring Expression Language) is supported by surrounding SpEL expression blocks between #{ and }. A few N1QL-specific values are provided through SpEL:

  • #n1ql.selectEntity allows to easily make sure the statement will select all the fields necessary to build the full entity (including document ID and CAS value).

  • #n1ql.filter in the WHERE clause adds a criteria matching the entity type with the field that Spring Data uses to store type information.

  • #n1ql.bucket will be replaced by the name of the bucket the entity is stored in, escaped in backticks.

  • #n1ql.fields will be replaced by the list of fields (eg. for a SELECT clause) necessary to reconstruct the entity.

We recommend that you always use the selectEntity SpEL and a WHERE clause with a filter SpEL (since otherwise your query could be impacted by entities from other repositories).

String-based queries support parametrized queries. You can either use positional placeholders like “$1”, in which case each of the method parameters will map, in order, to $1, $2, $3…​ Alternatively, you can use named placeholders using the “$someString” syntax. Method parameters will be matched with their corresponding placeholder using the parameter’s name, which can be overridden by annotating each parameter (except a Pageable or Sort) with @Param (eg. @Param("someString")). You cannot mix the two approaches in your query and will get an IllegalArgumentException if you do.

You can also do single projections in your N1QL queries (provided it selects only one field and returns only one result, usually an aggregation like COUNT, AVG, MAX…​). Such projection would have a simple return type like long, boolean or String. This is NOT intended for projections to DTOs.

Another example: “#{#n1ql.selectEntity} WHERE #{#n1ql.filter} AND test = $1”, which is equivalent to `SELECT #{#n1ql.fields} FROM #{#n1ql.bucket} WHERE #{#n1ql.filter} AND test = $1`".

A practical application of SpEL with Spring Security

SpEL can be useful when you want to do a query depending on data injected by other Spring components, like Spring Security. Here is what you need to do to extend the SpEL context to get access to such external data.

First, you need to implement an EvaluationContextExtension (use the support class as below):

class SecurityEvaluationContextExtension extends EvaluationContextExtensionSupport {

  public String getExtensionId() {
    return "security";

  public SecurityExpressionRoot getRootObject() {
    Authentication authentication = SecurityContextHolder.getContext().getAuthentication();
    return new SecurityExpressionRoot(authentication) {};

Then all you need to do for Spring Data Couchbase to be able to access associated SpEL values is to declare a corresponding bean in your configuration:

EvaluationContextExtension securityExtension() {
    return new SecurityEvaluationContextExtension();

This could be useful to craft a query according to the role of the connected user for instance:

@Query("#{#n1ql.selectEntity} WHERE #{#n1ql.filter} AND " +
"role = '?#{hasRole('ROLE_ADMIN') ? 'public_admin' : 'admin'}'")
List<UserInfo> findAllAdmins(); //only ROLE_ADMIN users will see hidden admins

The second method uses Spring-Data’s query derivation mechanism to build a N1QL query from the method name and parameters. This will produce a query looking like this: SELECT …​ FROM …​ WHERE firstName = "valueOfFnameAtRuntime". You can combine these criteria, even do a count with a name like countByFirstname or a limit with a name like findFirst3ByLastname…​

Actually the generated N1QL query will also contain an additional N1QL criteria in order to only select documents that match the repository’s entity class.

Most Spring-Data keywords are supported: .Supported keywords inside @Query (N1QL) method names

Keyword Sample N1QL WHERE clause snippet



lastName = a AND firstName = b



lastName = a OR firstName = b



field = a



field != a



field BETWEEN a AND b



field < a



field ⇐ a



field > a



field >= a



field IS NULL






field LIKE "a" - a should be a String containing % and _ (matching n and 1 characters)



field NOT LIKE "a" - a should be a String containing % and _ (matching n and 1 characters)



field LIKE "a%" - a should be a String prefix



field LIKE "%a" - a should be a String suffix



field LIKE "%a%" - a should be a String



field NOT LIKE "%a%" - a should be a String



field IN array - note that the next parameter value (or its children if a collection/array) should be compatible for storage in a JsonArray)



field NOT IN array - note that the next parameter value (or its children if a collection/array) should be compatible for storage in a JsonArray)



field = TRUE



field = FALSE



REGEXP_LIKE(field, "a") - note that the ignoreCase is ignored here, a is a regular expression in String form



field IS NOT MISSING - used to verify that the JSON contains this attribute



field = a ORDER BY lastname DESC



LOWER(field) = LOWER("a") - a must be a String

You can use both counting queries and Limiting query results features with this approach.

With N1QL, another possible interface for the repository is the PagingAndSortingRepository one (which extends CRUDRepository). It adds two methods:

Table 4. Exposed methods on the PagingAndSortingRepository
Method Description

Iterable<T> findAll(Sort sort);

Allows to retrieve all relevant entities while sorting on one of their attributes.

Page<T> findAll(Pageable pageable);

Allows to retrieve your entities in pages. The returned Page allows to easily get the next page’s Pageable as well as the list of items. For the first call, use new PageRequest(0, pageSize) as Pageable.

You can also use Page and Slice as method return types as well with a N1QL backed repository.

The second way of querying, supported also in older versions of Couchbase Server, is the View-backed one that we’ll see in the next section.

7.3.2. Backing Views

This is the historical way of secondary indexing in Couchbase. Views are much more limited in terms of querying flexibility, and each custom method may very well need its own backing view, to be prepared in the cluster beforehand.

We’ll only cover views to the extent to which they are needed, if you need in-depth information about them please refer to the official Couchbase Server manual and the Couchbase Java SDK manual.

As a rule of thumb, all repository CRUD access methods which are not "by a specific key" still require a single backing view, by default all, to find the one or more matching entities.

This is only true for the methods directly defined by the CrudRepository interface (the one marked with a * in Table 1. above), since your additional methods can now be backed by N1QL.

To cover the basic CRUD methods from the CrudRepository, one view needs to be implemented in Couchbase Server. It basically returns all documents for the specific entity and also adds the optional reduce function _count.

Since every view has a design document and view name, by convention we default to all as the view name and the uncapitalized (lowercase first letter) entity name as the design document name. So if your entity is named UserInfo, then the code expects the all view in the userInfo design document. It needs to look like this:

Example 67. The all view map function
// do not forget the _count reduce function!
function (doc, meta) {
  if (doc._class == "namespace.to.entity.UserInfo") {
    emit(meta.id, null);

Note that the important part in this map function is to only include the document IDs which correspond to our entity. Because the library always adds the _class property, this is a quick and easy way to do it. If you have another property in your JSON which does the same job (like a explicit type field), then you can use that as well - you don’t have to stick to _class all the time.

Also make sure to publish your design documents into production so that they can be picked up by the library! Also, if you are curious why we use emit(meta.id, null) in the view despite the document id being always sent over to the client implicitly, it is so the view can be queried with a list of ids, eg. in the findAll(Iterable<ID> ids) CRUD method.

7.3.3. Automatic Index Management

We’ve seen that the repositories default methods can be backed by two broad kind of features: views and N1QL (in the case of paging and sorting). In order for the CRUD operations to work, the adequate view must have been created beforehand, and this is usually left for the user to do. First because view creation (and index creation) is an expensive operation that can take quite some time if the quantity of documents is high. Second, because in production it is considered best practice to avoid administration of the cluster elements like buckets, indexes and view by an application code.

In the case where the index creation cost isn’t considered too high and you are not in a production environment, it can be triggered automatically instead, in two steps. You will first need to annotate the repositories you want managed with the relevant annotation(s):

  • @ViewIndexed will create a view like the "all" view previously seen, to list all entities in the bucket.

  • @N1qlPrimaryIndexed can be used to ensure a general-purpose PRIMARY INDEX is available in N1QL.

  • @N1qlSecondaryIndexed will create a more specific N1QL index that does the same kind of filtering on entity type that the view does. It’ll allow for efficient listing of all documents that correspond to a Repository’s associated domain object.

Secondly, you’ll need to opt-in to this feature by customizing the indexManager() bean of your env-specific AbstractCouchbaseConfiguration to take certain types of annotations into account. This is done through the IndexManager(boolean processViews, boolean processN1qlPrimary, boolean processN1qlSecondary) constructor. Set the flags for the category of annotations you want processed to true, or false to deactivate the automatic creation feature.

The @Profile annotation is one possible Spring annotation to be used to differentiate configurations (or individual beans) per environment.

Example 68. A Dev configuration where only @ViewIndexed annotations will be processed.
public class ExampleDevApplicationConfig extends AbstractCouchbaseConfiguration {

  // note a few other overrides are actually needed

  //this is for dev so it is ok to auto-create indexes
  public IndexManager indexManager() {
    return new IndexManager(true, false, false);

7.3.4. View based querying

In 2.0, since N1QL has been introduced as a more powerful concept, view-backed queries have changed a bit outside of the CRUD methods:

  • the @View annotation is mandatory.

  • if you just want all the results from the view, you can let the framework guess the view name to use by just using the plain annotation @View. You won’t be able to customize the ViewQuery (eg. adding limits and specifying a startkey) using this method anymore.

  • if you want your view query to have restrictions, those can be derived from the method name but in this case you must explicitly provide the viewName attribute in the annotation.

  • View based query derivation is limited to a few keywords and only works on simple keys (not compound keys like [ age, fname ]).

  • View based query derivation still needs you to include one valid property before keywords in the method name.

Example 69. An extended UserInfo repository with View queries
public interface UserRepository extends CrudRepository<UserInfo, String> {

    List<UserInfo> findAllAdmins();

    List<UserInfo> findByFirstnameStartingWith(String fnamePrefix);

Implementing your custom repository finder methods also needs backing views. The findAllAdmins guesses to use the allAdmins view in the userInfo design document, by convention. Imagine we have a field on our entity which looks like boolean isAdmin. We can write a view like this to expose them (we don’t need a reduce function for this one, unless you plan to call one by prefixing your method with count instead of find!):

Example 70. The allAdmins map function
function (doc, meta) {
  if (doc._class == "namespace.to.entity.UserInfo" && doc.isAdmin) {
    emit(null, null);

By now, we’ve never actually customized our view at query time. This is where the alternative, query derivation, comes along - like in our findByFirstnameStartingWith(String fnamePrefix) method.

Example 71. The firstNames view map function
function (doc, meta) {
  if (doc._class == "namespace.to.entity.UserInfo") {
    emit(doc.firstname, null);

This view not only emits the document id, but also the firstname of every UserInfo as the key. We can now run a ViewQuery which returns us all users with a firstname of "Michael" or "Michele".

Example 72. Query a repository method with custom params.
// Load the bean, or @Autowire it
UserRepository repo = ctx.getBean(UserRepository.class);

// Find all users with first name starting with "Mich"
List<UserInfo> users = repo.findByFirstnameStartingWith("Mich");

On all these derived custom finder methods, you have to use the @View annotation with at least the view name specified (and you can also override the design document name, otherwise determined by convention).

For any other usage and customization of the ViewQuery that goes beyond that, recommended approach is to provide an implementation that uses the underlying template, like described in Changing repository behaviour. For more details on behavior, please consult the Couchbase Server and Java SDK documentation directly.

For view-based query derivation, here are the supported keywords (A and B are method parameters in this table):

Table 5. Supported keywords inside @View method names
Is,Equals findAllByUsername,findByFieldEquals key=A - if only keyword, the method can have no parameter (return all items from the view)















startkey="A"&endkey="A\uefff" - A should be a String prefix



keys=[A] - A should be a Collection/Array with elements compatible for storage in a JsonArray (or a single element to be stored in a JsonArray)

Note that both reduce functions and Limiting query results are also supported.

In order to trigger a reduce, you can use the count prefix instead of find. But sometimes is doesn’t make much sense (eg. because you actually use the _stats built in function, which returns a JSON object). So alternatively you can also explicitly ask for reduce to be executed by setting reduce = true in the @View annotation. Be sure to specify a return type that make sense for the reduce function of your view.
Compound keys are not supported, and neither are Or composition, Ignore Case and Order By. You have to include a valid entity property in the naming of your method.

Last method of querying in Couchbase (from Couchbase Server 4.0, like for N1QL) is querying for dimensional data through Spatial Views, as we’ll see in the next section.

7.3.5. Spatial View based querying

Couchbase can accommodate multi-dimensional data and query it with the use of special views, the Spatial Views. Such views allows to perform multi-dimensional queries, not only limited to geographical data.

Integration of these views in Spring Data Couchbase repositories is done through the @Dimensional annotation. Like @View, the annotation allows to indicate usage of a Spatial View as the backing mechanism for the annotated method. The annotation requires you to give the name of the designDocument and the spatialViewName to use. Additionally, you should specify the number of dimensions the view works with (unless it is the default classical 2).

Multi-dimensionality concept is interesting, it means you can craft views that allows you to answer questions like "find all shops that are within Manhattan and open between 14:00 and 23:00" (the third dimension of the view being the opening hours).

Couchbase’s Spatial View support querying through ranges that represent "lowest" and "highest" values in each dimension, so for 2D it represents a bounding box, with the southwest-most point [x,y] as startRange and northeast-most point [x,y] as endRange.

Even though Couchbase Spatial View engine only support Bounding Box querying, the Spring Data Couchbase framework will attempt to remove false positives for you when querying with a Polygon or a Circle (in TRACE log level each false positive elimination will be logged). Note that a point on the edge of a Polygon is not considered within (whereas it is when dealing with a Circle).

The following query derivation keywords and parameters relative to geographical data in Spring Data are supported for Spatial Views:

Table 6. Supported keywords inside @Dimensional method names
Keyword Sample Remarks





expects a Point and a Distance, will approximate to bounding box



useful for dimensions beyond 2, adds two numerical values to the startRange and endRange respectively



useful for dimensions beyond 2, adds a numerical value to the startRange



useful for dimensions beyond 2, adds a numerical value to the endRange

For "within" types of queries, the expected parameters map to geographical 2D data. Classes from the org.springframework.data.geo package are usually expected, but Polygon and Boxes can also be expressed as arrays of `Point`s.

Further dimensions are supported through keywords other than Within and Near and require numerical input.

7.3.6. Querying with consistency

One aspect that is often needed and doesn’t have a direct equivalent in the Spring Data query derivation mechanism is query consistency. In both view-based queries and N1QL, you have this concept that the secondary index can return stale data, because the latest version hasn’t been indexed yet. This gives the best performance at the expense of consistency.

Note that weaker consistencies can lead to data being returned that doesn’t match the criteria of a derived query. One trickier case is when documents are deleted from Couchbase but views have not yet caught up to the deletion. With weak consistency this can mean that a view would return IDs that are not in the database anymore, leading to null entities. The CouchbaseTemplate`s `findByView and findBySpatialView methods will remove such stale deleted entities from their result in order to avoid having nulls in the returned collections. Similarly, CouchbaseRepository’s `deleteAll method will ignore documents that the backing view provided but the SDK remove operation couldn’t find.

If one wants to have stronger consistency, there are two possibilities described in the next sections.

Configure it on a global level

A global consistency can be defined using the Consistency enumeration (eg. Consistency.READ_YOUR_OWN_WRITE):

  • in xml, this is done via the consistency attribute on <couchbase:template>.

  • in javaConfig, this is done by overriding the getDefaultConsistency() method.

By default it is Consistency.READ_YOUR_OWN_WRITES (which means consistency is prioritized over speed, especially when a large number of documents has been created recently).

This is only used in repositories, either for index-backed methods automatically provided by the repository interface (findAll(), findAll(keys), count(), deleteAll()…​) or methods you define in your specific interface using query derivation.
Provide an implementation

Provide the implementation and directly use queryView and queryN1QL methods on the template with a specific consistency (see Changing repository behaviour).

  • one can specify the consistency on those via their respective query classes, according to the Couchbase Java SDK documentation.

  • for example for views ViewQuery.stale(Stale.FALSE)

  • for example for N1QL Query.simple("SELECT * FROM default", QueryParams.build().consistency(ScanConsistency.REQUEST_PLUS));

7.4. Working with multiple buckets

The Java Config version allows you to define multiple Bucket and CouchbaseTemplate, but in order to have different repositories use different underlying buckets/templates, you need to follow these steps:

  • in your AbstractCouchbaseConfiguration implementation, override the configureRepositoryOperationsMapping method.

  • mutate the provided RepositoryOperationsMapping as needed (it defaults to mapping everything to the default template).

  • configure the mapping by chaining calls to map, mapEntity and setDefault.

    • map maps a specific repository interface to the CouchbaseOperations it should use

    • mapEntity maps all unmapped repositories of a domain type / entity class to a common CouchbaseOperations

    • setDefault maps all remaining unmapped repositories to a default CouchaseOperations (the default, using couchbaseTemplate bean unless modified).

The idea is that the framework will look for an entry corresponding to the repository’s interface when instantiating it. If none is found it will look at the mapping for the repository’s domain type. Eventually it will fallback to the default setting. Here is an example:

Example 73. Example of configuring multiple templates and repositories.
public class ConcreteCouchbaseConfig extends AbstractCouchbaseConfig {

  //the default bucket and template must be created, implement abstract methods here to that end

  //we want all User objects to be stored in a second bucket
  //let's define the bucket reference...
  public Bucket userBucket() {
    return couchbaseCluster().openBucket("users", "");

  //... then the template (inspired by couchbaseTemplate() method)...
  public CouchbaseTemplate userTemplate() {
    CouchbaseTemplate template = new CouchbaseTemplate(
        couchbaseClusterInfo(), //reuse the default bean
      userBucket(), //the bucket is non-default
        mappingCouchbaseConverter(), translationService() //default beans here as well
    return template;

  //... then finally make sure all repositories of Users will use it
  public void configureRepositoryOperationsMapping(RepositoryOperationsMapping baseMapping) {
    baseMapping //this is already using couchbaseTemplate as default
      .mapEntity(User.class, userTemplate()); //every repository dealing with User will be backed by userTemplate()

7.5. Changing repository behaviour

Sometimes you don’t simply want the repository to create methods for you, but instead you want to tune the base repository’s behaviour. You can either do that for all repositories - by changing the base class for them - or just for a single repository - by adding custom implementations for either new or existing methods - (see Custom implementations for Spring Data repositories for a generic introduction to these concepts).

7.5.1. Couchbase specifics about changing the base class

This follows the standard procedure for changing all repositories' base class:

  1. Create an generic interface for your base that extends CouchbaseRepository (CRUD) or CouchbasePagingAndSortingRepository. Declare any method you want to add to all repositories there.

  2. Create an implementation (eg. MyRepositoryImpl). This should extend one the concrete base classes (SimpleCouchbaseRepository or N1qlCouchbaseRepository) and you can also override existing methods from the Spring Data interfaces.

  3. Declare your repository interfaces as extending MyRepository instead of eg. CRUDRepository or CouchbaseRepository.

  4. In the @EnableCouchbaseRepositories annotation of your configuration, use the repositoryBaseClass parameter.

Here is a complete example that you can find in RepositoryBaseTest in the integration tests:

Changing repository base class
@NoRepositoryBean (1)
public interface MyRepository<T, ID extends Serializable> extends CouchbaseRepository<T, ID> { (2)

  int sharedCustomMethod(ID id); (3)

public class MyRepositoryImpl<T, ID extends Serializable>
    extends N1qlCouchbaseRepository<T, ID> (4)
    implements MyRepository<T, ID> { (5)

  public MyRepositoryImpl(CouchbaseEntityInformation<T, String> metadata, CouchbaseOperations couchbaseOperations) { (6)
    super(metadata, couchbaseOperations);

  public int sharedCustomMethod(ID id) {
    //... implement common behavior (7)

@EnableCouchbaseRepositories(repositoryBaseClass = MyRepositoryImpl.class) (8)
public class MyConfig extends AbstractCouchbaseConfiguration { /** ... */ }
1 This annotation prevents picking this custom interface as a repository declaration.
2 The new base interface extends one from Spring Data Couchbase.
3 This method will be available in all repositories.
4 Custom base implementation relies on the existing bases…​
5 …​and also implements new interface (so that common methods are exposed).
6 Constructors that follow the signature of superconstructor will be picked up by the framework.
7 Custom functionality to be implemented by the user (eg. return string’s length).
8 Weaving it all in by changing the repository base class.

7.5.2. Couchbase specifics about adding methods to a single repository

Again following the standard procedure for custom repository methods, here is a complete example that you can find in RepositoryCustomMethodTest in the integration tests:

Adding and overriding methods in a single repository
public interface MyRepositoryCustom {
  long customCountItems(); (1)

public interface MyRepository extends CrudRepository<MyItem, String>, MyRepositoryCustom { } (2)

public class MyRepositoryImpl implements MyRepositoryCustom { (3)

  RepositoryOperationsMapping templateProvider; (4)

  public long customCountItems() {
    CouchbaseOperations template = templateProvider.resolve(MyRepository.class, Item.class); (5)

    CouchbasePersistentEntity<Object> itemPersistenceEntity = (CouchbasePersistentEntity<Object>)

    CouchbaseEntityInformation<? extends Object, String> itemEntityInformation =
        new MappingCouchbaseEntityInformation<Object, String>(itemPersistenceEntity);

    Statement countStatement = N1qlUtils.createCountQueryForEntity( (6)

    ScanConsistency consistency = template.getDefaultConsistency().n1qlConsistency(); (7)
    N1qlParams queryParams = N1qlParams.build().consistency(consistency);
    N1qlQuery query = N1qlQuery.simple(countStatement, queryParams);

    List<CountFragment> countFragments = template.findByN1QLProjection(query, CountFragment.class); (8)

    if (countFragments == null || countFragments.isEmpty()) {
      return 0L;
    } else {
      return countFragments.get(0).count * -1L; (9)

  public long count() { (10)
    return 100;
1 This method is to be added with a user-provided implementation for a single repository.
2 This is the declaration of the customized repository, both a CRUD and exposing the custom interface.
3 This is the implementation of the custom interface.
4 The custom implementation doesn’t have access to the original base implementation, so use dependency injection to get access to necessary resources.
5 Here is a couchbase specificity: if you need to use the CouchbaseTemplate, be sure to use the one that would be associated with the customized repository or associated entity type.
6 We use N1QLUtils to prepare a complete N1QL statement for counting. It relies on the information above that we got from the correct template.
7 We want to make sure that the default consistency configured in the associated template is used for this query.
8 Using CouchbaseTemplate.findByN1qlProjection, we execute the count query and store the single aggregation result into a CountFragment.
9 Now we return this count result with a twist: it is negated.
10 TIP: You can actually also change implementation of methods from the CRUDRepository interface!

By storing 3 items using a MyRepository instance and calling count() then customCountItems(), we’d obtain


8. Template & direct operations

The template provides lower level access to the underlying database and also serves as the foundation for repositories. Any time a repository is too high-level for you needs chances are good that the templates will serve you well.

8.1. Supported operations

The template can be accessed through the couchbaseTemplate bean out of your context. Once you’ve got a reference to it, you can run all kinds of operations against it. Other than through a repository, in a template you need to always specify the target entity type which you want to get converted.

To mutate documents, you’ll find save, insert and update methods exposed. Saving will insert or update the document, insert will fail if it has been created already and update only works against documents that have already been created.

Since Couchbase Server has different levels of persistence (by default you’ll get a positive response if it has been acknowledged in the managed cache), you can provide higher durability options through the overloaded PersistTo and/or ReplicateTo options. The behaviour is part of the Couchbase Java SDK, please refer to the official documentation for more details.

Removing documents through the remove methods works exactly the same.

If you want to load documents, you can do that through the findById method, which is the fastest and if possible your tool of choice. The find methods for views are findByView which converts it into the target entity, but also queryView which exposes lower level semantics. Similarly, find methods using N1QL are provided in findByN1QL and queryN1QL. Additionally, since N1QL allows you to select specific fields in documents (or even across documents using joins), findByN1QLProjection will allow you to skip full Document conversion and map these fields to an ad-hoc class.

If it is detected at runtime that the cluster doesn’t support N1QL, these methods will throw a UnsupportedCouchbaseFeatureException.

If you really need low-level semantics, the couchbaseBucket is also always in scope through getCouchbaseBucket().

8.2. Xml Configuration

The template can be configured via xml, including setting a custom TranslationService.

Example 74. XML Based Template Declaration
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
       xsi:schemaLocation="http://www.springframework.org/schema/data/couchbase http://www.springframework.org/schema/data/couchbase/spring-couchbase.xsd
		http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans.xsd">


    <couchbase:template translation-service-ref="myCustomTranslationService"/>

    <bean id="myCustomTranslationService" class="org.springframework.data.couchbase.core.convert.translation.JacksonTranslationService"/>

In the example above most tags assume their default values, that is a localhost cluster and bucket "default". In production you would have to also provide specifics to these tags.


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.[3]

Table 7. Attributes
Name Description


Defines the package to be used to be scanned for repository interfaces extending *Repository (actual interface is determined by specific Spring Data module) in auto detection mode. All packages below the configured package will be scanned, too. Wildcards are allowed.


Defines the postfix to autodetect custom repository implementations. Classes whose names end with the configured postfix will be considered as candidates. Defaults to Impl.


Determines the strategy to be used to create finder queries. See Query lookup strategies for details. Defaults to create-if-not-found.


Defines the location to look for a Properties file containing externally defined queries.


Controls whether nested repository interface definitions should be considered. Defaults to false.

Appendix B: Populators namespace reference

The <populator /> element

The <populator /> element allows to populate the a data store via the Spring Data repository infrastructure.[4]

Table 8. Attributes
Name Description


Where to find the files to read the objects from the repository shall be populated with.

Appendix C: Repository query keywords

Supported query keywords

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

Table 9. Query keywords
Logical keyword Keyword expressions






After, IsAfter


Before, IsBefore


Containing, IsContaining, Contains


Between, IsBetween


EndingWith, IsEndingWith, EndsWith




False, IsFalse


GreaterThan, IsGreaterThan


GreaterThanEqual, IsGreaterThanEqual


In, IsIn


Is, Equals, (or no keyword)


NotNull, IsNotNull


Null, IsNull


LessThan, IsLessThan


LessThanEqual, IsLessThanEqual


Like, IsLike


Near, IsNear


Not, IsNot


NotIn, IsNotIn


NotLike, IsNotLike


Regex, MatchesRegex, Matches


StartingWith, IsStartingWith, StartsWith


True, IsTrue


Within, IsWithin

Appendix D: Repository query return types

Supported query return types

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

Geospatial types like (GeoResult, GeoResults, GeoPage) are only available for data stores that support geospatial queries.
Table 10. Query return types
Return type Description


Denotes no return value.


Java primitives.

Wrapper types

Java wrapper types.


An unique entity. Expects the query method to return one result at most. In case no result is found null is returned. More than one result will trigger an IncorrectResultSizeDataAccessException.


An Iterator.


A Collection.


A List.


A Java 8 or Guava Optional. Expects the query method to return one result at most. In case no result is found Optional.empty()/Optional.absent() is returned. More than one result will trigger an IncorrectResultSizeDataAccessException.


A Java 8 Stream.


A Future. Expects method to be annotated with @Async and requires Spring’s asynchronous method execution capability enabled.


A Java 8 CompletableFuture. Expects method to be annotated with @Async and requires Spring’s asynchronous method execution capability enabled.


A org.springframework.util.concurrent.ListenableFuture. Expects method to be annotated with @Async and requires Spring’s asynchronous method execution capability enabled.


A sized chunk of data with information whether there is more data available. Requires a Pageable method parameter.


A Slice with additional information, e.g. the total number of results. Requires a Pageable method parameter.


A result entry with additional information, e.g. distance to a reference location.


A list of GeoResult<T> with additional information, e.g. average distance to a reference location.


A Page with GeoResult<T>, e.g. average distance to a reference location.

1. JavaConfig in the Spring reference documentation
2. Spring HATEOAS - https://github.com/SpringSource/spring-hateoas
3. see XML configuration
4. see XML configuration