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Preface

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

Project Information

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.

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.

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.

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.

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 [repositories.single-repository-behaviour].

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

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

is to be replaced by the (more flexible):

@View("byLastName")
List<User> findFirst3ByLastnameEquals(String lastName);

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

1. Installation & Configuration

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

1.1. 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
<dependency>
    <groupId>org.springframework.data</groupId>
    <artifactId>spring-data-couchbase</artifactId>
    <version>2.0.0.RELEASE</version>
</dependency>

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
<dependency>
  <groupId>org.springframework.data</groupId>
  <artifactId>spring-data-couchbase</artifactId>
  <version>2.1.0.BUILD-SNAPSHOT</version>
</dependency>

<repository>
  <id>spring-libs-snapshot</id>
  <name>Spring Snapshot Repository</name>
  <url>https://repo.spring.io/libs-snapshot</url>
</repository>

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.

1.2. 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
@Configuration
public class Config extends AbstractCouchbaseConfiguration {

    @Override
    protected List<String> getBootstrapHosts() {
        return Collections.singletonList("127.0.0.1");
    }

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

    @Override
    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.

1.3. 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"
  xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xmlns="http://www.springframework.org/schema/data/couchbase
  xsi:schemaLocation="http://www.springframework.org/schema/beans
    https://www.springframework.org/schema/beans/spring-beans.xsd
    http://www.springframework.org/schema/data/couchbase
    https://www.springframework.org/schema/data/couchbase/spring-couchbase.xsd">

    <couchbase:cluster>
      <couchbase:node>127.0.0.1</couchbase:node>
    </couchbase:cluster>

    <!-- 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=""/>
</beans:beans>

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.

2. Modeling Entities

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

2.1. Object Mapping Fundamentals

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

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

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

  2. Instance population to materialize all exposed properties.

2.1.1. Object creation

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

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

  2. If there’s a single constructor taking arguments, it will be used.

  3. If there are multiple constructors taking arguments, the one to be used by Spring Data will have to be annotated with @PersistenceConstructor.

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

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

Object creation internals

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

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

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

class PersonObjectInstantiator implements ObjectInstantiator {

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

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

  • it must not be a private class

  • it must not be a non-static inner class

  • it must not be a CGLib proxy class

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

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

2.1.2. Property population

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

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

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

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

Property population internals

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

class Person {

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

  Person() {
    this.id = null;
  }

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

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

  void setLastname(String lastname) {
    this.lastname = lastname;
  }
}
Example 5. A generated Property Accessor
class PersonPropertyAccessor implements PersistentPropertyAccessor {

  private static final MethodHandle firstname;              (2)

  private Person person;                                    (1)

  public void setProperty(PersistentProperty property, Object value) {

    String name = property.getName();

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

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

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

  • Types and their constructors must be public

  • Types that are inner classes must be static.

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

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

Let’s have a look at the following entity:

Example 6. A sample entity
class Person {

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

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

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

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

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

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

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

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

2.1.3. General recommendations

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

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

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

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

  • For identifiers to be generated, still use a final field in combination with a wither method — 

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

2.1.4. Kotlin support

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

Kotlin object creation

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

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

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

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

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

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

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

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

Property population of Kotlin data classes

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

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

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

2.2. 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 7. 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;

@Document
public class User {

    @Id
    private String id;

    @Field
    private String firstname;

    @Field
    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). Alternatively, you can configure the expiry using Spring’s property support and the expiryExpression parameter, to allow for dynamically changing the expiry value. For example: @Document(expiryExpression = "${valid.document.expiry}"). The property must be resolvable to an int value and the two approaches cannot be mixed.

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.

2.3. 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

string

string

boolean

boolean

byte

number

short

number

int

number

long

number

float

number

double

number

null

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 8. A Document with Map and List
@Document
public class User {

    @Id
    private String id;

    @Field
    private List<String> firstnames;

    @Field
    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 9. A Document with Map and List - JSON
{
    "_class": "foo.User",
    "childrenAges": {
        "Alice": 10,
        "Bob": 5
    },
    "firstnames": [
        "Foo",
        "Bar",
        "Baz"
    ]
}

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 10. A Document with composed objects
@Document
public class User {

    @Id
    private String id;

    @Field
    private List<String> firstnames;

    @Field
    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 11. A Document with composed objects - JSON
{
  "_class": "foo.User",
  "children": [
    {
      "age": 4,
      "name": "Alice"
    },
    {
      "age": 3,
      "name": "Bob"
    }
  ],
  "firstnames": [
    "Foo",
    "Bar",
    "Baz"
  ]
}

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 12. A Document with Date and Calendar
@Document
public class BlogPost {

    @Id
    private String id;

    @Field
    private Date created;

    @Field
    private Calendar updated;

    @Field
    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 13. A Document with Date and Calendar - JSON
{
  "title": "a blog post title",
  "_class": "foo.BlogPost",
  "updated": 1394610843,
  "created": 1394610843897
}

Optionally, Date can be converted to and from ISO-8601 compliant strings by setting system property org.springframework.data.couchbase.useISOStringConverterForDate to true. 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 14. Custom Converters
@Override
public CustomConversions customConversions() {
    return new CustomConversions(Arrays.asList(FooToBarConverter.INSTANCE, BarToFooConverter.INSTANCE));
}

@WritingConverter
public static enum FooToBarConverter implements Converter<Foo, Bar> {
    INSTANCE;

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

}

@ReadingConverter
public static enum BarToFooConverter implements Converter<Bar, Foo> {
    INSTANCE;

    @Override
    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.

2.4. 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 15. A Document with optimistic locking.
@Document
public class User {

        @Version
        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.

2.5. 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 16. Validation dependencies
<dependency>
  <groupId>javax.validation</groupId>
  <artifactId>validation-api</artifactId>
</dependency>
<dependency>
  <groupId>org.hibernate</groupId>
  <artifactId>hibernate-validator</artifactId>
</dependency>

Now you need to add two beans to your configuration:

Example 17. Validation beans
@Bean
public LocalValidatorFactoryBean validator() {
    return new LocalValidatorFactoryBean();
}

@Bean
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 18. Sample Validation Annotation
@Size(min = 10)
@Field
private String name;

2.6. 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 19. Sample Auditing Entity
@Document
public class AuditedItem {

  @Id
  private final String id;

  private String value;

  @CreatedBy
  private String creator;

  @LastModifiedBy
  private String lastModifiedBy;

  @LastModifiedDate
  private Date lastModification;

  @CreatedDate
  private Date creationDate;

  @Version
  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 20. Sample AuditorAware implementation
public class NaiveAuditorAware implements AuditorAware<String> {

  private String auditor = "auditor";

  @Override
  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 21. Sample Auditing Configuration
@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
    @Bean
    public NaiveAuditorAware testAuditorAware() {
      return new NaiveAuditorAware();
    }

3. 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.

3.1. 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 22. Annotation for GeneratedValue
@Document
public class User {
     @Id @GeneratedValue(strategy = USE_ATTRIBUTES, delimiter = ".")
     private String id;
     @IdPrefix(order=0)
     private String userPrefix;
     @IdSuffix(order=0)
     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 23. Common key settings in CouchbaseTemplate
@Autowired
CouchbaseTemplate couchbaseTemplate;
...
couchbaseTemplate.keySettings(KeySettings.build().prefix("ApplicationA").suffix("Server1").delimiter("::"));

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 24. Standalone key generation in CouchbaseTemplate
@Autowired
CouchbaseTemplate couchbaseTemplate;
...
String id = couchbaseTemplate.getGeneratedId(entity);
...
repo.exists(id);

3.2. 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 25. Annotation for IdAttribute
@Document
public class User {
     @Id @GeneratedValue(strategy = USE_ATTRIBUTES)
     private String id;
     @IdAttribute
     private String userid;
     ...
}

3.3. 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 26. Annotation for Unique key generation
@Document
public class User {
     @Id @GeneratedValue(strategy = UNIQUE)
     private String id;
     ...
}

4. Working with Spring Data Repositories

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

Spring Data repository documentation and your module

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

4.1. Core concepts

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

Example 27. CrudRepository interface
public interface CrudRepository<T, ID> extends Repository<T, ID> {

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

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

  Iterable<T> findAll();               (3)

  long count();                        (4)

  void delete(T entity);               (5)

  boolean existsById(ID primaryKey);   (6)

  // … more functionality omitted.
}
1 Saves the given entity.
2 Returns the entity identified by the given ID.
3 Returns all entities.
4 Returns the number of entities.
5 Deletes the given entity.
6 Indicates whether an entity with the given ID exists.
We also provide persistence technology-specific abstractions, such as JpaRepository or MongoRepository. Those interfaces extend CrudRepository and expose the capabilities of the underlying persistence technology in addition to the rather generic persistence technology-agnostic interfaces such as CrudRepository.

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

Example 28. PagingAndSortingRepository interface
public interface PagingAndSortingRepository<T, ID> extends CrudRepository<T, ID> {

  Iterable<T> findAll(Sort sort);

  Page<T> findAll(Pageable pageable);
}

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

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

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

Example 29. Derived Count Query
interface UserRepository extends CrudRepository<User, Long> {

  long countByLastname(String lastname);
}

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

Example 30. Derived Delete Query
interface UserRepository extends CrudRepository<User, Long> {

  long deleteByLastname(String lastname);

  List<User> removeByLastname(String lastname);
}

4.2. Query methods

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

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

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

  2. Declare query methods on the interface.

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

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

    1. To use Java configuration, create a class similar to the following:

      import org.springframework.data.jpa.repository.config.EnableJpaRepositories;

@EnableJpaRepositories
class Config { … }

    2. To use XML configuration, define a bean similar to the following:

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

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

</beans>

    The JPA namespace is used in this example. If you use the repository abstraction for any other store, you need to change this to the appropriate namespace declaration of your store module. In other words, you should exchange jpa in favor of, for example, mongodb.

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

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

    class SomeClient {

  private final PersonRepository repository;

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

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

The sections that follow explain each step in detail:

4.3. Defining Repository Interfaces

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

4.3.1. Fine-tuning Repository Definition

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

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

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

Example 31. Selectively exposing CRUD methods
@NoRepositoryBean
interface MyBaseRepository<T, ID> extends Repository<T, ID> {

  Optional<T> findById(ID id);

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

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

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

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

4.3.2. Using Repositories with Multiple Spring Data Modules

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

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

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

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

Example 32. Repository definitions using module-specific interfaces
interface MyRepository extends JpaRepository<User, Long> { }

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

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

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

The following example shows a repository that uses generic interfaces:

Example 33. Repository definitions using generic interfaces
interface AmbiguousRepository extends Repository<User, Long> { … }

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

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

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

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

Example 34. Repository definitions using domain classes with annotations
interface PersonRepository extends Repository<Person, Long> { … }

@Entity
class Person { … }

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

@Document
class User { … }

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

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

Example 35. Repository definitions using domain classes with mixed annotations
interface JpaPersonRepository extends Repository<Person, Long> { … }

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

@Entity
@Document
class Person { … }

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

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

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

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

Example 36. Annotation-driven configuration of base packages
@EnableJpaRepositories(basePackages = "com.acme.repositories.jpa")
@EnableMongoRepositories(basePackages = "com.acme.repositories.mongo")
class Configuration { … }

4.4. Defining Query Methods

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

  • By deriving the query from the method name directly.

  • By using a manually defined query.

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

4.4.1. Query Lookup Strategies

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

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

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

  • CREATE_IF_NOT_FOUND (default) combines CREATE and USE_DECLARED_QUERY. It looks up a declared query first, and, if no declared query is found, it creates a custom method name-based query. This is the default lookup strategy and, thus, is used if you do not configure anything explicitly. It allows quick query definition by method names but also custom-tuning of these queries by introducing declared queries as needed.

4.4.2. Query Creation

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

Example 37. Query creation from method names
interface PersonRepository extends Repository<Person, Long> {

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

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

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

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

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

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

  • The method parser supports setting an IgnoreCase flag for individual properties (for example, findByLastnameIgnoreCase(…)) or for all properties of a type that supports ignoring case (usually String instances — for example, findByLastnameAndFirstnameAllIgnoreCase(…)). Whether ignoring cases is supported may vary by store, so consult the relevant sections in the reference documentation for the store-specific query method.

  • You can apply static ordering by appending an OrderBy clause to the query method that references a property and by providing a sorting direction (Asc or Desc). To create a query method that supports dynamic sorting, see “Special parameter handling”.

4.4.3. Property Expressions

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

List<Person> findByAddressZipCode(ZipCode zipCode);

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

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

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

List<Person> findByAddress_ZipCode(ZipCode zipCode);

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

4.4.4. Special parameter handling

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

Example 38. Using Pageable, Slice, and Sort in query methods
Page<User> findByLastname(String lastname, Pageable pageable);

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

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

List<User> findByLastname(String lastname, Pageable pageable);
APIs taking Sort and Pageable expect non-null values to be handed into methods. If you don’t want to apply any sorting or pagination use Sort.unsorted() and Pageable.unpaged().

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

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

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

Simple sorting expressions can be defined by using property names. Expressions can be concatenated to collect multiple criterias into one expression.

Example 39. Defining sort expressions
Sort sort = Sort.by("firstname").ascending()
  .and(Sort.by("lastname").descending());

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

Example 40. Defining sort expressions using the type-safe API
TypedSort<Person> person = Sort.sort(Person.class);

TypedSort<Person> sort = person.by(Person::getFirstname).ascending()
  .and(person.by(Person::getLastname).descending());

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

Example 41. Defining sort expressions using the Querydsl API
QSort sort = QSort.by(QPerson.firstname.asc())
  .and(QSort.by(QPerson.lastname.desc()));

4.4.5. Limiting Query Results

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

Example 42. Limiting the result size of a query with Top and First
User findFirstByOrderByLastnameAsc();

User findTopByOrderByAgeDesc();

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

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

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

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

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

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

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

4.4.6. Repository Methods Returning Collections or Iterables

Query methods that return multiple results can use standard Java Iterable, List, Set. Beyond that we support returning Spring Data’s Streamable, a custom extension of Iterable, as well as collection types provided by Vavr.

Using Streamable as Query Method Return Type

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

Example 43. Using Streamable to combine query method results
interface PersonRepository extends Repository<Person, Long> {
  Streamable<Person> findByFirstnameContaining(String firstname);
  Streamable<Person> findByLastnameContaining(String lastname);
}

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

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

  1. The type implements Streamable.

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

A sample use case looks as follows:

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

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

  private Streamable<Product> streamable;

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

interface ProductRepository implements Repository<Product, Long> {
  Products findAllByDescriptionContaining(String text); (4)
}
1 A Product entity that exposes API to access the product’s price.
2 A wrapper type for a Streamable<Product> that can be constructed via Products.of(…) (factory method created via the Lombok annotation).
3 The wrapper type exposes additional API calculating new values on the Streamable<Product>.
4 That wrapper type can be used as query method return type directly. No need to return Stremable<Product> and manually wrap it in the repository client.
Support for Vavr Collections

Vavr is a library to embrace functional programming concepts in Java. It ships with a custom set of collection types that can be used as query method return types.

Vavr collection type Used Vavr implementation type Valid Java source types

io.vavr.collection.Seq

io.vavr.collection.List

java.util.Iterable

io.vavr.collection.Set

io.vavr.collection.LinkedHashSet

java.util.Iterable

io.vavr.collection.Map

io.vavr.collection.LinkedHashMap

java.util.Map

The types in the first column (or subtypes thereof) can be used as quer method return types and will get the types in the second column used as implementation type depending on the Java type of the actual query result (thrid column). Alternatively, Traversable (Vavr the Iterable equivalent) can be declared and we derive the implementation class from the actual return value, i.e. a java.util.List will be turned into a Vavr List/Seq, a java.util.Set becomes a Vavr LinkedHashSet/Set etc.

4.4.7. Null Handling of Repository Methods

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

  • com.google.common.base.Optional

  • scala.Option

  • io.vavr.control.Option

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

Nullability Annotations

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

  • @NonNullApi: Used on the package level to declare that the default behavior for parameters and return values is to not accept or produce null values.

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

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

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

Example 44. Declaring Non-nullability in package-info.java
@org.springframework.lang.NonNullApi
package com.acme;

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

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

Example 45. Using different nullability constraints
package com.acme;                                                       (1)

import org.springframework.lang.Nullable;

interface UserRepository extends Repository<User, Long> {

  User getByEmailAddress(EmailAddress emailAddress);                    (2)

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

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

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

Example 46. Using nullability constraints on Kotlin repositories
interface UserRepository : Repository<User, String> {

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

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

4.4.8. Streaming query results

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

Example 47. Stream the result of a query with Java 8 Stream<T>
@Query("select u from User u")
Stream<User> findAllByCustomQueryAndStream();

Stream<User> readAllByFirstnameNotNull();

@Query("select u from User u")
Stream<User> streamAllPaged(Pageable pageable);
A Stream potentially wraps underlying data store-specific resources and must, therefore, be closed after usage. You can either manually close the Stream by using the close() method or by using a Java 7 try-with-resources block, as shown in the following example:
Example 48. Working with a Stream<T> result in a try-with-resources block
try (Stream<User> stream = repository.findAllByCustomQueryAndStream()) {
  stream.forEach(…);
}
Not all Spring Data modules currently support Stream<T> as a return type.

4.4.9. Async query results

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

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

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

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

4.5. Creating Repository Instances

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

4.5.1. XML configuration

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

Example 49. Enabling Spring Data repositories via XML
<?xml version="1.0" encoding="UTF-8"?>
<beans:beans xmlns:beans="http://www.springframework.org/schema/beans"
  xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xmlns="http://www.springframework.org/schema/data/jpa"
  xsi:schemaLocation="http://www.springframework.org/schema/beans
    https://www.springframework.org/schema/beans/spring-beans.xsd
    http://www.springframework.org/schema/data/jpa
    https://www.springframework.org/schema/data/jpa/spring-jpa.xsd">

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

</beans:beans>

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

Using filters

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

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

Example 50. Using exclude-filter element
<repositories base-package="com.acme.repositories">
  <context:exclude-filter type="regex" expression=".*SomeRepository" />
</repositories>

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

4.5.2. JavaConfig

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

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

Example 51. Sample annotation based repository configuration
@Configuration
@EnableJpaRepositories("com.acme.repositories")
class ApplicationConfiguration {

  @Bean
  EntityManagerFactory entityManagerFactory() {
    // …
  }
}
The preceding example uses the JPA-specific annotation, which you would change according to the store module you actually use. The same applies to the definition of the EntityManagerFactory bean. See the sections covering the store-specific configuration.

4.5.3. Standalone usage

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

Example 52. Standalone usage of repository factory
RepositoryFactorySupport factory = … // Instantiate factory here
UserRepository repository = factory.getRepository(UserRepository.class);

4.6. Custom Implementations for Spring Data Repositories

This section covers repository customization and how fragments form a composite repository.

When a query method requires a different behavior or cannot be implemented by query derivation, then it is necessary to provide a custom implementation. Spring Data repositories let you provide custom repository code and integrate it with generic CRUD abstraction and query method functionality.

4.6.1. Customizing Individual Repositories

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

Example 53. Interface for custom repository functionality
interface CustomizedUserRepository {
  void someCustomMethod(User user);
}
Example 54. Implementation of custom repository functionality
class CustomizedUserRepositoryImpl implements CustomizedUserRepository {

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

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

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

Example 55. Changes to your repository interface
interface UserRepository extends CrudRepository<User, Long>, CustomizedUserRepository {

  // Declare query methods here
}

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

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

The following example shows custom interfaces and their implementations:

Example 56. Fragments with their implementations
interface HumanRepository {
  void someHumanMethod(User user);
}

class HumanRepositoryImpl implements HumanRepository {

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

interface ContactRepository {

  void someContactMethod(User user);

  User anotherContactMethod(User user);
}

class ContactRepositoryImpl implements ContactRepository {

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

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

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

Example 57. Changes to your repository interface
interface UserRepository extends CrudRepository<User, Long>, HumanRepository, ContactRepository {

  // Declare query methods here
}

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

The following example shows a repository fragment and its implementation:

Example 58. Fragments overriding save(…)
interface CustomizedSave<T> {
  <S extends T> S save(S entity);
}

class CustomizedSaveImpl<T> implements CustomizedSave<T> {

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

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

Example 59. Customized repository interfaces
interface UserRepository extends CrudRepository<User, Long>, CustomizedSave<User> {
}

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

If you use namespace configuration, the repository infrastructure tries to autodetect custom implementation fragments by scanning for classes below the package in which it found a repository. These classes need to follow the naming convention of appending the namespace element’s repository-impl-postfix attribute to the fragment interface name. This postfix defaults to Impl. The following example shows a repository that uses the default postfix and a repository that sets a custom value for the postfix:

Example 60. Configuration example
<repositories base-package="com.acme.repository" />

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

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

Resolution of Ambiguity

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

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

Example 61. Resolution of amibiguous implementations
package com.acme.impl.one;

class CustomizedUserRepositoryImpl implements CustomizedUserRepository {

  // Your custom implementation
}
package com.acme.impl.two;

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

  // Your custom implementation
}

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

Manual Wiring

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

Example 62. Manual wiring of custom implementations
<repositories base-package="com.acme.repository" />

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

4.6.2. Customize the Base Repository

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

Example 63. Custom repository base class
class MyRepositoryImpl<T, ID>
  extends SimpleJpaRepository<T, ID> {

  private final EntityManager entityManager;

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

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

  @Transactional
  public <S extends T> S save(S entity) {
    // implementation goes here
  }
}
The class needs to have a constructor of the super class which the store-specific repository factory implementation uses. If the repository base class has multiple constructors, override the one taking an EntityInformation plus a store specific infrastructure object (such as an EntityManager or a template class).

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

Example 64. Configuring a custom repository base class using JavaConfig
@Configuration
@EnableJpaRepositories(repositoryBaseClass = MyRepositoryImpl.class)
class ApplicationConfiguration { … }

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

Example 65. Configuring a custom repository base class using XML
<repositories base-package="com.acme.repository"
     base-class="….MyRepositoryImpl" />

4.7. Publishing Events from Aggregate Roots

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

Example 66. Exposing domain events from an aggregate root
class AnAggregateRoot {

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

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

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

4.8. Spring Data Extensions

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

4.8.1. Querydsl Extension

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

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

Example 67. QuerydslPredicateExecutor interface
public interface QuerydslPredicateExecutor<T> {

  Optional<T> findById(Predicate predicate);  (1)

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

  long count(Predicate predicate);            (3)

  boolean exists(Predicate predicate);        (4)

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

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

Example 68. Querydsl integration on repositories
interface UserRepository extends CrudRepository<User, Long>, QuerydslPredicateExecutor<User> {
}

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

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

userRepository.findAll(predicate);

4.8.2. Web support

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

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

Example 69. Enabling Spring Data web support
@Configuration
@EnableWebMvc
@EnableSpringDataWebSupport
class WebConfiguration {}

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

Alternatively, if you use XML configuration, register either SpringDataWebConfiguration or HateoasAwareSpringDataWebConfiguration as Spring beans, as shown in the following example (for SpringDataWebConfiguration):

Example 70. Enabling Spring Data web support in XML
<bean class="org.springframework.data.web.config.SpringDataWebConfiguration" />

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

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

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

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

DomainClassConverter

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

Example 71. A Spring MVC controller using domain types in method signatures
@Controller
@RequestMapping("/users")
class UserController {

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

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

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 findById(…) on the repository instance registered for the domain type.

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

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

Example 72. Using Pageable as controller method argument
@Controller
@RequestMapping("/users")
class UserController {

  private final UserRepository repository;

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

  @RequestMapping
  String showUsers(Model model, Pageable pageable) {

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

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

Table 2. Request parameters evaluated for Pageable instances

page

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

size

Size of the page you want to retrieve. Defaults to 20.

sort

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

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

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

If setting the properties of an existing MethodArgumentResolver is not sufficient for your purpose, extend either SpringDataWebConfiguration or the HATEOAS-enabled equivalent, override the pageableResolver() or sortResolver() methods, and import your customized configuration file instead of using the @Enable annotation.

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

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

you have to populate thing1_page and thing2_page and so on.

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

Hypermedia Support for Pageables

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

Example 73. Using a PagedResourcesAssembler as controller method argument
@Controller
class PersonController {

  @Autowired PersonRepository repository;

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

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

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

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

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

  • The PagedResources may get prev and next links attached, depending on the page’s state. The links point to the URI to which the method maps. The pagination parameters added to the method match the setup of the PageableHandlerMethodArgumentResolver to make sure the links can be resolved later.

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

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

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

Web Databinding Support

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

Example 74. HTTP payload binding using JSONPath or XPath expressions
@ProjectedPayload
public interface UserPayload {

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

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

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

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

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

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

Querydsl Web Support

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

Consider the following query string:

?firstname=Dave&lastname=Matthews

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

QUser.user.firstname.eq("Dave").and(QUser.user.lastname.eq("Matthews"))
The feature is automatically enabled, along with @EnableSpringDataWebSupport, when Querydsl is found on the classpath.

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

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

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

@Controller
class UserController {

  @Autowired UserRepository repository;

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

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

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

The default binding is as follows:

  • Object on simple properties as eq.

  • Object on collection like properties as contains.

  • Collection on simple properties as in.

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

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

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

    bindings.bind(user.username).first((path, value) -> path.contains(value))    (3)
    bindings.bind(String.class)
      .first((StringPath path, String value) -> path.containsIgnoreCase(value)); (4)
    bindings.excluding(user.password);                                           (5)
  }
}
1 QuerydslPredicateExecutor provides access to specific finder methods for Predicate.
2 QuerydslBinderCustomizer defined on the repository interface is automatically picked up and shortcuts @QuerydslPredicate(bindings=…​).
3 Define the binding for the username property to be a simple contains binding.
4 Define the default binding for String properties to be a case-insensitive contains match.
5 Exclude the password property from Predicate resolution.

4.8.3. Repository Populators

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

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

Example 75. Data defined in JSON
[ { "_class" : "com.acme.Person",
 "firstname" : "Dave",
  "lastname" : "Matthews" },
  { "_class" : "com.acme.Person",
 "firstname" : "Carter",
  "lastname" : "Beauford" } ]

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

Example 76. Declaring a Jackson repository populator
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
  xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xmlns:repository="http://www.springframework.org/schema/data/repository"
  xsi:schemaLocation="http://www.springframework.org/schema/beans
    https://www.springframework.org/schema/beans/spring-beans.xsd
    http://www.springframework.org/schema/data/repository
    https://www.springframework.org/schema/data/repository/spring-repository.xsd">

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

</beans>

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

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

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

Example 77. Declaring an unmarshalling repository populator (using JAXB)
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
  xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xmlns:repository="http://www.springframework.org/schema/data/repository"
  xmlns:oxm="http://www.springframework.org/schema/oxm"
  xsi:schemaLocation="http://www.springframework.org/schema/beans
    https://www.springframework.org/schema/beans/spring-beans.xsd
    http://www.springframework.org/schema/data/repository
    https://www.springframework.org/schema/data/repository/spring-repository.xsd
    http://www.springframework.org/schema/oxm
    https://www.springframework.org/schema/oxm/spring-oxm.xsd">

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

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

</beans>

5. 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)

5.1. 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 78. Annotation-Based Repository Setup
@Configuration
@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 79. XML-Based Repository Setup
<couchbase:repositories base-package="com.couchbase.example.repos" />

5.2. 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 80. 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.

5.3. Repositories and Querying

5.3.1. 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. DML queries are supported from Couchbase server version 4.1.

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 81. 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.

  • #n1ql.delete will be replaced by the delete from statement.

  • #n1ql.returning will be replaced by returning clause needed for reconstructing 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.

Note that you can mix N1QL placeholders and SpEL. N1QL placeholders will still consider all method parameters, so be sure to use the correct index like in the example below:

Example 82. An inline query that mixes SpEL and N1QL placeholders
@Query("#{#n1ql.selectEntity} WHERE #{#n1ql.filter} AND #{[0]} = $2")
public List<User> findUsersByDynamicCriteria(String criteriaField, Object criteriaValue)

This allows you to generate queries that would work similarly to eg. AND name = "someName" or AND age = 3, with a single method declaration.

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
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 {

  @Override
  public String getExtensionId() {
    return "security";
  }

  @Override
  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:

@Bean
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

Delete query example:

@Query("#{#n1ql.delete} WHERE #{#n1ql.filter} AND " +
"username = $1 #{#n1ql.returning}")
UserInfo removeUser(String username);

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

And

findByLastnameAndFirstname

lastName = a AND firstName = b

Or

findByLastnameOrFirstname

lastName = a OR firstName = b

Is,Equals

findByField,findByFieldEquals

field = a

IsNot,Not

findByFieldIsNot

field != a

Between

findByFieldBetween

field BETWEEN a AND b

IsLessThan,LessThan,IsBefore,Before

findByFieldIsLessThan,findByFieldBefore

field < a

IsLessThanEqual,LessThanEqual

findByFieldIsLessThanEqual

field ⇐ a

IsGreaterThan,GreaterThan,IsAfter,After

findByFieldIsGreaterThan,findByFieldAfter

field > a

IsGreaterThanEqual,GreaterThanEqual

findByFieldGreaterThanEqual

field >= a

IsNull

findByFieldIsNull

field IS NULL

IsNotNull,NotNull

findByFieldIsNotNull

field IS NOT NULL

IsLike,Like

findByFieldLike

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

IsNotLike,NotLike

findByFieldNotLike

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

IsStartingWith,StartingWith,StartsWith

findByFieldStartingWith

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

IsEndingWith,EndingWith,EndsWith

findByFieldEndingWith

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

IsContaining,Containing,Contains

findByFieldContains

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

IsNotContaining,NotContaining,NotContains

findByFieldNotContaining

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

IsIn,In

findByFieldIn

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

IsNotIn,NotIn

findByFieldNotIn

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)

IsTrue,True

findByFieldIsTrue

field = TRUE

IsFalse,False

findByFieldFalse

field = FALSE

MatchesRegex,Matches,Regex

findByFieldMatches

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

Exists

findByFieldExists

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

OrderBy

findByFieldOrderByLastnameDesc

field = a ORDER BY lastname DESC

IgnoreCase

findByFieldIgnoreCase

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.
If pageable and sort parameters are used with inline queries, there should not be any order by, limit or offset clause in the inline query itself otherwise the server would reject the query as malformed.

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.

5.3.2. 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 3. 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 83. 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.

5.3.3. 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 84. A Dev configuration where only @ViewIndexed annotations will be processed.
@Configuration
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
  @Override
  public IndexManager indexManager() {
    return new IndexManager(true, false, false);
  }
}

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

    @View
    List<UserInfo> findAllAdmins();

    @View(viewName="firstNames")
    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 86. 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 87. 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 88. 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)

Between

findByFieldBetween

startkey=A&endkey=B

IsLessThan,LessThan,IsBefore,Before

findByFieldIsLessThan,findByFieldBefore

endkey=A

IsLessThanEqual,LessThanEqual

findByFieldIsLessThanEqual

endkey=A&inclusive_end=true

IsGreaterThanEqual,GreaterThanEqual

findByFieldGreaterThanEqual

startkey=A

IsStartingWith,StartingWith,StartsWith

findByFieldStartingWith

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

IsIn,In

findByFieldIn

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.

5.3.5. 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

Within,IsWithin

findByLocationWithin

Near,IsNear

findByLocationNear

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

Between

findByLocationWithinAndOpeningHoursBetween

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

GreaterThan,GreaterThanEqual,After

findByLocationWithinAndOpeningHoursAfter

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

LessThan,LessThanEqual,Before

findByLocationWithinAndOpeningHoursBefore

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.

5.3.6. 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 three 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.
Set consistency for N1QL queries

For N1QL queries, the ScanConsistency can be set using the @WithConsistency annotation. This is independent of whether the query is derived from the method name or specified using @Query. If the annotation is omitted, the global default consistency is used. Consider the three queries in the following example:

Example 89. Setting the scan consistency on repository methods
public interface UserRepository extends CrudRepository<UserInfo, String> {

    List<UserInfo> findByLastname(String name); (1)

    @WithConsistency(ScanConsistency.NOT_BOUNDED)
    List<UserInfo> findByFirstname(String name); (2)

    @WithConsistency(ScanConsistency.NOT_BOUNDED)
    @Query("#{#n1ql.selectEntity} WHERE role = 'admin' AND #{#n1ql.filter}")
    List<UserInfo> findAllAdmins(); (3)
}
1 Since neither @Query nor @WithConsistency is specified, a N1QL query is derived from the method name and executed with default consistency.
2 The N1QL query is derived automatically but executed with the given consistency, i.e. NOT_BOUNDED.
3 The N1QL query is specified using @Query and is being executed with the given consistency.
The @WithConsistency annotation is currently only evaluated for N1QL queries. View queries use the global default consistency.
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));

5.4. 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 90. Example of configuring multiple templates and repositories.
@Configuration
@EnableCouchbaseRepositories
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...
  @Bean
  public Bucket userBucket() {
    return couchbaseCluster().openBucket("users", "");
  }

  //... then the template (inspired by couchbaseTemplate() method)...
  @Bean
  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
    );
    template.setDefaultConsistency(getDefaultConsistency());
    return template;
  }

  //... then finally make sure all repositories of Users will use it
  @Override
  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()
  }
}

5.5. 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).

5.5.1. 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);
  }

  @Override
  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.

5.5.2. 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)

  @Autowired
  RepositoryOperationsMapping templateProvider; (4)

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

    CouchbasePersistentEntity<Object> itemPersistenceEntity = (CouchbasePersistentEntity<Object>)
        template.getConverter()
            .getMappingContext()
            .getPersistentEntity(MyItem.class);

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

    Statement countStatement = N1qlUtils.createCountQueryForEntity( (6)
        template.getCouchbaseBucket().name(),
        template.getConverter(),
        itemEntityInformation);

    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

100
-3

5.5.3. DTO Projections

Spring Data Repositories usually return the domain model when using query methods. However, sometimes, you may need to alter the view of that model for various reasons. In this section, you will learn how to define projections to serve up simplified and reduced views of resources.

Look at the following domain model:

@Entity
public class Person {

  @Id @GeneratedValue
  private Long id;
  private String firstName, lastName;

  @OneToOne
  private Address address;
  …
}

@Entity
public class Address {

  @Id @GeneratedValue
  private Long id;
  private String street, state, country;

  …
}

This Person has several attributes:

  • id is the primary key

  • firstName and lastName are data attributes

  • address is a link to another domain object

Now assume we create a corresponding repository as follows:

interface PersonRepository extends CrudRepository<Person, Long> {

  Person findPersonByFirstName(String firstName);
}

Spring Data will return the domain object including all of its attributes. There are two options just to retrieve the address attribute. One option is to define a repository for Address objects like this:

interface AddressRepository extends CrudRepository<Address, Long> {}

In this situation, using PersonRepository will still return the whole Person object. Using AddressRepository will return just the Address.

However, what if you do not want to expose address details at all? You can offer the consumer of your repository service an alternative by defining one or more projections.

Example 91. Simple Projection
interface NoAddresses {  (1)

  String getFirstName(); (2)

  String getLastName();  (3)
}

This projection has the following details:

1 A plain Java interface making it declarative.
2 Export the firstName.
3 Export the lastName.

The NoAddresses projection only has getters for firstName and lastName meaning that it will not serve up any address information. The query method definition returns in this case NoAdresses instead of Person.

interface PersonRepository extends CrudRepository<Person, Long> {

  NoAddresses findByFirstName(String firstName);
}

Projections declare a contract between the underlying type and the method signatures related to the exposed properties. Hence it is required to name getter methods according to the property name of the underlying type. If the underlying property is named firstName, then the getter method must be named getFirstName otherwise Spring Data is not able to look up the source property.

6. Reactive Couchbase repository

6.1. Introduction

This chapter describes the reactive repository support for couchbase. This builds on the core repository support explained in Couchbase repositories. So make sure you’ve got a sound understanding of the basic concepts explained there.

6.2. Reactive Composition Libraries

Couchbase Java SDK 2.x has taken a reactive programming approach since its inception using an early reactive extension to JVM, RxJava1. It provides RxJava1 observable sequence API to compose asynchronous database operations.

Reactive Couchbase repositories provide project Reactor wrapper types and can be used by simply extending from one of the library-specific repository interfaces:

  • ReactiveCrudRepository

  • ReactiveSortingRepository

Spring-data-couchbase converts RxJava 1 observables to reactor types by using reactive-streams adapters from RxJavaReactiveStreams for convenience since these conversions can easily clutter application code. This transformation happens on same thread. It also provides direct access to RxJava1 observable sequence API from SDK through RxJavaCouchbaseOperations methods.

6.3. Usage

To access domain entities stored in a Couchbase bucket you can leverage our sophisticated repository support that eases implementing those quite significantly. To do so, simply create an interface for your repository:

Example 92. Sample Person entity
public class Person {

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

  // … getters and setters omitted
}

We have a quite simple domain object here.

Example 93. Basic repository interface to persist Person entities
public interface ReactivePersonRepository extends ReactiveSortingRepository<Person, Long> {

  Flux<Person> findByFirstname(String firstname);

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

  Flux<Person> findByFirstnameOrderByLastname(String firstname, Pageable pageable);

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

For JavaConfig use the @EnableReactiveCouchbaseRepositories annotation. The annotation carries the very same attributes like the namespace element. If no base package is configured the infrastructure will scan the package of the annotated configuration class.

Example 94. JavaConfig for repositories
@Configuration
@EnableReactiveCouchbaseRepositories
class ApplicationConfig extends AbstractReactiveCouchbaseConfiguration {

  @Override
  protected List<String> getBootstrapHosts() {
    return Collections.singletonList("127.0.0.1");
  }

  @Override
  protected String getBucketName() {
  		return "default";
  }

  @Override
  protected String getBucketPassword() {
 	return "";
 }
}

As our domain repository extends ReactiveSortingRepository it provides you with CRUD operations as well as methods for sorted access to the entities. Working with the repository instance is just a matter of dependency injecting it into a client.

Example 95. Sorted access to Person entities
public class PersonRepositoryTests {

    @Autowired
    ReactivePersonRepository repository;

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

6.4. Repositories and Querying

Spring Data’s Reactive Couchbase comes with full querying support already provided by the blocking Repositories and Querying

7. 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.

7.1. 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().

7.2. Xml Configuration

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

Example 96. XML Based Template Declaration
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
       xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
       xmlns:couchbase="http://www.springframework.org/schema/data/couchbase"
       xsi:schemaLocation="http://www.springframework.org/schema/data/couchbase https://www.springframework.org/schema/data/couchbase/spring-couchbase.xsd
		http://www.springframework.org/schema/beans https://www.springframework.org/schema/beans/spring-beans.xsd">

    <couchbase:env/>
    <couchbase:cluster/>
    <couchbase:clusterInfo/>
    <couchbase:bucket/>

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

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

</beans>
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.

8. ANSI Joins

This chapter describes hows ANSI joins can be used across entities. Since 5.5 version, Couchbase server provides support for ANSI joins for joining documents using fields. Previous versions allowed index & lookup joins, which were supported in SDC only by querying directly through the SDK.

Relationships between entities across repositories can be one to one or one to many. By defining such relationships, a synchronized view of associated entities can be fetched.

8.1. Configuration

Associated entities can be fetched by annotating the entity’s property reference with @N1qlJoin. The prefix lks refers to left-hand side key space (current entity) and rks refers to the right-hand side key space (associated entity). The required element for @N1qlJoin annotation is the on clause, a boolean expression representing the join condition between the left-hand side (lks) and the right-hand side (rks), which can be fields, constant expressions or any complex N1QL expression. There could also be an optional where clause specified on the annotation for the join, similarly using lks to refer the current entity and rks to refer the associated entity.

Example 97. Annotation for ANSI Join
@Document
public class Author {
      @Id
      String id;

      String name;

      @N1qlJoin(on = "lks.name=rks.authorName")
      List<Book> books;

      @N1qlJoin(on = "lks.name=rks.name")
      Address address;
     ...
}

8.2. Lazy fetching

Associated entities can be lazily fetched upon the first access of the property, this could save on fetching more data than required when loading the entity. To load the associated entities lazily, @N1qlJoin annotation’s element fetchType has to be set to FetchType.LAZY. The default is FetchType.IMMEDIATE.

Example 98. Configuration for lazy fetch
@N1qlJoin(on = "lks.name=rks.authorName", fetchType = FetchType.LAZY)
List<Book> books;

8.3. ANSI Join Hints

8.3.1. Use Index Hint

index element on the @N1qlJoin can be used to provided the hint for the lks (current entity) index and rightIndex element can be used to provided the rks (associated entity) index.

8.3.2. Hash Join Hint

If the join type is going to be hash join, the hash side can be specified for the rks (associated entity). If the associated entity is on the build side, it can be specified as HashSide.BUILD else HashSide.PROBE.

8.3.3. Use Keys Hint

keys element on the @N1qlJoin annotation can be used to specify unique document keys to restrict the join key space. :leveloffset: -1

9. Appendix

Appendix A: Namespace reference

The <repositories /> Element

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

Table 7. Attributes
Name Description

base-package

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

repository-impl-postfix

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

query-lookup-strategy

Determines the strategy to be used to create finder queries. See “Query Lookup Strategies” for details. Defaults to create-if-not-found.

named-queries-location

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

consider-nested-repositories

Whether nested repository interface definitions should be considered. Defaults to false.

Appendix B: Populators namespace reference

The <populator /> element

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

Table 8. Attributes
Name Description

locations

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

Appendix C: Repository query keywords

Supported query keywords

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

Table 9. Query keywords
Logical keyword Keyword expressions

AND

And

OR

Or

AFTER

After, IsAfter

BEFORE

Before, IsBefore

CONTAINING

Containing, IsContaining, Contains

BETWEEN

Between, IsBetween

ENDING_WITH

EndingWith, IsEndingWith, EndsWith

EXISTS

Exists

FALSE

False, IsFalse

GREATER_THAN

GreaterThan, IsGreaterThan

GREATER_THAN_EQUALS

GreaterThanEqual, IsGreaterThanEqual

IN

In, IsIn

IS

Is, Equals, (or no keyword)

IS_EMPTY

IsEmpty, Empty

IS_NOT_EMPTY

IsNotEmpty, NotEmpty

IS_NOT_NULL

NotNull, IsNotNull

IS_NULL

Null, IsNull

LESS_THAN

LessThan, IsLessThan

LESS_THAN_EQUAL

LessThanEqual, IsLessThanEqual

LIKE

Like, IsLike

NEAR

Near, IsNear

NOT

Not, IsNot

NOT_IN

NotIn, IsNotIn

NOT_LIKE

NotLike, IsNotLike

REGEX

Regex, MatchesRegex, Matches

STARTING_WITH

StartingWith, IsStartingWith, StartsWith

TRUE

True, IsTrue

WITHIN

Within, IsWithin

Appendix D: Repository query return types

Supported Query Return Types

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

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

void

Denotes no return value.

Primitives

Java primitives.

Wrapper types

Java wrapper types.

T

A unique entity. Expects the query method to return one result at most. If no result is found, null is returned. More than one result triggers an IncorrectResultSizeDataAccessException.

Iterator<T>

An Iterator.

Collection<T>

A Collection.

List<T>

A List.

Optional<T>

A Java 8 or Guava Optional. Expects the query method to return one result at most. If no result is found, Optional.empty() or Optional.absent() is returned. More than one result triggers an IncorrectResultSizeDataAccessException.

Option<T>

Either a Scala or Vavr Option type. Semantically the same behavior as Java 8’s Optional, described earlier.

Stream<T>

A Java 8 Stream.

Streamable<T>

A convenience extension of Iterable that directy exposes methods to stream, map and filter results, concatenate them etc.

Types that implement Streamable and take a Streamable constructor or factory method argument

Types that expose a constructor or ….of(…)/….valueOf(…) factory method taking a Streamable as argument. See Returning Custom Streamable Wrapper Types for details.

Vavr Seq, List, Map, Set

Vavr collection types. See Support for Vavr Collections for details.

Future<T>

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

CompletableFuture<T>

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

ListenableFuture

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

Slice

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

Page<T>

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

GeoResult<T>

A result entry with additional information, such as the distance to a reference location.

GeoResults<T>

A list of GeoResult<T> with additional information, such as the average distance to a reference location.

GeoPage<T>

A Page with GeoResult<T>, such as the average distance to a reference location.

Mono<T>

A Project Reactor Mono emitting zero or one element using reactive repositories. Expects the query method to return one result at most. If no result is found, Mono.empty() is returned. More than one result triggers an IncorrectResultSizeDataAccessException.

Flux<T>

A Project Reactor Flux emitting zero, one, or many elements using reactive repositories. Queries returning Flux can emit also an infinite number of elements.

Single<T>

A RxJava Single emitting a single element using reactive repositories. Expects the query method to return one result at most. If no result is found, Mono.empty() is returned. More than one result triggers an IncorrectResultSizeDataAccessException.

Maybe<T>

A RxJava Maybe emitting zero or one element using reactive repositories. Expects the query method to return one result at most. If no result is found, Mono.empty() is returned. More than one result triggers an IncorrectResultSizeDataAccessException.

Flowable<T>

A RxJava Flowable emitting zero, one, or many elements using reactive repositories. Queries returning Flowable can emit also an infinite number of elements.
1. see XML configuration