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.

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

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

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:

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

The following example shows a repository that uses generic interfaces:

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

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

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:

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.

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:

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:

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:

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:

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).

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:

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.

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:

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.

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:

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:

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:

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.

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:

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:

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

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

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

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

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

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

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

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

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

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

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:

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

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

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:

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):

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:

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:

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:

The Spring Data Solr module contains a custom namespace allowing definition of repository beans as well as elements for instantiating a SolrClient .

Using the repositories element looks up Spring Data repositories as described in Creating Repository Instances .

Using the solr-server or embedded-solr-server element registers an instance of SolrClient in the context.

The Spring Data Solr repositories support cannot only be activated through an XML namespace but also using an annotation through JavaConfig.

The configuration above sets up an EmbeddedSolrServer which is used by the SolrTemplate . Spring Data Solr Repositories are activated using the @EnableSolrRepositories annotation, which essentially carries the same attributes as the XML namespace does. If no base package is configured, it will use the one the configuration class resides in.

Solr handles different collections within one core. Use MulticoreSolrClientFactory to create separate SolrClient for each core.

The Spring Data Solr repositories can also be set up using CDI functionality.

Solr supports transactions on server level means create, updaet, delete actions since the last commit/optimize/rollback are queued on the server and committed/optimized/rolled back at once. Spring Data Solr Repositories will participate in Spring Managed Transactions and commit/rollback changes on complete.

The Solr module supports defining a query manually as String or have it being derived from the method name. NOTE: There is no QueryDSL Support present at this time.

Generally the query creation mechanism for Solr works as described in Query methods . Here’s a short example of what a Solr query method translates into:

The method name above will be translated into the following solr query

A list of supported keywords for Solr is shown below.

Using named queries ( Using NamedQueries ) to declare queries for entities is a valid approach and works fine for a small number of queries. As the queries themselves are tied to the Java method that executes them, you actually can bind them directly using the Spring Data Solr @Query annotation.

Named queries can be kept in a properties file and wired to the accroding method. Please mind the naming convention described in Query Lookup Strategies or use @Query .

MappingSolrConverter allows you to register custom converters for your SolrDocument and SolrInputDocument as well as for other types nested within your beans. The Converter is not 100% compartible with DocumentObjectBinder and @Indexed has to be added with readonly=true to ignore fields from beeing written to solr.

Taking a look as the above MappingSolrConverter will do as follows:

To register a custom converter one must add CustomConversions to SolrTemplate initializing it with own Converter implementation.

Range faceting queries may be done by configure required ranges on FacetOptions. A simple way to request ranges would be by creating a FacetOption, setting this options to a FacetQuery and query for a facet page through SolrTemplate as follows.

There are two implementations of fields for facet range requests:

Additionally the following properties can be configured for a field with range parameters (org.springframework.data.solr.core.query.FacetOptions.FieldWithRangeParameters):

Pivot faceting (Decision Tree) are also supported, and can be queried using @Facet annotation as follows:

Alternatively it can be queried using SolrTemplate as follows:

In order to retrieve the pivot results the method getPivot can be used as follows:

Boosting documents score can be done on index time by using @SolrDocument annotation on classes (for Solr documents) and/or @Indexed on fields (for Solr fields).

Spellcheck query parameters are added to request when SpellcheckOptions are set.

The @Spellcheck annotations allows usage of the spellcheck feature on Repository level.

In order to load score information of a query result, a field annotated with @Score annotation could be added, indicating the property holding the documents score.