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

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

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

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

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

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

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 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. Assume a Person has an Address with a ZipCode. In that case a method name of

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.

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

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 JavaConfig this is achieved by using the repositoryBaseClass attribute of the @Enable…Repositories annotation:

A corresponding attribute is available in the XML namespace.

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

Several Spring Data modules offer integration with Querydsl via QueryDslPredicateExecutor.

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

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

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

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

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

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

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

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

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

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

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

Create a properties file with the information you need to connect to Cassandra. The contact points are keyspace are the minimal required fields, but port is added here for clarity.

We will call this cassandra.properties

We will use spring to load these properties into the Spring Context in the next two examples.

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

While this example show how easy it is to configure Spring to connect to Cassandra, there are many other options. Basically, any option available with the DataStax Java Driver is also available in the Spring Data Cassandra configuration. This is including, but not limited to Authentication, Load Balancing Policies, Retry Policies and Pooling Options. All of the Spring Data Cassandra method names and XML elements are named exactly (or as close as possible) like the configuration options on the driver so mapping any existing driver configuration should be straight forward.

The following class show a basic and minimal Cassandra configuration using the AnnotationConfigApplicationContext (aka JavaConfig).

CassandraTemplate should always be configured as a Spring Bean, although we show an example above where you can instantiate it directly. But for the purposes of this being a Spring module, lets assume we are using the Spring Container.

CassandraTemplate is an implementation of CassandraOperations. You should always assign your CassandraTemplate to its interface definition, CassandraOperations.

There are 2 easy ways to get a CassandraTemplate, depending on how you load you Spring Application Context.

Like all Spring Autowiring, this assumes there is only one bean of type CassandraOperations in the ApplicationContext. If you have multiple CassandraTemplate beans (which will be the case if you are working with multiple keyspaces in the same project), use the `@Qualifier`annotation to designate which bean you want to Autowire.

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

Cassandra requires that you have at least 1 Partition Key field for a CQL Table. Alternately, you can have one or more Clustering Key fields. When your CQL Table has a composite Primary Key field you must create a @PrimaryKeyClass to define the structure of the composite PK. In this context, composite PK means one or more partition columns, or 1 partition column plus one or more clustering columns.

Spring Data Cassandra relies on the DataStax Java Driver type mapping component. This approach ensures that as types are added or changed, the Spring Data Cassandra module will continue to function without requiring changes. For more information on the DataStax CQL3 to Java Type mappings, please see their Documentation here.

Much like inserting, there are several flavors of update from which you can choose.

Update a record with an annotated POJO.

Update a row using the QueryBuilder.Update object that is part of the DataStax Java Driver.

Then there is always the old fashioned way. You can write your own CQL statements.

Much like inserting, there are several flavors of delete from which you can choose.

Delete a record with an annotated POJO.

Delete a row using the QueryBuilder.Delete object that is part of the DataStax Java Driver.

Then there is always the old fashioned way. You can write your own CQL statements.

Much like inserting, there are several flavors of truncate from which you can choose.

Truncate a table using the truncate() method.

Truncate a table using the QueryBuilder.Truncate object that is part of the DataStax Java Driver.

Then there is always the old fashioned way. You can write your own CQL statements.

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

This example uses the basic AsynchronousQueryListener that comes with Spring Data Cassandra. Please see the API documentation for all the options. There should be nothing you cannot perform in Cassandra with the execute() and executeAsync() methods.

This example shows how to create and drop a table, using different API objects, all passed to the execute() methods.

The Spring Data Cassandra CDI extension will pick up the CassandraTemplate available as CDI bean and create a proxy for a Spring Data repository whenever an bean of a repository type is requested by the container. Thus obtaining an instance of a Spring Data repository is a matter of declaring an @Inject-ed property:

TODO

Unless explicitly configured, an instance of CassandraMappingConverter is created by default when creating a CassandraTemplate . You can create your own instance of the MappingCassandraConverter so as to tell it where to scan the classpath at startup your domain classes in order to extract metadata and construct indexes. Also, by creating your own instance you can register Spring converters to use for mapping specific classes to and from the database.

You can configure the CassandraMappingConverter and CassandraTemplate either using Java or XML based metadata. Here is an example using Spring’s Java based configuration