You can use the Spring Boot Starter for Spring Data Datastore to autoconfigure Google Cloud Datastore in your Spring application. It contains all the necessary setup that makes it easy to authenticate with your Google Cloud project. The following configuration options are available:

Spring Data Repositories can be configured via the @EnableDatastoreRepositories annotation on your main @Configuration class. With our Spring Boot Starter for Spring Data Cloud Datastore, @EnableDatastoreRepositories is automatically added. It is not required to add it to any other class, unless there is a need to override finer grain configuration parameters provided by @EnableDatastoreRepositories.

Our Spring Boot autoconfiguration creates the following beans available in the Spring application context:

This Spring Boot autoconfiguration can also configure and start a local Datastore Emulator server if enabled by property.

It is useful for integration testing, but not for production.

When enabled, the spring.cloud.gcp.datastore.host property will be ignored and the Datastore autoconfiguration itself will be forced to connect to the autoconfigured local emulator instance.

It will create an instance of LocalDatastoreHelper as a bean that stores the DatastoreOptions to get the Datastore client connection to the emulator for convenience and lower level API for local access. The emulator will be properly stopped after the Spring application context shutdown.

Simple constructors are supported on POJOs. The constructor arguments can be a subset of the persistent properties. Every constructor argument needs to have the same name and type as a persistent property on the entity and the constructor should set the property from the given argument. Arguments that are not directly set to properties are not supported.

The @Entity annotation can provide the name of the Cloud Datastore kind that stores instances of the annotated class, one per row.

@Id identifies the property corresponding to the ID value.

You must annotate one of your POJO’s fields as the ID value, because every entity in Cloud Datastore requires a single ID value:

Datastore can automatically allocate integer ID values. If a POJO instance with a Long ID property is written to Cloud Datastore with null as the ID value, then Spring Data Cloud Datastore will obtain a newly allocated ID value from Cloud Datastore and set that in the POJO for saving. Because primitive long ID properties cannot be null and default to 0, keys will not be allocated.

All accessible properties on POJOs are automatically recognized as a Cloud Datastore field. Field naming is generated by the PropertyNameFieldNamingStrategy by default defined on the DatastoreMappingContext bean. The @Field annotation optionally provides a different field name than that of the property.

Spring Data Cloud Datastore supports the following types for regular fields and elements of collections:

In addition, all types that can be converted to the ones listed in the table by org.springframework.core.convert.support.DefaultConversionService are supported.

Custom converters can be used extending the type support for user defined types.

For example:

We would like to have a field of type Album on our Singer POJO and want it to be stored as a string property:

Where Album is a simple class:

We have to define the two converters:

That will be configured in our @Configuration file:

Arrays and collections (types that implement java.util.Collection) of supported types are supported. They are stored as com.google.cloud.datastore.ListValue. Elements are converted to Cloud Datastore supported types individually. byte[] is an exception, it is converted to com.google.cloud.datastore.Blob.

Users can provide converters from List<?> to the custom collection type. Only read converter is necessary, the Collection API is used on the write side to convert a collection to the internal list type.

Collection converters need to implement the org.springframework.core.convert.converter.Converter interface.

Example:

Let’s improve the Singer class from the previous example. Instead of a field of type Album, we would like to have a field of type Set<Album>:

We have to define a read converter only:

And add it to the list of custom converters:

Java entity types related by inheritance can be stored in the same Kind. When reading and querying entities using DatastoreRepository or DatastoreTemplate with a superclass as the type parameter, you can receive instances of subclasses if you annotate the superclass and its subclasses with DiscriminatorField and DiscriminatorValue:

Instances of all 3 types are stored in the pets Kind. Because a single Kind is used, all classes in the hierarchy must share the same ID property and no two instances of any type in the hierarchy can share the same ID value.

Entity rows in Cloud Datastore store their respective types' DiscriminatorValue in a field specified by the root superclass’s DiscriminatorField (pet_type in this case). Reads and queries using a given type parameter will match each entity with its specific type. For example, reading a List<Pet> will produce a list containing instances of all 3 types. However, reading a List<Dog> will produce a list containing only Dog and Pug instances. You can include the pet_type discrimination field in your Java entities, but its type must be convertible to a collection or array of String. Any value set in the discrimination field will be overwritten upon write to Cloud Datastore.

Fields whose types are also annotated with @Entity are converted to EntityValue and stored inside the parent entity.

Here is an example of Cloud Datastore entity containing an embedded entity in JSON:

This corresponds to a simple pair of Java entities:

Child entities are not stored in their own kind. They are stored in their entirety in the child field of the parents kind.

Multiple levels of embedded entities are supported.

Example:

Entities can hold embedded entities that are their own type. We can store trees in Cloud Datastore using this feature:

Parent-child relationships are supported via the @Descendants annotation.

Unlike embedded children, descendants are fully-formed entities residing in their own kinds. The parent entity does not have an extra field to hold the descendant entities. Instead, the relationship is captured in the descendants' keys, which refer to their parent entities:

For example, an instance of a GQL key-literal representation for Item would also contain the parent ShoppingOrder ID value:

The GQL key-literal representation for the parent ShoppingOrder would be:

The Cloud Datastore entities exist separately in their own kinds.

The ShoppingOrder:

The two items inside that order:

The parent-child relationship structure of objects is stored in Cloud Datastore using Datastore’s ancestor relationships. Because the relationships are defined by the Ancestor mechanism, there is no extra column needed in either the parent or child entity to store this relationship. The relationship link is part of the descendant entity’s key value. These relationships can be many levels deep.

Properties holding child entities must be collection-like, but they can be any of the supported inter-convertible collection-like types that are supported for regular properties such as List, arrays, Set, etc…​ Child items must have Key as their ID type because Cloud Datastore stores the ancestor relationship link inside the keys of the children.

Reading or saving an entity automatically causes all subsequent levels of children under that entity to be read or saved, respectively. If a new child is created and added to a property annotated @Descendants and the key property is left null, then a new key will be allocated for that child. The ordering of the retrieved children may not be the same as the ordering in the original property that was saved.

Child entities cannot be moved from the property of one parent to that of another unless the child’s key property is set to null or a value that contains the new parent as an ancestor. Since Cloud Datastore entity keys can have multiple parents, it is possible that a child entity appears in the property of multiple parent entities. Because entity keys are immutable in Cloud Datastore, to change the key of a child you must delete the existing one and re-save it with the new key.

General relationships can be stored using the @Reference annotation.

@Reference relationships are between fully-formed entities residing in their own kinds. The relationship between ShoppingOrder and Item entities are stored as a Key field inside ShoppingOrder, which are resolved to the underlying Java entity type by Spring Data Cloud Datastore:

Reference properties can either be singular or collection-like. These properties correspond to actual columns in the entity and Cloud Datastore Kind that hold the key values of the referenced entities. The referenced entities are full-fledged entities of other Kinds.

Similar to the @Descendants relationships, reading or writing an entity will recursively read or write all of the referenced entities at all levels. If referenced entities have null ID values, then they will be saved as new entities and will have ID values allocated by Cloud Datastore. There are no requirements for relationships between the key of an entity and the keys that entity holds as references. The order of collection-like reference properties is not preserved when reading back from Cloud Datastore.

In addition to retrieving entities by their IDs, you can also submit queries.

These methods, respectively, allow querying for:

Using DatastoreTemplate you can find entities by id. For example:

Cloud Datastore uses key-based reads with strong consistency, but queries with eventual consistency. In the example above the first two reads utilize keys, while the third is run by using a query based on the corresponding Kind of Trader.

The write methods of DatastoreOperations accept a POJO and writes all of its properties to Datastore. The required Datastore kind and entity metadata is obtained from the given object’s actual type.

If a POJO was retrieved from Datastore and its ID value was changed and then written or updated, the operation will occur as if against a row with the new ID value. The entity with the original ID value will not be affected.

The save method behaves as update-or-insert.

Read and write transactions are provided by DatastoreOperations via the performTransaction method:

The performTransaction method accepts a Function that is provided an instance of a DatastoreOperations object. The final returned value and type of the function is determined by the user. You can use this object just as you would a regular DatastoreOperations with an exception:

Because of Cloud Datastore’s consistency guarantees, there are limitations to the operations and relationships among entities used inside transactions.

You can work with Maps of type Map<String, ?> instead of with entity objects by directly reading and writing them to and from Cloud Datastore.

The map keys are used as field names for a Datastore entity and map values are converted to Datastore supported types. Only simple types are supported (i.e. collections are not supported). Converters for custom value types can be added (see Custom types section).

Example:

In the example above the query methods in TradeRepository are generated based on the name of the methods using the Spring Data Query creation naming convention.

Cloud Datastore only supports filter components joined by AND, and the following operations:

After writing a custom repository interface specifying just the signatures of these methods, implementations are generated for you and can be used with an auto-wired instance of the repository. Because of Cloud Datastore’s requirement that explicitly selected fields must all appear in a composite index together, find name-based query methods are run as SELECT *.

Delete queries are also supported. For example, query methods such as deleteByAction or removeByAction delete entities found by findByAction. Delete queries are run as separate read and delete operations instead of as a single transaction because Cloud Datastore cannot query in transactions unless ancestors for queries are specified. As a result, removeBy and deleteBy name-convention query methods cannot be used inside transactions via either performInTransaction or @Transactional annotation.

Delete queries can have the following return types:

Methods can have org.springframework.data.domain.Pageable parameter to control pagination and sorting, or org.springframework.data.domain.Sort parameter to control sorting only. See Spring Data documentation for details.

For returning multiple items in a repository method, we support Java collections as well as org.springframework.data.domain.Page and org.springframework.data.domain.Slice. If a method’s return type is org.springframework.data.domain.Page, the returned object will include current page, total number of results and total number of pages.

Java java.util.Optional can be used to indicate the potential absence of a return value.

Alternatively, query methods can return the result without a wrapper. In that case the absence of a query result is indicated by returning null. Repository methods returning collections are guaranteed never to return null but rather the corresponding empty collection.

Query by Example is an alternative querying technique. It enables dynamic query generation based on a user-provided object. See Spring Data Documentation for details.

Custom GQL queries can be mapped to repository methods in one of two ways:

These transactions work very similarly to those of DatastoreOperations, but is specific to the repository’s domain type and provides repository functions instead of template functions.

For example, this is a read-write transaction:

Spring Data Cloud Datastore supports projections. You can define projection interfaces based on domain types and add query methods that return them in your repository:

Projections can be provided by name-convention-based query methods as well as by custom GQL queries. If using custom GQL queries, you can further restrict the fields retrieved from Cloud Datastore to just those required by the projection. However, custom select statements (those not using SELECT *) require composite indexes containing the selected fields.

Properties of projection types defined using SpEL use the fixed name target for the underlying domain object. As a result, accessing underlying properties take the form target.<property-name>.

When running with Spring Boot, repositories can be exposed as REST services by simply adding this dependency to your pom file:

If you prefer to configure parameters (such as path), you can use @RepositoryRestResource annotation:

For example, you can retrieve all Trade objects in the repository by using curl http://<server>:<port>/trades, or any specific trade via curl http://<server>:<port>/trades/<trader_id>.

You can also write trades using curl -XPOST -H"Content-Type: application/json" -d@test.json http://<server>:<port>/trades/ where the file test.json holds the JSON representation of a Trade object.

To delete trades, you can use curl -XDELETE http://<server>:<port>/trades/<trader_id>

If you are using Spring Boot Actuator, you can take advantage of the Cloud Datastore health indicator called datastore. The health indicator will verify whether Cloud Datastore is up and accessible by your application. To enable it, all you need to do is add the Spring Boot Actuator to your project.