Chapter 20. Programming model

This chapter covers the fundamentals of the programming model behind Spring Data Neo4j. It discusses the simple and advanced mapping modes, the annotations provided by Spring Data Neo4j and how to use them. Examples for this section are taken from the "IMDB" project of Spring Data Neo4j examples.

20.1. Object Graph Mapping

Up until recently Spring Data Neo4j supported only the more advanced and flexible AspectJ based mapping approach, see Section 20.2, “Advanced Mapping with AspectJ”. Feedback about issues with the AspectJ tooling and other implications persuaded us to add a simpler mapping (see Section 20.3, “Simple Object Graph Mapping”) to Spring Data Neo4j. Both versions work with the same annotations and provide similar API's, but differ in behaviour.

Reflection and Annotation-based metadata is collected about persistent entities in the Neo4jMappingContext which provides it to any part of the library. The information is stored in Neo4jPersistentEntity instances which hold all the Neo4jPersistentProperty's of the type. Each entity can be checked to determine whether it represents a Node or a Relationship. Properties declare detailed data about their indexing and relationship information as well as type information that also covers nested generic types. With all that information available it is simple to select the appropriate strategy for mapping each entity and field to elements, relationships and properties of the graph.

The main difference is in the way of accessing the graph. In the simple mapping the required information is copied into the entity on load and only stored back when an explicit save operation occurs. In the advanced mapping (AspectJ-enhanced) approach a node or relationship is attached via an additional field to the entity and all read- and write-operations (inside of Transactions) happen through that.

For the simple mapping mode, declaration of fetch strategies for related entities is necessary to avoid loading the whole graph eagerly into memory. The initial approach uses just a simple @Fetch annotations on relationship properties. The resulting MappingPolicy is provided to the infrastructure methods to ensure the correct loading behaviour. Both, Neo4jPersistentEntiy and Neo4jPersistentProperty can be queried for the MappingPolicy.

Otherwise the two approaches share much of the infrastructure. E.g. for creating new entity instances from type information store in the graph (Section 20.14, “Entity type representation”), the infrastructure for mapping individual fields to graph properties and relationships and everything related to indexing and querying. A certain part of that is also exposed via the Neo4jTemplate for direct use.

20.2. Advanced Mapping with AspectJ

Behind the scenes, Spring Data Neo4j leverages AspectJ aspects to modify the behavior of annotated POJO entities (see Chapter 26, AspectJ details). Each node entity is backed by a graph node that holds its properties and relationships to other entities. AspectJ is used for intercepting field access, so that Spring Data Neo4j can retrieve the appropriate information from the entity's backing node or relationship.

The aspect introduces a internal field (entityState)and some public methods (see Section 20.11, “Active Record Methods for Advanced Mapping Mode”) to the entities, for instance as entity.getPersistentState() and entity.relateTo. It also introduces some methods for graph operations that start at the current entity. Introduced methods for equals() and hashCode() use the underlying node or relationship. Please take the introduced field into account when serializing your entities and exclude it from the serialization process.

Spring Data Neo4j internally uses an abstraction called EntityState that the field access and instantiation advices of the aspect delegate to. This way, the aspect code is kept to a minimum, focusing mainly on the pointcuts and delegation. The EntityState then uses a number of FieldAccessorFactories to create a FieldAccessor instance per field that does the specific handling needed for the concrete field type. There is some caching involved as well, so it handles repeated instantiation efficiently.

To use the advanced, AspectJ based mapping, please add spring-data-neo4j-aspects as a dependency and set up the AspectJ integration in Maven or other build tools as explained in Chapter 21, Environment setup. Some hints for your IDE setup are described below.

20.2.1. AspectJ IDE support

As Spring Data Neo4j uses some advanced features of AspectJ, users may experience issues with their IDE reporting errors where in fact there are none. Features that might be reported wrongfully include: introduction of methods to interfaces, declaration of additional interfaces for annotated classes, and generified introduced methods.

IDE's not providing the full AJ support might mark parts of your code as errors. You should rely on your build-system and tests to verify the correctness of the code. You might also have your Entities (or their interfaces) implement the NodeBacked and RelationshipBacked interfaces directly to benefit from completion support and error checking.

Eclipse and STS support AspectJ via the AJDT plugin which can be installed from the update-site: http://download.eclipse.org/tools/ajdt/37/update/ (it might be necessary to use the latest development snapshot of the plugin http://download.eclipse.org/tools/ajdt/36/dev/update). The current version that does not show incorrect errors is AspectJ 1.6.12 (included in STS 2.8.0), previous versions are reported to mislead the user.

Note

There might be some issues with the eclipse maven plugin not adding AspectJ files correctly to the build path. If you encounter issues, please try the following: Try editing the build path to include **/*.aj for the spring-data-neo4j project. You can do this by selecting "Build Path -> Configure Build Path ..." from the Package Explorer. Then for the spring-data-neo4j/src/main/java add **/*.aj to the Included path. For importing an Spring Data Graph project into Eclipse with m2e. Please make sure that the AspectJ Configurator is installed and

The AspectJ support in IntelliJ IDEA lacks some of the features. JetBrains is working on improving the situation in their upcoming 11 release of their popular IDE. Their latest work is available under their early access program (EAP). Building the project with the AspectJ compiler ajc works in IDEA (Options -> Compiler -> Java Compiler should show ajc). Make sure to give the compiler at least 512 MB of RAM.

20.3. Simple Object Graph Mapping

In addition to the advanced object graph mapping using AspectJ, Spring Data Neo4j also supports a simpler mode that converts graph data into domain objects and vice versa. It does not require any additional set up and should work out of the box. The simple mapping approach uses the same annotations (???) as the advanced mapping to declare mapping meta-information.

The simple object graph mapping comes into play whenever an entity is constructed from a node or relationship. This could be done explicitly like during the lookup- or create-operations of the repositories and the Neo4jTemplate but also implicitly while executing any graph operation that returns nodes or relationships and expecting mapped entities to be returned.

It uses the available meta-information about the persistent entity to iterate over its properties and relationships, fetching their data from the graph while doing so. It also executes computed fields and stores the resulting values in the properties.

We try to avoid loading the whole graph into memory by not following relationships eagerly. A dedicated @Fetch annotation controls instead if related entities are loaded or not. Whenever an entity is not fully loaded, then only its id is stored. Those entities or collections of entities can then later be loaded explicitly using the template.fetch() operation.

The additional fetch information is stored in a MappingPolicy which can be retrieved via the Neo4jTemplate for classes. Both Neo4jPersistentEntitity as well as Neo4jPersistentProperty provide access to that information on their scope.

Note

Please note that if you have two collections in an entity pointing to the same relationship and one of them has data and the other is empty due to the nature of persisting it, one will override the other in the graph so that you might end up with no data. If you want a relationship-collection to be ignored on save set it to null.

Example 20.1. Examples for loading entities from the graph

  @Autowired Neo4jOperations template;


  @NodeEntity class Person {
    String name;
    @Fetch Person boss;
    Person spouse;

    @RelatedTo(type = "FRIEND", direction = BOTH)
    @Fetch Set<Person> friends;
  }
  Person person = template.findOne(personId);
  assertNotNull(person.getBoss().getName());

  assertNotNull(person.getSpouse().getId());
  assertNull(person.getSpouse().getName());

  template.fetch(person.getSpouse());
  assertNotNull(person.getSpouse().getName());

  assertEquals(10,person.getFriends().size());
  assertNotNull(firstFriend.getName());


Note

Both the simple mapping approach as well as the fetch strategies (MappingPolicy) debuted in Spring Data Neo4j 2.0. So there might be rough edges and there are certainly many areas for improvement and extension. We look forward to your feedback on this topic.

As we tried to encapsulate each aspect of the mapping process into a separate class the resulting fabric of responsibilities is quite intricate. All of them are set up in the MappingInfrastructure that is part of the Neo4jTemplate setup.

20.4. Defining node entities

Node entities are declared using the @NodeEntity annotation. Relationship entities use the @RelationshipEntity annotation.

20.4.1. @NodeEntity: The basic building block

The @NodeEntity annotation is used to turn a POJO class into an entity backed by a node in the graph database. Fields on the entity are by default mapped to properties of the node. Fields referencing other node entities (or collections thereof) are linked with relationships. If the useShortNames attribute is set to false, the property and relationship names will have the class name of the entity prepended.

@NodeEntity annotations are inherited from super-types and interfaces. It is not necessary to annotate your domain objects at every inheritance level.

If the partial attribute is set to true, this entity takes part in a cross-store setting, where the entity lives in both the graph database and a JPA data source. See Chapter 22, Cross-store persistence for more information.

Entity fields can be annotated with @GraphProperty, @RelatedTo, @RelatedToVia, @Indexed, @GraphId, @Query and @GraphTraversal.

Example 20.2. Simplest node entity

@NodeEntity
public class Movie {
    String title;
}

20.4.2. @GraphId: Neo4j -id field

For the simple mapping this is a required field which must be of type Long. It is used by Spring Data Neo4j to store the node or relationship-id to re-connect the entity to the graph.

Note

It must not be a primitive type because then the "non-attached" case can not be represented as the default value 0 would point to the reference node. Please make also sure that an equals() and hashCode() method have to be provided which take the id field into account (and also handle the "non-attached", null case).

For the advanced mapping such a field is optional. Only if the underlying id has to be accessed, it is needed.

20.4.3. @GraphProperty: Optional annotation for property fields

It is not necessary to annotate property fields, as they are persisted by default; all fields that contain primitive values are persisted directly to the graph. All fields convertible to a String using the Spring conversion services will be stored as a string. Spring Data Neo4j includes a custom conversion factory that comes with converters for Enums and Dates. Transient fields are not persisted.

Collections of collections of primitive or convertable values are stored as well. They are converted to arrays of their type or strings respectively.

This annotation is typically used with cross-store persistence. When a node entity is configured as partial, then all fields that should be persisted to the graph must be explicitly annotated with @GraphProperty.

20.4.4. @Indexed: Making entities searchable by field value

The @Indexed annotation can be declared on fields that are intended to be indexed by the Neo4j indexing facilities. The resulting index can be used to later retrieve nodes or relationships that contain a certain property value, e.g. a name. Often an index is used to establish the start node for a traversal. Indexes are accessed by a repository for a particular node or relationship entity type. See Section 20.6, “Indexing” and Section 20.8, “CRUD with repositories” for more information.

20.4.5. @Query: fields as query result views

The @Query annotation leverages the delegation infrastructure supported by Spring Data Neo4j. It provides dynamic fields which, when accessed, return the values selected by the provided query language expression. The provided query must contain a placeholder named {self} for the the current entity. For instance the query start n=node({self}) match n-[:FRIEND]->friend return friend. Graph queries can return variable number of entities. That's why annotation can be put onto fields with a single value, a subclass of Iterable of a concrete type or an Iterable of Map<String,Object>. Additional parameters are taken from the params attribute of the @Query annotation. These parameter tuples form key-value pairs that are provided to the query at execution time.

Example 20.3. @Graph on a node entity field

@NodeEntity
public class Group {
    @Query(value = "start n=({self}) match (n)-[r]->(friend) where r.type = {relType} return friend",
                params = {"relType", "FRIEND"})
    private Iterable<Person> friends;
}

Note

Please note that this annotation can also be used on repository methods. (Section 20.8, “CRUD with repositories”)

20.4.6. @GraphTraversal: fields as traversal result views

The @GraphTraversal annotation also leverages the delegation infrastructure supported by Spring Data aspects. It provides dynamic fields which, when accessed, return an Iterable of node or relationship entities that are the result of a traversal starting at the entity containing the field. The TraversalDescription used for this is created by the FieldTraversalDescriptionBuilder class defined by the traversal attribute. The class of the resulting node entities must be provided with the elementClass attribute.

Example 20.4. @GraphTraversal from a node entity

@NodeEntity
public class Group {
    @GraphTraversal(traversal = PeopleTraversalBuilder.class,
            elementClass = Person.class, params = "persons")
    private Iterable<Person> people;

    private static class PeopleTraversalBuilder implements FieldTraversalDescriptionBuilder {
        @Override
        public TraversalDescription build(NodeBacked start, Field field, String... params) {
            return new TraversalDescriptionImpl()
                    .relationships(DynamicRelationshipType.withName(params[0]))
                    .filter(Traversal.returnAllButStartNode());
        }
    }
}

20.5. Relating node entities

Since relationships are first-class citizens in Neo4j, associations between node entities are represented by relationships. In general, relationships are categorized by a type, and start and end nodes (which imply the direction of the relationship). Relationships can have an arbitrary number of properties. Spring Data Neo4j has special support to represent Neo4j relationships as entities too, but it is often not needed.

Note

As of Neo4j 1.4.M03, circular references are allowed. Spring Data Neo4j reflects this accordingly.

20.5.1. @RelatedTo: Connecting node entities

Every field of a node entity that references one or more other node entities is backed by relationships in the graph. These relationships are managed by Spring Data Neo4j automatically.

The simplest kind of relationship is a single field pointing to another node entity (1:1). In this case, the field does not have to be annotated at all, although the annotation may be used to control the direction and type of the relationship. When setting the field, a relationship is created when the entity is persisted. If the field is set to null, the relationship is removed.

Example 20.5. Single relationship field

@NodeEntity
public class Movie {
    private Actor topActor;
}

It is also possible to have fields that reference a set of node entities (1:N). These fields come in two forms, modifiable or read-only. Modifiable fields are of the type Set<T>, and read-only fields are Iterable<T>, where T is a @NodeEntity-annotated class.

Example 20.6. Node entity with relationships

@NodeEntity
public class Actor {
    @RelatedTo(type = "topActor", direction = Direction.INCOMING)
    private Set<Movie> topActorIn;

    @RelatedTo(type = "ACTS_IN")
    private Set<Movie> movies;
}

For the simple mapping, the automatic transitive loading of related entities depends on declaration of @Fetch at the property. Otherwise the related node or relationship entities will just be initialized with their id for later loading.

When using the advanced mapping, Fields referencing other entities should not be manually initialized, as they are managed by Spring Data Neo4j Aspects under the hood. 1:N fields can be accessed immediately, and Spring Data Neo4j will provide a Set representing the relationships.

If this Set of related entities is modified, the changes are reflected in the graph, relationships are added, removed or updated accordingly.

Note

Spring Data Neo4j ensures by default that there is only one relationship of a given type between any two given entities. This can be circumvented by using the createRelationshipBetween() method with the allowDuplicates parameter on repositories or entities.

Note

Before an entity has been persisted for the first time, it will not have its state managed by Spring Data Neo4j. For example, given the Actor class defined above, if actor.movies was accessed in a non-persisted entity, it would return null, whereas if it was accessed in a persisted entity, it would return an empty managed set.

When an Interface is used as target type for the Set and/or as elementClass it should be marked as @NodeEntity too.

By setting direction to BOTH, relationships are created in the outgoing direction, but when the 1:N field is read, it will include relationships in both directions. A cardinality of M:N is not necessary because relationships can be navigated in both directions.

In the advanced mapping mode, the relationships can also be accessed by using the methods entity.getRelationshipBetween(target, type) and entity.relateTo(target, type) available on each NodeEntity. These methods find and create Neo4j relationships. It is also possible to manually remove relationships by using entity.removeRelationshipTo(target, type). Using these methods is significantly faster than adding/removing from the collection of relationships as it doesn't have to re-synchronize a whole set of relationships with the graph.

Methods of the same semantics exist in the repositories to be used in the simple mapping mode.

Note

Other collection types than Set are not supported so far, also currently NO Map<RelationshipType,Set<NodeBacked>>.

20.5.2. @RelationshipEntity: Rich relationships

To access the full data model of graph relationships, POJOs can also be annotated with @RelationshipEntity, making them relationship entities. Just as node entities represent nodes in the graph, relationship entities represent relationships. As described above, fields annotated with @RelatedTo provide a way to link node entities together via relationships, but it provides no way of accessing the relationships themselves.

Relationship entities can be accessed via by @RelatedToVia-annotated (Section 20.5.3, “@RelatedToVia: Accessing relationship entities”) fields or methods like entity.getRelationshipTo() or template|repository.getRelationshipsBetween().

Relationship entities either be instantiated directly and added to Set's of @RelatedToVia fields or created by the introduced entity.relateTo(), template|repository.createRelationshipBetween() methods (see Section 20.11, “Active Record Methods for Advanced Mapping Mode”)

Fields in relationship entities are, similarly to node entities, persisted as properties on the relationship. For accessing the two endpoints of the relationship, two special annotations are available: @StartNode and @EndNode. A field annotated with one of these annotations will provide read-only access to the corresponding endpoint, depending on the chosen annotation.

For the relationship-type a String or RelationshipType field annotated with @RelationshipType is available. When Relationship-Entities are instantiated directly, the relationship type has to be provided either in this annotated field or as part of the @RelationshipEntity annotation.

Example 20.7. Relationship entity (in advanced mapping)

@NodeEntity
public class Actor {
    public Role playedIn(Movie movie, String title) {
        return relateTo(movie, Role.class, "ACTS_IN");
    }
}

@RelationshipEntity
public class Role {
    String title;

    @StartNode private Actor actor;
    @EndNode private Movie movie;
}
        

20.5.3. @RelatedToVia: Accessing relationship entities

To provide easy programmatic access to the richer relationship entities of the data model, the annotation @RelatedToVia can be added on fields of type Iterable<T> or Set<T>, where T is a @RelationshipEntity-annotated class. These fields provide access to relationship entities.

Example 20.8. Relationship entity (in simple mapping)

@NodeEntity
public class Actor {
    @Set<Role> roles=new HashSet<Role>();
    public Role playedIn(Movie movie, String title) {
        Role role=new Role(this,movie,title);
        roles.add(role);
        return role;
    }
}

@RelationshipEntity(type = "ACTS_IN")
public class Role {
    String title;

    @StartNode private Actor actor;
    @EndNode private Movie movie;
}
        

20.6. Indexing

Indexing is used in Neo4j to quickly find nodes and relationships to start graph operations from. Either for manually traversing the graph, using the traversal framework, cypher or gremlin queries or for "global" graph operations. Indexes are also employed to ensure uniqueness of elements with certain properties.

The Neo4j graph database employs different index providers for exact lookups and fulltext searches. Lucene is the default index provider implementation. Each named index is configured to be fulltext or exact. There is also a spatial index provider for geo-searches.

20.6.1. Exact and numeric index

When using the standard Neo4j API, nodes and relationships have to be manually indexed with key-value pairs, typically being the property name and value. When using Spring Data Neo4j, this task is simplified to just adding an @Indexed annotation on entity fields by which the entity should be searchable. This will result in automatic updates of the index every time an indexed field changes.

Numerical fields are indexed numerically so that they are available for range queries. All other fields are indexed with their string representation.

The @Indexed annotation also provides the option of using a custom index name. The default index name is the simple class name of the entity, so that each class typically gets its own index. It is recommended to not have two entity classes with the same class name, regardless of package.

If a field is declared in a superclass but different indexes for subclasses are needed, the level attribute declares what will be used as index. Level.CLASS uses the class where the field was declared and Level.INSTANCE uses the class that is provided or of the actual entity instance.

The indexes can be queried by using a repository (see Section 20.8, “CRUD with repositories”). The repository is an instance of org.springframework.data.neo4j.repository.IndexRepository. The methods findByPropertyValue() and findAllByPropertyValue() work on the exact indexes and return the first or all matches. To do range queries, use findAllByRange() (please note that currently both values are inclusive).

For providing explicit index names the repository has to extend NamedIndexRepository. This adds the shown methods with another signature that take the index name as first parameter.

Example 20.9. Indexing entities

@NodeEntity
class Person {
    @Indexed(indexName = "people") String name;
    @Indexed int age;
}

GraphRepository<Person> graphRepository = template.repositoryFor(Person.class);

// Exact match, in named index
Person mark = graphRepository.findByPropertyValue("people", "name", "mark");

// Numeric range query, index name inferred automatically
for (Person middleAgedDeveloper : graphRepository.findAllByRange("age", 20, 40)) {
    Developer developer=middleAgedDeveloper.projectTo(Developer.class);
}

20.6.2. Fulltext indexes

Spring Data Neo4j also supports fulltext indexes. By default, indexed fields are stored in an exact lookup index. To have them analyzed and prepared for fulltext search, the @Indexed annotation has the type attribute which can be set to IndexType.FULLTEXT. Please note that fulltext indexes require a separate index name as the fulltext configuration is stored in the index itself.

Access to the fulltext index is provided by the findAllByQuery() repository method. Wildcards like * are allowed. Generally though, the fulltext querying rules of the underlying index provider apply. See the Lucene documentation for more information on this.

Example 20.10. Fulltext indexing

@NodeEntity
class Person {
    @Indexed(indexName = "people-search", type=FULLTEXT) String name;
}

GraphRepository<Person> graphRepository =
             template.repositoryFor(Person.class);

Person mark = graphRepository.findAllByQuery("people-search", "name", "ma*");


Note

Please note that indexes are currently created on demand, so whenever an index that doesn't exist is requested from a query or get operation it is created. This is subject to change but has currently the implication that those indexes won't be configured as fulltext which causes subsequent fulltext updates to those indexes to fail.

20.6.3. Manual index access

The index for a domain class is also available from Neo4jTemplate via the getIndex() method. The second parameter is optional and takes the index name if it should not be inferred from the class name. It returns the index implementation that is provided by Neo4j.

Example 20.11. Manual index retrieval by type and name

@Autowired Neo4jTemplate template;

// Default index
Index<Node> personIndex = template.getIndex(null, Person.class);
personIndex.query(new QueryContext(NumericRangeQuery.newÍntRange("age", 20, 40, true, true))
                       .sort(new Sort(new SortField("age", SortField.INT, false))));

// Named index
Index<Node> namedPersonIndex = template.getIndex("people",Person.class);
namedPersonIndex.get("name", "Mark");

// Fulltext index
Index<Node> personFulltextIndex = template.getIndex("people-search", Person.class);
personFulltextIndex.query("name", "*cha*");
personFulltextIndex.query("{name:*cha*}");

It is also possible to pass in the property name of the entity with an @Indexed annotation whose index should be returned.

Example 20.12. Manual index retrieval by property configuration

@Autowired Neo4jTemplate template;

Index<Node> personIndex = template.getIndex(Person.class, "age");
personIndex.query(new QueryContext(NumericRangeQuery.newÍntRange("age", 20, 40, true, true))
                       .sort(new Sort(new SortField("age", SortField.INT, false))));

// Fulltext index
Index<Node> personFulltextIndex = template.getIndex(Person.class,"name");
personFulltextIndex.query("name", "*cha*");
personFulltextIndex.query("{name:*cha*}");

20.6.4. Index queries in Neo4jTemplate

For querying the index, the template offers query methods that take either the exact match parameters or a query object/expression, return the results as Result objects which then can be converted and projected further using the result-conversion-dsl (see Section 20.7, “Neo4jTemplate”).

20.6.5. Neo4j Auto Indexes

Neo4j allows to configure auto-indexing for certain properties on nodes and relationships. This auto-indexing differs from the approach used in Spring Data Neo4j because it only updates the indexes when the transaction is committed. So the index modifications will only be available after the successful commit. It is possible to use the specific index names node_auto_index and relationship_auto_index when querying indexes in Spring Data Neo4j either with the query methods in template and repositories or via Cypher and Gremlin.

20.6.6. Spatial Indexes

Spring Data Neo4j offers limited support for spatial queries using the neo4j-spatial library. See the separate chapter Section 20.10, “Geospatial Queries” for details.

20.7. Neo4jTemplate

The Neo4jTemplate offers the convenient API of Spring templates for the Neo4j graph database. The Spring Data Neo4j Object Graph mapping builds upon the core functionality of the template to persist objects to the graph and load them in a variety of ways. The template handles the active mapping mode (Section 20.1, “Object Graph Mapping”) transparently.

Besides methods for creating, storing and deleting entities, nodes and relationships in the graph, Neo4jTemplate also offers a wide range of query methods. To reduce the proliferation of query methods a simple result handling DSL was added.

20.7.1. Basic operations

For direct retrieval of nodes and relationships, the getReferenceNode(), getNode() and getRelationship() methods can be used.

There are methods (createNode() and createRelationship()) for creating nodes and relationships that automatically set provided properties.

Example 20.13. Neo4j template

        // TODO auto-post-construct !!
        final Neo4jTemplate neo = new Neo4jTemplate(graphDatabase);
        neo.postConstruct();

        Node mark = neo.createNode(map("name", "Mark"));
        Node thomas = neo.createNode(map("name", "Thomas"));

        neo.createRelationshipBetween(mark, thomas, "WORKS_WITH", map("project", "spring-data"));

        neo.index("devs", thomas, "name", "Thomas");
        // Cypher TODO
        assertEquals( "Mark", neo.query("start p=node({person}) match p<-[:WORKS_WITH]-other return other.name",
                                  map("person", asList(thomas.getId()))).to(String.class).single());



        // Gremlin
        assertEquals(thomas, neo.execute("g.v(person).out('WORKS_WITH')",
                map("person", mark.getId())).to(Node.class).single());

        // Index lookup
        assertEquals(thomas, neo.lookup("devs", "name", "Thomas").to(Node.class).single());

        // Index lookup with Result Converter
        assertEquals("Thomas", neo.lookup("devs", "name", "Thomas").to(String.class, new ResultConverter.ResultConverterAdapter<PropertyContainer, String>() {
            public String convert(PropertyContainer element, Class<String> type) {
                return (String) element.getProperty("name");
            }
        }).single());

20.7.2. Result

All querying methods of the template return a uniform result type: Result<T> which is also an Iterable<T>. The query result offers methods of converting each element to a target type result.to(Type.class) optionally supplying a ResultConverter<FROM,TO> which takes care of custom conversions. By default most query methods can already handle conversions from and to: Paths, Nodes, Relationship and GraphEntities as well as conversions backed by registered ConversionServices. A converted Result<FROM> is an Iterable<TO>. Results can be limited to a single value using the result.single() or result.singleOrNull() methods. It also offers support for a pure callback function using a Handler<T>.

20.7.3. Indexing

Adding nodes and relationships to an index is done with the index() method.

The lookup() methods either take a field/value combination to look for exact matches in the index, or a Lucene query object or string to handle more complex queries. All lookup() methods return a Result<PropertyContainer> to be used or transformed.

20.7.4. Graph traversal

The traversal methods are at the core of graph operations. The traverse() method covers the full traversal operation that takes a TraversalDescription (typically built with the template.getGraphDatabase().traversalDescription() DSL) and runs it from the given start node. traverse returns a Result<Path> to be used or transformed.

20.7.5. Cypher Queries

The Neo4jTemplate also allows execution of arbitrary Cypher queries. Via the query methods the statement and parameter-Map are provided. Cypher Queries return tabular results, so the Result<Map<String,Object>> contains the rows which can be either used as they are or converted as needed.

20.7.6. Gremlin Scripts

Gremlin Scripts can run with the execute method, which also takes the parameters that will be available as variables inside the script. The result of the executions is a generic Result<Object> fit for conversion or usage.

20.7.7. Transactions

The Neo4jTemplate provides implicit transactions for some of its methods. For instance save uses them. For other modifying operations please provide Spring Transaction management using @Transactional or the TransactionTemplate.

20.7.8. Neo4j REST Server

If the template is configured to use a SpringRestGraphDatabase the operations that would be expensive over the wire, like traversals and querying are executed efficiently on the server side by using the REST API to forward those calls. All the other template methods require individual network operations.

The REST-batch-mode of the SpringRestGraphDatabase is not yet exposed via the template, but it is available via the graph database.

20.8. CRUD with repositories

The repositories provided by Spring Data Neo4j build on the composable repository infrastructure in Spring Data Commons. They allow for interface based composition of repositories consisting of provided default implementations for certain interfaces and additional custom implementations for other methods.

Spring Data Neo4j repositories support annotated and named queries for the Neo4j Cypher query-language and Gremlin graph DSL.

Spring Data Neo4j comes with typed repository implementations that provide methods for locating node and relationship entities. There are several types of basic repository interfaces and implementations. CRUDRepository provides basic operations, IndexRepository and NamedIndexRepository delegate to Neo4j's internal indexing subsystem for queries, and TraversalRepository handles Neo4j traversals.

With the RelationshipOperationsRepository it is possible to access, create and delete relationships between entitites or nodes. The SpatialRepository allows geographic searches (Section 20.10, “Geospatial Queries”)

GraphRepository is a convenience repository interface, combining CRUDRepository, IndexRepository, and TraversalRepository. Generally, it has all the desired repository methods. If other operations are required then the additional repository interfaces should be added to the individual interface declaration.

20.8.1. CRUDRepository

CRUDRepository delegates to the configured TypeRepresentationStrategy (see Section 20.14, “Entity type representation”) for type based queries.

Load an entity instance via an id

T findOne(id)

Check for existence of a id in the graph

boolean exists(id)

Iterate over all entities instances of the repository entity type

Iterable<T> findAll() Iterable<T> findAll(Sort) Page<T> findAll(Pageable)

Count the instances of the repository entity type

Long count()

Save entities

T save(T) and Iterable<T> save(Iterable<T>)

Delete graph entities

void delete(T), void; delete(Iterable<T>), and deleteAll()

20.8.2. IndexRepository and NamedIndexRepository

IndexRepository works with the indexing subsystem and provides methods to find entities by indexed properties, ranged queries, and combinations thereof. The index key is the name of the indexed entity field, unless overridden in the @Indexed annotation.

Iterate over all indexed entity instances with a certain field value

Iterable<T> findAllByPropertyValue(key, value)

Get a single entity instance with a certain field value

T findByPropertyValue(key, value)

Iterate over all indexed entity instances with field values in a certain numerical range (inclusive)

Iterable<T> findAllByRange(key, from, to)

Iterate over all indexed entity instances with field values matching the given fulltext string or QueryContext query

Iterable<T> findAllByQuery(key, queryOrQueryContext)

There is also a NamedIndexRepository with the same methods, but with an additional index name parameter, making it possible to query any index.

20.8.3. TraversalRepository

TraversalRepository delegates to the Neo4j traversal framework.

Iterate over a traversal result

Iterable<T> findAllByTraversal(startEntity, traversalDescription)

20.8.4. Query and Finder Methods

20.8.4.1. Annotated queries

Queries using the Cypher graph query language can be supplied with the @Query annotation. That means every method annotated with @Query("start n=node:IndexName(key={node or 0}) match (n)-->(m) return m") will use the supplied query string. The named or indexed parameter {node} will be substituted by the actual method parameter. Node and Relationship-Entities are handled directly, Iterables thereof as well. All other parameters are replaced directly (i.e. Strings, Longs, etc). There is special support for the Sort and Pageable parameters from Spring Data Commons, which are supported to add programmatic paging and sorting (alternatively static paging and sorting can be supplied in the query string itself). For using the named parameters you have to either annotate the parameters of the method with the @Param("node") annotation or enable debug symbols. Indexed parameters are always usable.

Gremlin queries can be used similarly, the @Query annotation would just need a type=QueryType.GREMLIN attribute. Parameters are supported in the same way.

20.8.4.2. Named queries

Spring Data Neo4j also supports the notion of named queries which are externalized in property-config-files (META-INF/neo4j-named-queries.properties). Those files have the format: Entity.finderName=query (e.g. Person.findBoss=start p=node({0}) match (p)<-[:BOSS]-(boss) return boss). Otherwise named queries support the same parameters as annotated queries.

20.8.4.3. Query results

Typical results for queries are Iterable<Type>, Iterable<Map<String,Object>>, Type and Page<Type>. Nodes and Relationships are converted to their respective Entities (if they exist). Other values are converted using the registered Spring conversion services (e.g. enums).

20.8.4.4. Cypher examples

There is a screencast available showing many features of the query language. The following examples are taken from the cineasts dataset of the tutorial section.

start n=node(0) return n

returns the node with id 0

start movie=node:Movie(title='Matrix') return movie

returns the nodes which are indexed with title equal to 'Matrix'

start movie=node:Movie(title='Matrix') match (movie)<-[:ACTS_IN]-(actor) return actor.name

returns the names of the actors that have a ACTS_IN relationship to the movie node for 'Matrix'

start movie=node:Movie(title='Matrix') match (movie)<-[r:RATED]-(user) where r.stars > 3 return user.name, r.stars, r.comment

returns users names and their ratings (>3) of the movie titled 'Matrix'

start user=node:User(login='micha') match (user)-[:FRIEND]-(friend)-[r:RATED]->(movie) return movie.title, AVG(r.stars), COUNT(*) order by AVG(r.stars) desc, COUNT(*) desc

returns the movies rate by the friends of the user 'micha', aggregated by movie.title, with averaged ratings and rating-counts sorted by both

20.8.4.5. Queries derived from finder-method names

As known from Rails or Grails it is possible to derive queries for domain entities from finder method names like Iterable<Person> findByNameAndAgeGreaterThan(String name, int age). Using the infrastructure in Spring Data Commons that allows to collect the meta information about entities and their properties a finder method name can be split into its semantic parts and converted into a cypher query. @Indexed fields will be converted into index-lookups of the start clause, navigation along relationships will be reflected in the match clause properties with operators will end up as expressions in the where clause. Order and limiting of the query will by handled by provided Pageable or Sort parameters. The other parameters will be used in the order they appear in the method signature so that should align with the expressions stated in the method name.

Example 20.14. Some examples of methods and resulting cypher queries of a PersonRepository

public interface PersonRepository 
               extends GraphRepository<Person> {

// start person=node:Person(id={0}) return person
Person findById(String id)

// start person=node:Person({0}) return person - {0} will be "id:"+name
Iterable<Person> findByNameLike(String name)

// start person=node:__types__("className"="com...Person") 
// where person.age = {0} and person.married = {1}
// return person
Iterable<Person> findByAgeAndMarried(int age, boolean married)

// start person=node:__types__("className"="com...Person")
// match person<-[:CHILD]-parent
// where parent.age > {0} and person.married = {1}
// return person
Iterable<Person> findByParentAgeAndMarried(int age, boolean married)
}


20.8.4.6. Derived Finder Methods

Use the meta information of your domain model classes to declare repository finders that navigate along relationships and compare properties. The path defined with the method name is used to create a Cypher query that is executed on the graph.

Example 20.15. Repository and usage of derived finder methods

    @NodeEntity
    public static class Person {
        @GraphId Long id;
        private String name;
        private Group group;

        private Person(){}
        public Person(String name) {
            this.name = name;
        }
    }
    @NodeEntity
    public static class Group {
        @GraphId Long id;
        private String title;
        // incoming relationship for the person -> group
        @RelatedTo(type = "group", direction = Direction.INCOMING)
        private Set<Person> members=new HashSet<Person>();

        private Group(){}
        public Group(String title, Person...people) {
            this.title = title;
            members.addAll(asList(people));
        }
    }
    public interface PersonRepository extends GraphRepository<Person> {
        Iterable<Person> findByGroupTitle(String name);
    }

    @Autowired PersonRepository personRepository;

        Person oliver=personRepository.save(new Person("Oliver"));
        final Group springData = new Group("spring-data",oliver);
        groupRepository.save(springData);

        final Iterable<Person> members = personRepository.findByGroupTitle("spring-data");
        assertThat(members.iterator().next().name, is(oliver.name));

20.8.5. CypherDSL repository

Spring Data Neo4j supports the new cypher-dsl to write Cypher queries in a statically typed way. Just by including CypherDslRepository to your repository you get the Page<T> query(Execute query, params, Pageable page) and the EndResult<T> query(Execute query, params);. The result type of the Cypher-DSL builder is called Execute

Example 20.16. Examples for Cypher-DSL repository

	public interface PersonRepository extends GraphRepository<Person>,
	  CypherDslRepository<Person> {}

	@Autowired PersonRepository repo;
	// START company=node:Company(name={name}) MATCH company<-[:WORKS_AT]->person RETURN person

	Execute query = start( lookup( "company", "Company", "name", param("name") ) ).
	                          match( path().from( "company" ).in( "WORKS_AT" ).to( "person" )).
	                          returns( nodes( "person" ))
	Page<Person> people = repo.query(query , map("name","Neo4j"), new PageRequest(1,10));

	QPerson person = QPerson.person;
	QCompany company = QCompany.company;
	Execute query = start( lookup( company, "Company", company.name, param("name") ) ).
	                          match( path().from( company ).in( "WORKS_AT" ).to( person ).
	                          .where(person.firstName.like("P*").and(person.age.gt(25))).
	                          returns( nodes( person ))
	EndResult<Person> people = repo.query(query , map("name","Neo4j"));

	

20.8.6. Creating repositories

The Repository instances should normally be injected but can also be created manually via the Neo4jTemplate.

Example 20.17. Using basic GraphRepository methods

public interface PersonRepository extends GraphRepository<Person> {}

@Autowired PersonRepository repo;
// OR
GraphRepository<Person> repo = template
                           .repositoryFor(Person.class);

Person michael = repo.save(new Person("Michael", 36));

Person dave = repo.findOne(123);

Long numberOfPeople = repo.count();

Person mark = repo.findByPropertyValue("name", "mark");

Iterable<Person> devs = repo.findAllByProperyValue("occupation", "developer");

Iterable<Person> middleAgedPeople = repo.findAllByRange("age", 20, 40);

Iterable<Person> aTeam = repo.findAllByQuery("name", "A*");

Iterable<Person> davesFriends = repo.findAllByTraversal(dave,
    Traversal.description().pruneAfterDepth(1)
    .relationships(KNOWS).filter(returnAllButStartNode()));

20.8.7. Composing repositories

The recommended way of providing repositories is to define a repository interface per domain class. The mechanisms provided by the repository infrastructure will automatically detect them, along with additional implementation classes, and create an injectable repository implementation to be used in services or other spring beans.

Example 20.18. Composing repositories

public interface PersonRepository extends GraphRepository<Person>, PersonRepositoryExtension {}

// configure the repositories, preferably via the neo4j:repositories namespace
// (template reference is optional)
<neo4j:repositories base-package="org.example.repository"
    graph-database-context-ref="template"/>

// have it injected
@Autowired
PersonRepository personRepository;
// or created via the template
PersonRepository personRepository = template.repositoryFor(Person.class);


Person michael = personRepository.save(new Person("Michael",36));

Person dave=personRepository.findOne(123);

Iterable<Person> devs = personRepository.findAllByPropertyValue("occupation","developer");

Iterable<Person> aTeam = graphRepository.findAllByQuery( "name","A*");

Iterable<Person> friends = personRepository.findFriends(dave);


// alternatively select some of the required repositories individually
public interface PersonRepository extends CRUDGraphRepository<Node,Person>,
        IndexQueryExecutor<Node,Person>, TraversalQueryExecutor<Node,Person>,
        PersonRepositoryExtension {}

// provide a custom extension if needed
public interface PersonRepositoryExtension {
    Iterable<Person> findFriends(Person person);
}

public class PersonRepositoryImpl implements PersonRepositoryExtension {
    // optionally inject default repository, or use DirectGraphRepositoryFactory
    @Autowired PersonRepository baseRepository;
    public Iterable<Person> findFriends(Person person) {
        return baseRepository.findAllByTraversal(person, friendsTraversal);
    }
}

Note

If you use <context:component-scan> in your spring config, please make sure to put it behind <neo4j:repositories>, as the RepositoryFactoryBean adds new bean definitions for all the declared repositories, the context scan doesn't pick them up otherwise.

20.9. Projecting entities

As the underlying data model of a graph database doesn't imply and enforce strict type constraints like a relational model does, it offers much more flexibility on how to model your domain classes and which of those to use in different contexts.

For instance an order can be used in these contexts: customer, procurement, logistics, billing, fulfillment and many more. Each of those contexts requires its distinct set of attributes and operations. As Java doesn't support mixins one would put the sum of all of those into the entity class and thereby making it very big, brittle and hard to understand. Being able to take a basic order and project it to a different (not related in the inheritance hierarchy or even an interface) order type that is valid in the current context and only offers the attributes and methods needed here would be very beneficial.

Spring Data Neo4j offers initial support for projecting node and relationship entities to different target types. All instances of this projected entity share the same backing node or relationship, so changes are reflected on the same data.

This could for instance also be used to handle nodes of a traversal with a unified (simpler) type (e.g. for reporting or auditing) and only project them to a concrete, more functional target type when the business logic requires it.

Example 20.19. Projection of entities

@NodeEntity
class Trainee {
    String name;
    @RelatedTo
    Set<Training> trainings;
}

for (Person person : graphRepository.findAllByPropertyValue("occupation","developer")) {
    Developer developer = person.projectTo(Developer.class);
    if (developer.isJavaDeveloper()) {
        trainInSpringData(developer.projectTo(Trainee.class));
    }
}

20.10. Geospatial Queries

SpatialRepository is a dedicated Repository for spatial queries. Spring Data Neo4j provides an optional dependency to neo4j-spatial which is an advanced library for GIS operations. So if you include the maven dependency in your pom.xml, Neo4j-Spatial and the required SPATIAL index provider is available.

Example 20.20. Neo4j-Spatial Dependencies

<dependency>
    <groupId>org.neo4j</groupId>
    <artifactId>neo4j-spatial</artifactId>
    <version>0.7-SNAPSHOT</version>
</dependency>


To have your entities available for spatial index queries, please include a String property containing a "well known text", location string. WKT is the Well Known Text Spatial Format eg. POINT( LON LAT ) or POLYGON (( LON1 LAT1 LON2 LAT2 LON3 LAT3 LON1 LAT1 ))

Example 20.21. Fields of Well Known Text

@NodeEntity
class Venue {
   String name;
   @Indexed(type = POINT, indexName = "VenueLocation") String wkt;
   public void setLocation(float lon, float lat) {
      this.wkt = String.format("POINT( %.2f %.2f )",lon,lat);
   }
}

venue.setLocation(56,15);


After adding the SpatialRepository to your repository you can use the findWithinBoundingBox, findWithinDistance, findWithinWellKnownText.

Example 20.22. Spatial Queries

    Iterable<Person> teamMembers = personRepository.findWithinBoundingBox("personLayer", 55, 15, 57, 17);
Iterable<Person> teamMembers = personRepository.findWithinWellKnownText("personLayer", "POLYGON ((15 55, 15 57, 17 57, 17 55, 15 55))");
Iterable<Person> teamMembers = personRepository.findWithinDistance("personLayer", 16,56,70);


Example 20.23. Methods of the Spatial Repository

public interface SpatialRepository<T> {
    ClosableIterable<T> findWithinBoundingBox(String indexName, double lowerLeftLat,
                                              double lowerLeftLon,
                                              double upperRightLat,
                                              double upperRightLon);

    ClosableIterable<T> findWithinDistance( final String indexName, final double lat, double lon, double distanceKm);

    ClosableIterable<T> findWithinWellKnownText( final String indexName, String wellKnownText);
}


20.11. Active Record Methods for Advanced Mapping Mode

This chapter only applies to the advanced mapping. Currently the Aspects introduce the following methods by default, this will change in the future, there will be separate Mixin-Interfaces that can selectively mixed into the domain entities if needed. Otherwise the AspectJ interaction will be restricted to field access interception and post constructor handling.

The node and relationship aspects introduce (via AspectJ ITD - inter type declaration) several methods to the entities.

Persisting the node entity after creation and after changes outside of a transaction. Participates in an open transaction, or creates its own implicit transaction otherwise.

nodeEntity.persist()

Accessing node and relationship IDs

nodeEntity.getNodeId() and relationshipEntity.getRelationshipId()

Accessing the node or relationship backing the entity

entity.getPersistentState()

equals() and hashCode() are delegated to the underlying state

entity.equals() and entity.hashCode()

Creating relationships to a target node entity, and returning the relationship entity instance

nodeEntity.relateTo(targetEntity, relationshipClass, relationshipType)

Retrieving a single relationship entity

nodeEntity.getRelationshipTo(targetEntity, relationshipClass, relationshipType)

Creating relationships to a target node entity and returning the relationship

nodeEntity.relateTo(targetEntity, relationshipType)

Retrieving a single relationship

nodeEntity.getRelationshipTo(targetEnttiy, relationshipType)

Removing a single relationship

nodeEntity.removeRelationshipTo(targetEntity, relationshipType)

Remove the node entity, its relationships, and all index entries for it

nodeEntity.remove() and relationshipEntity.remove()

Project entity to a different target type, using the same backing state

entity.projectTo(targetClass)

Traverse, starting from the current node. Returns end nodes of traversal converted to the provided type.

nodeEntity.findAllByTraversal(targetType, traversalDescription)

Traverse, starting from the current node. Returns EntityPaths of the traversal result bound to the provided start and end-node-entity types

Iterable<EntityPath> findAllPathsByTraversal(traversalDescription)

Executes the given Cypher query, providing the {self} variable with the node-id and returning the results converted to the target type.

<T> Iterable<T> NodeBacked.findAllByQuery(final String query, final Class<T> targetType)

Executes the given query, providing {self} variable with the node-id and returning the original result, but with nodes and relationships replaced by their appropriate entities.

Iterable<Map<String,Object>> NodeBacked.findAllByQuery(final String query)

Executes the given query, providing {self} variable with the node-id and returns a single result converted to the target type.

<T> T NodeBacked.findByQuery(final String query, final Class<T> targetType)

20.12. Transactions

Neo4j is a transactional database, only allowing modifications to be performed within transaction boundaries. Reading data does however not require transactions. Spring Data Neo4j integrates nicely with both the declarative transaction support with @Transactional as well as the manual transaction handling with TransactionTemplate. It also supports the rollback mechanisms of the Spring Testing library.

Spring Data Neo4j integrates with transaction managers configured using Spring. The simplest scenario of just running the graph database uses a SpringTransactionManager provided by the Neo4j kernel to be used with Spring's JtaTransactionManager. That is, configuring Spring to use Neo4j's transaction manager.

Note

To avoid name collisons the transaction manager configured by Spring Data Neo4j is called neo4jTransactionManager and is aliased to transactionManager. So defining a separate transactionManager bean should not interfere with Spring Data Neo4j operations.

Note

The explicit XML configuration given below is encoded in the Neo4jConfiguration configuration bean that uses Spring's @Configuration feature. This greatly simplifies the configuration of Spring Data Neo4j.

Example 20.24. Simple transaction manager configuration

<bean id="neo4jTransactionManager" 
	   class="org.springframework.transaction.jta.JtaTransactionManager">
    <property name="transactionManager">
        <bean class="org.neo4j.kernel.impl.transaction.SpringTransactionManager">
            <constructor-arg ref="graphDatabaseService"/>
        </bean>
    </property>
    <property name="userTransaction">
        <bean class="org.neo4j.kernel.impl.transaction.UserTransactionImpl">
            <constructor-arg ref="graphDatabaseService"/>
        </bean>
    </property>
</bean>

<tx:annotation-driven mode="aspectj" transaction-manager="neo4jTransactionManager"/>

For scenarios with multiple transactional resources there are two options. The first option is to have Neo4j participate in the externally configured transaction manager using the Spring support in Neo4j by enabling the configuration parameter for your graph database. Neo4j will then use Spring's transaction manager instead of its own.

Example 20.25. Neo4j Spring integration

<![CDATA[<context:annotation-config />
<context:spring-configured/>

<bean id="transactionManager" 
	         class="org.springframework.transaction.jta.JtaTransactionManager">
    <property name="transactionManager">
        <bean id="jotm" class="org.springframework.data.neo4j.transaction.JotmFactoryBean"/>
    </property>
</bean>

<bean id="graphDatabaseService" class="org.neo4j.kernel.EmbeddedGraphDatabase" 
	   destroy-method="shutdown">
    <constructor-arg value="target/test-db"/>
    <constructor-arg>
        <map>
            <entry key="tx_manager_impl" value="spring-jta"/>
        </map>
    </constructor-arg>
</bean>

<tx:annotation-driven mode="aspectj" transaction-manager="transactionManager"/>

One can also configure a stock XA transaction manager (e.g. Atomikos, JOTM, App-Server-TM) to be used with Neo4j and the other resources. For a bit less secure but fast 1-phase-commit-best-effort, use ChainedTransactionManager, which comes bundled with Spring Data Neo4j. It takes a list of transaction managers as constructor params and will handle them in order for transaction start and commit (or rollback) in the reverse order.

Example 20.26. ChainedTransactionManager example

<![CDATA[<bean id="jpaTransactionManager"
        class="org.springframework.orm.jpa.JpaTransactionManager">
    <property name="entityManagerFactory" ref="entityManagerFactory"/>
</bean>
<bean id="jtaTransactionManager"
        class="org.springframework.transaction.jta.JtaTransactionManager">
    <property name="transactionManager">
        <bean class="org.neo4j.kernel.impl.transaction.SpringTransactionManager">
            <constructor-arg ref="graphDatabaseService" />
        </bean>
    </property>
    <property name="userTransaction">
        <bean  class="org.neo4j.kernel.impl.transaction.UserTransactionImpl">
            <constructor-arg ref="graphDatabaseService" />
        </bean>
    </property>
</bean>
<bean id="transactionManager"
        class="org.springframework.data.neo4j.transaction.ChainedTransactionManager">
    <constructor-arg>
        <list>
            <ref bean="jpaTransactionManager"/>
            <ref bean="jtaTransactionManager"/>
        </list>
    </constructor-arg>
</bean>

<tx:annotation-driven mode="aspectj" transaction-manager="transactionManager"/>

20.13. Detached node entities in advanced mapping mode

This section only applies to the advanced mapping (AspectJ-backed). The simple mapping always detaches entities on load as it copies the data out of the graph into the entities and stores it back fully too.

Node entities can be in two different persistence states: attached or detached. By default, newly created node entities are in the detached state. When persist() or template.save() is called on the entity, it becomes attached to the graph, and its properties and relationships are stores in the database. If the save operation is not called within a transaction, it automatically creates an implicit transaction only for the operation.

Changing an attached entity inside a transaction will immediately write through the changes to the datastore. Whenever an entity is changed outside of a transaction it becomes detached. The changes are stored in the entity (its fields) itself until the next call to a save operation.

All entities returned by library functions are initially in an attached state. Just as with any other entity, changing them outside of a transaction detaches them, and they must be reattached with persist() for the data to be saved.

Example 20.27. Persisting entities

@NodeEntity
class Person {
    String name;
    Person(String name) { this.name = name; }
}

// Store Michael in the database.
Person p = new Person("Michael").persist();

20.13.1. Relating detached entities

As mentioned above, an entity simply created with the new keyword starts out detached. It also has no state assigned to it. If you create a new entity with new and then throw it away, the database won't be touched at all.

Now consider this scenario:

Example 20.28. Relationships outside of transactions

@NodeEntity
class Movie {
    private Actor topActor;
    public void setTopActor(Actor actor) {
        topActor = actor;
    }
}

@NodeEntity
class Actor {
}

Movie movie = new Movie();
Actor actor = new Actor();

movie.setTopActor(actor);


Neither the actor nor the movie has been assigned a node in the graph. If we were to call movie.persist(), then Spring Data Neo4j would first create a node for the movie. It would then note that there is a relationship to an actor, so it would call actor.persist() in a cascading fashion. Once the actor has been persisted, it will create the relationship from the movie to the actor. All of this will be done atomically in one transaction.

Important to note here is that if actor.persist() is called instead, then only the actor will be persisted. The reason for this is that the actor entity knows nothing about the movie entity. It is the movie entity that has the reference to the actor. Also note that this behavior is not dependent on any configured relationship direction on the annotations. It is a matter of Java references and is not related to the data model in the database.

The save operation (merge) stores all properties of the entity to the graph database and puts the entity in attached mode. There is no need to update the reference to the Java POJO as the underlying backing node handles the read-through transparently. If multiple object instances that point to the same node are persisted, the ordering is not important as long as they contain distinct changes. For concurrent changes a concurrent modification exception is thrown (subject to be parameterized in the future).

If the relationships form a cycle, then the entities will first of all be assigned a node in the database, and then the relationships will be created. The cascading of persist() is however only cascaded to related entity fields that have been modified.

In the following example, the actor and the movie are both attached entites, having both been previously persisted to the graph:

Example 20.29. Cascade for modified fields

actor.setName("Billy Bob");
movie.persist();


In this case, even though the movie has a reference to the actor, the name change on the actor will not be persisted by the call to movie.persist(). The reason for this is, as mentioned above, that cascading will only be done for fields that have been modified. Since the movie.topActor field has not been modified, it will not cascade the persist operation to the actor.

20.14. Entity type representation

There are several ways to represent the Java type hierarchy of the data model in the graph. In general, for all node and relationship entities, type information is needed to perform certain repository operations. Some of this type information is saved in the graph database.

Implementations of TypeRepresentationStrategy take care of persisting this information during entity instance creation. They also provide the repository methods that use this type information to perform their operations, like findAll and count. The derived finderMethods also use the type information for graph global queries.

There are three available implementations for node entities to choose from.

  • IndexingNodeTypeRepresentationStrategy this is the default strategy used.

    Stores entity types in the integrated index. Each entity node gets indexed with its type and all supertypes that are also @NodeEntity-annotated. The special index used for this is named __types__. Additionally, in order to retrieve the type of an entity node, each node has a property __type__ with the fully qualified type of that entity.

  • SubReferenceNodeTypeRepresentationStrategy

    Stores entity types in a tree in the graph representing the type hierarchy. Each entity has a INSTANCE_OF relationship to a type node representing that entity's type. The type may or may not have a SUBCLASS_OF relationship to another type node.

  • NoopNodeTypeRepresentationStrategy

    Does not store any type information, and does hence not support finding by type, counting by type, or retrieving the type of any entity.

There are two implementations for relationship entities available, same behavior as the corresponding ones above:

  • IndexingRelationshipTypeRepresentationStrategy

    Stores relationship entity types in the integrated index. Each entity relationship gets indexed with its type and all supertypes that are also @RelationshipEntity-annotated. The special index used for this is named __rel_types__. Additionally, in order to retrieve the type of an entity relationship, each relationship has a property __type__ with the fully qualified type of that entity.

  • NoopRelationshipTypeRepresentationStrategy

Spring Data Neo4j will by default autodetect which are the most suitable strategies for node and relationship entities. For new data stores, it will always opt for the indexing strategies. If a data store was created with the olderSubReferenceNodeTypeRepresentationStrategy, then it will continue to use that strategy for node entities. It will however in that case use the no-op strategy for relationship entities, which means that the old data stores have no support for searching for relationship entities. The indexing strategies are recommended for all new users.

20.15. Bean validation (JSR-303)

Spring Data Neo4j supports property-based validation support. When a property is changed and persisted, it is checked against the annotated constraints, e.g. @Min, @Max, @Size, etc. Validation errors throw a ValidationException. The validation support that comes with Spring is used for evaluating the constraints. To use this feature, a validator has to be registered with the Neo4jTemplate, which is done automatically by the Neo4jConfiguration if one is present in the Spring Config.

Example 20.30. Bean validation

@NodeEntity
class Person {
    @Size(min = 3, max = 20)
    String name;

    @Min(0) @Max(100)
    int age;
}