Native projection

Native projections are the easiest way to create a GDS graph from a Neo4j database. A native projection is entirely described by configuration parameters.

Node projections and relationship projections describe the way nodes and relationships are loaded (projected) from the database into the in-memory graph. While node projections are based on node labels, relationship projections are based on relationship types. Both can include properties.

Considerations

Lifecycle

Projected graphs reside in memory (in the graph catalog) until any of the following happens:

  • The graph is dropped with the gds.graph.drop procedure.

  • The Neo4j database from which the graph was projected is stopped or dropped.

  • The Neo4j DBMS is stopped.

Node property support

Native projections can only project a limited set of node property types from the Neo4j database. The Node Properties page details which node property types are supported. Other types of node properties have to be transformed or encoded into one of the supported types in order to be projected using a native projection.

Syntax

CALL gds.graph.project(
  graphName: String,
  nodeProjection: String or List or Map,
  relationshipProjection: String or List or Map,
  configuration: Map
) YIELD
  graphName: String,
  nodeProjection: Map,
  nodeCount: Integer,
  relationshipProjection: Map,
  relationshipCount: Integer,
  projectMillis: Integer
Table 1. Parameters
Name Type Optional Description

graphName

String

no

The name under which the graph is stored in the catalog.

nodeProjection

String, List or Map

no

One or more node projections.

relationshipProjection

String, List or Map

no

One or more relationship projections.

configuration

Map

yes

Additional parameters to configure the native projection.

Table 2. Configuration
Name Type Default Description

readConcurrency

Integer

4

The number of concurrent threads used for creating the graph.

nodeProperties

String, List or Map

{}

The node properties to load from nodes that match any of the labels specified in nodeProjection.

relationshipProperties

String, List or Map

{}

The relationship properties to load from relationships that match any of the types specified in relationshipProjection.

validateRelationships

Boolean

false

Whether to throw an error if the relationshipProjection includes relationships between nodes not part of the nodeProjection.

jobId

String

Generated internally

An ID that can be provided to more easily track the projection’s progress.

Table 3. Results
Name Type Description

graphName

String

The name under which the graph is stored in the catalog.

nodeProjection

Map

The node projections used to project the graph.

nodeCount

Integer

The number of nodes stored in the projected graph.

relationshipProjection

Map

The relationship projections used to project the graph.

relationshipCount

Integer

The number of relationships stored in the projected graph.

projectMillis

Integer

Milliseconds for projecting the graph.

Node projection

A node projection can be specified using any of the following forms:

  • A single string (either a Neo4j node label <label> or a wildcard *)

  • A list of Neo4j node labels ([<label_1>, <label_2>, <label_3>])

  • A projection map, where each key is a node label in the projected graph and each value is itself a map

The projection map is specified as follows:

{
    <projected_label_1>: {                       (1)
        label: <label_1>,                        (2)
        properties: <prop_1>                     (3)
    },
    <projected_label_2>: {
        label: <label_2>,
        properties: [<prop_1>, <prop_2>, ...]    (3)
    },
    <projected_label_3>: {
        label: <label_3>,
        properties: {                            (3)
            <projected_prop_1>: {                (4)
                property: <prop_1>,              (5)
                defaultValue: <default_1>        (6)
            },
            <projected_prop_2>: {
                property: <prop_2>,
                defaultValue: <default_2>
            },
            ...
        }
    },
    ...
}
1 Node label to create in the projected graph. It can be the same as the corresponding Neo4j node label.
2 Source Neo4j node label as a string. Default: same as the projected label (<projected_label_1> here).
3 Node property projection, specified as a single Neo4j node property, a list of Neo4j node properties, or a projection map. Default: empty map.
4 Node property to create in the projected graph. It can be the same as the corresponding Neo4j node property.
5 Source Neo4j node property as a string. Default: same as the projected property name (<projected_prop_1> here).
6 Default value if the property is not defined for a node. Default: a fallback value depending on the property type.

Notes

  • When specified as a string or a list, the projection does not include any node properties.

  • The wildcard form does not retain the labels on the projected nodes. Node labels are useful with algorithms that fully support heterogeneous nodes. The Graph with all the node labels example shows how to retain all the labels for these cases.

  • All nodes with any of the specified node labels are projected into the GDS graph.

  • All specified node labels and properties must exist in the database. You can use the db.createProperty() procedure to create a new node property without modifying the database.

Relationship projection

A Relationship projection can be specified using any of the following forms:

  • A single string (either a Neo4j relationship type <type> or a wildcard *)

  • A list of Neo4j relationship types ([<type_1>, <type_2>, <type_3>])

  • A projection map, where each key is a relationship type in the projected graph and each value is itself a map

The projection map is specified as follows:

{
    <projected_type_1>: {                        (1)
        type: <type_1>,                          (2)
        orientation: <orientation_1>,            (3)
        aggregation: <aggregation_1>,            (4)
        properties: <prop_1>                     (5)
    },
    <projected_type_2>: {
        type: <type_2>,
        orientation: <orientation_2>,
        aggregation: <aggregation_2>,
        properties: [<prop_1>, <prop_2>, ...]    (5)
    },
    <projected_type_3>: {
        type: <type_3>,
        orientation: <orientation_3>,
        aggregation: <aggregation_3>,
        properties: {                            (5)
            <projected_prop_1>: {                (6)
                property: <prop_1>,              (7)
                defaultValue: <default_1>,       (8)
                aggregation: <aggregation_1>     (9)
            },
            <projected_prop_2>: {
                property: <prop_2>,
                defaultValue: <default_2>,
                aggregation: <aggregation_2>
            },
            ...
        }
    },
    ...
}
1 Relationship type to create in the projected graph. It can be the same as the corresponding Neo4j relationship type.
2 Source Neo4j relationship type as a string. Default: same as the projected type (<projected_type_1> here).
3 Relationship orientation in the projected graph. Allowed values: NATURAL (default, same as orientation in the Neo4j graph), UNDIRECTED (makes all relationships undirected), REVERSE (reverses the orientation for all relationships).
4 Handling of multiple instances of all the relationship properties associated to the relationship. Allowed values: NONE (default), SINGLE, COUNT, MIN, MAX, SUM.
5 Relationship property projection, specified as a single Neo4j relationship property, a list of Neo4j relationship properties, or a projection map. Default: empty map.
6 Relationship property to create in the projected graph. It can be the same as the corresponding Neo4j relationship property.
7 Source Neo4j relationship property as a string. Default: same as the projected property (<projected_prop_1> here).
8 Default value if the property is not defined for a relationship. Default: Double.NaN.
9 Handling of multiple instances of a specific relationship property associated to the relationship. Allowed values: NONE (default), SINGLE, COUNT, MIN, MAX, SUM.

Notes

  • When specified as a string or a list, the projection does not include any relationship properties.

  • The wildcard form does not retain the types on the projected relationships. Relationship types are useful with algorithms that fully support heterogeneous relationships. The Graph with all the node labels example shows how to retain all the relationships for these cases.

  • All relationships with any of the specified relationship types, and whose endpoint nodes are included in the node projection, are projected into the GDS graph. The validateRelationships configuration parameter controls whether to fail or silently discard relationships whose endpoint nodes are not included in the node projection.

  • All specified relationship types and properties must exist in the database. You can use the db.createProperty() procedure to create a new relationship property without modifying the database.

Examples

All the examples below should be run in an empty database.

In order to demonstrate the GDS Graph Projection capabilities we are going to create a small social network graph in Neo4j. The example graph looks like this:

Visualization of the example graph
The following Cypher statement will create the example graph in the Neo4j database:
CREATE
  (florentin:Person { name: 'Florentin', age: 16 }),
  (adam:Person { name: 'Adam', age: 18 }),
  (veselin:Person { name: 'Veselin', age: 20, ratings: [5.0] }),
  (hobbit:Book { name: 'The Hobbit', isbn: 1234, numberOfPages: 310, ratings: [1.0, 2.0, 3.0, 4.5] }),
  (frankenstein:Book { name: 'Frankenstein', isbn: 4242, price: 19.99 }),

  (florentin)-[:KNOWS { since: 2010 }]->(adam),
  (florentin)-[:KNOWS { since: 2018 }]->(veselin),
  (florentin)-[:READ { numberOfPages: 4 }]->(hobbit),
  (florentin)-[:READ { numberOfPages: 42 }]->(hobbit),
  (adam)-[:READ { numberOfPages: 30 }]->(hobbit),
  (veselin)-[:READ]->(frankenstein)

Simple graph

A simple graph is a graph with only one node label and relationship type, i.e., a monopartite graph. We are going to start with demonstrating how to load a simple graph by projecting only the Person node label and KNOWS relationship type.

Project Person nodes and KNOWS relationships:
CALL gds.graph.project(
  'persons',            (1)
  'Person',             (2)
  'KNOWS'               (3)
)
YIELD
  graphName AS graph, nodeProjection, nodeCount AS nodes, relationshipProjection, relationshipCount AS rels
1 The name of the graph. Afterwards, persons can be used to run algorithms or manage the graph.
2 The nodes to be projected. In this example, the nodes with the Person label.
3 The relationships to be projected. In this example, the relationships of type KNOWS.
Table 4. Results
graph nodeProjection nodes relationshipProjection rels

"persons"

{Person={label=Person, properties={}}}

3

{KNOWS={aggregation=DEFAULT, indexInverse=false, orientation=NATURAL, properties={}, type=KNOWS}}

2

In the example above, we used a short-hand syntax for the node and relationship projection. The used projections are internally expanded to the full Map syntax as shown in the Results table. In addition, we can see the projected in-memory graph contains three Person nodes, and the two KNOWS relationships.

Multi-graph

A multi-graph is a graph with multiple node labels and relationship types.

To project multiple node labels and relationship types, we can adjust the projections as follows:

Project Person and Book nodes and KNOWS and READ relationships:
CALL gds.graph.project(
  'personsAndBooks',    (1)
  ['Person', 'Book'],   (2)
  ['KNOWS', 'READ']     (3)
)
YIELD
  graphName AS graph, nodeProjection, nodeCount AS nodes, relationshipCount AS rels
1 Projects a graph under the name personsAndBooks.
2 The nodes to be projected. In this example, the nodes with a Person or Book label.
3 The relationships to be projected. In this example, the relationships of type KNOWS or READ.
Table 5. Results
graph nodeProjection nodes rels

"personsAndBooks"

{Book={label=Book, properties={}}, Person={label=Person, properties={}}}

5

6

In the example above, we used a short-hand syntax for the node and relationship projection. The used projections are internally expanded to the full Map syntax as shown for the nodeProjection in the Results table. In addition, we can see the projected in-memory graph contains five nodes, and the two relationships.

Relationship orientation

By default, relationships are loaded in the same orientation as stored in the Neo4j db. In GDS, we call this the NATURAL orientation. Additionally, we provide the functionality to load the relationships in the REVERSE or even UNDIRECTED orientation.

Project Person nodes and undirected KNOWS relationships:
CALL gds.graph.project(
  'undirectedKnows',                    (1)
  'Person',                             (2)
  {KNOWS: {orientation: 'UNDIRECTED'}}  (3)
)
YIELD
  graphName AS graph,
  relationshipProjection AS knowsProjection,
  nodeCount AS nodes,
  relationshipCount AS rels
1 Projects a graph under the name undirectedKnows.
2 The nodes to be projected. In this example, the nodes with the Person label.
3 Projects relationships with type KNOWS and specifies that they should be UNDIRECTED by using the orientation parameter.
Table 6. Results
graph knowsProjection nodes rels

"undirectedKnows"

{KNOWS={aggregation=DEFAULT, indexInverse=false, orientation=UNDIRECTED, properties={}, type=KNOWS}}

3

4

To specify the orientation, we need to write the relationshipProjection with the extended Map-syntax. Projecting the KNOWS relationships UNDIRECTED, loads each relationship in both directions. Thus, the undirectedKnows graph contains four relationships, twice as many as the persons graph in Simple graph.

Node properties

To project node properties, we can either use the nodeProperties configuration parameter for shared properties, or extend an individual nodeProjection for a specific label.

Project Person and Book nodes and KNOWS and READ relationships:
CALL gds.graph.project(
  'graphWithProperties',                                (1)
  {                                                     (2)
    Person: {properties: 'age'},                        (3)
    Book: {properties: {price: {defaultValue: 5.0}}}    (4)
  },
  ['KNOWS', 'READ'],                                    (5)
  {nodeProperties: 'ratings'}                           (6)
)
YIELD
  graphName, nodeProjection, nodeCount AS nodes, relationshipCount AS rels
RETURN graphName, nodeProjection.Book AS bookProjection, nodes, rels
1 Projects a graph under the name graphWithProperties.
2 Use the expanded node projection syntax.
3 Projects nodes with the Person label and their age property.
4 Projects nodes with the Book label and their price property. Each Book that doesn’t have the price property will get the defaultValue of 5.0.
5 The relationships to be projected. In this example, the relationships of type KNOWS or READ.
6 The global configuration, projects node property rating on each of the specified labels.
Table 7. Results
graphName bookProjection nodes rels

"graphWithProperties"

{label=Book, properties={price={defaultValue=5.0, property=price}, ratings={defaultValue=null, property=ratings}}}

5

6

The projected graphWithProperties graph contains five nodes and six relationships. In the returned bookProjection we can observe, the node properties price and ratings are loaded for Books.

GDS currently only supports loading numeric properties.

Further, the price property has a default value of 5.0. Not every book has a price specified in the example graph. In the following we check if the price was correctly projected:

Verify the ratings property of Adam in the projected graph:
MATCH (n:Book)
RETURN n.name AS name, gds.util.nodeProperty('graphWithProperties', n, 'price') as price
ORDER BY price
Table 8. Results
name price

"The Hobbit"

5.0

"Frankenstein"

19.99

We can see, that the price was projected with the Hobbit having the default price of 5.0.

Relationship properties

Analogous to node properties, we can either use the relationshipProperties configuration parameter or extend an individual relationshipProjection for a specific type.

Project Person and Book nodes and READ relationships with numberOfPages property:
CALL gds.graph.project(
  'readWithProperties',                     (1)
  ['Person', 'Book'],                       (2)
  {                                         (3)
    READ: { properties: "numberOfPages" }   (4)
  }
)
YIELD
  graphName AS graph,
  relationshipProjection AS readProjection,
  nodeCount AS nodes,
  relationshipCount AS rels
1 Projects a graph under the name readWithProperties.
2 The nodes to be projected. In this example, the nodes with a Person or Book label.
3 Use the expanded relationship projection syntax.
4 Project relationships of type READ and their numberOfPages property.
Table 9. Results
graph readProjection nodes rels

"readWithProperties"

{READ={aggregation=DEFAULT, indexInverse=false, orientation=NATURAL, properties={numberOfPages={defaultValue=null, property=numberOfPages, aggregation=DEFAULT}}, type=READ}}

5

4

Next, we will verify that the relationship property numberOfPages were correctly loaded.

Stream the relationship property numberOfPages of the projected graph:
CALL gds.graph.relationshipProperty.stream('readWithProperties', 'numberOfPages')
YIELD sourceNodeId, targetNodeId, propertyValue AS numberOfPages
RETURN
  gds.util.asNode(sourceNodeId).name AS person,
  gds.util.asNode(targetNodeId).name AS book,
  numberOfPages
ORDER BY person ASC, numberOfPages DESC
Table 10. Results
person book numberOfPages

"Adam"

"The Hobbit"

30.0

"Florentin"

"The Hobbit"

42.0

"Florentin"

"The Hobbit"

4.0

"Veselin"

"Frankenstein"

NaN

We can see, that the numberOfPages property is loaded. The default property value is Double.NaN and could be changed using the Map-Syntax the same as for node properties in Node properties.

Parallel relationships

Neo4j supports parallel relationships, i.e., multiple relationships between two nodes. By default, GDS preserves parallel relationships. For some algorithms, we want the projected graph to contain at most one relationship between two nodes.

We can specify how parallel relationships should be aggregated into a single relationship via the aggregation parameter in a relationship projection.

For graphs without relationship properties, we can use the COUNT aggregation. If we do not need the count, we could use the SINGLE aggregation.

Project Person and Book nodes and COUNT aggregated READ relationships:
CALL gds.graph.project(
  'readCount',                      (1)
  ['Person', 'Book'],               (2)
  {
    READ: {                         (3)
      properties: {
        numberOfReads: {            (4)
          property: '*',            (5)
          aggregation: 'COUNT'      (6)
        }
      }
    }
  }
)
YIELD
  graphName AS graph,
  relationshipProjection AS readProjection,
  nodeCount AS nodes,
  relationshipCount AS rels
1 Projects a graph under the name readCount.
2 The nodes to be projected. In this example, the nodes with a Person or Book label.
3 Project relationships of type READ.
4 Project relationship property numberOfReads.
5 A placeholder, signaling that the value of the relationship property is derived and not based on Neo4j property.
6 The aggregation type. In this example, COUNT results in the value of the property being the number of parallel relationships.
Table 11. Results
graph readProjection nodes rels

"readCount"

{READ={aggregation=DEFAULT, indexInverse=false, orientation=NATURAL, properties={numberOfReads={defaultValue=null, property=*, aggregation=COUNT}}, type=READ}}

5

3

Next, we will verify that the READ relationships were correctly aggregated.

Stream the relationship property numberOfReads of the projected graph:
CALL gds.graph.relationshipProperty.stream('readCount', 'numberOfReads')
YIELD sourceNodeId, targetNodeId, propertyValue AS numberOfReads
RETURN
  gds.util.asNode(sourceNodeId).name AS person,
  gds.util.asNode(targetNodeId).name AS book,
  numberOfReads
ORDER BY numberOfReads DESC, person
Table 12. Results
person book numberOfReads

"Florentin"

"The Hobbit"

2.0

"Adam"

"The Hobbit"

1.0

"Veselin"

"Frankenstein"

1.0

We can see, that the two READ relationships between Florentin, and the Hobbit result in 2 numberOfReads.

Parallel relationships with properties

For graphs with relationship properties we can also use other aggregations.

Project Person and Book nodes and aggregated READ relationships by summing the numberOfPages:
CALL gds.graph.project(
  'readSums',                                                   (1)
  ['Person', 'Book'],                                           (2)
  {READ: {properties: {numberOfPages: {aggregation: 'SUM'}}}}   (3)
)
YIELD
  graphName AS graph,
  relationshipProjection AS readProjection,
  nodeCount AS nodes,
  relationshipCount AS rels
1 Projects a graph under the name readSums.
2 The nodes to be projected. In this example, the nodes with a Person or Book label.
3 Project relationships of type READ. Aggregation type SUM results in a projected numberOfPages property with its value being the sum of the numberOfPages properties of the parallel relationships.
Table 13. Results
graph readProjection nodes rels

"readSums"

{READ={aggregation=DEFAULT, indexInverse=false, orientation=NATURAL, properties={numberOfPages={defaultValue=null, property=numberOfPages, aggregation=SUM}}, type=READ}}

5

3

Next, we will verify that the relationship property numberOfPages was correctly aggregated.

Stream the relationship property numberOfPages of the projected graph:
CALL gds.graph.relationshipProperty.stream('readSums', 'numberOfPages')
YIELD
  sourceNodeId, targetNodeId, propertyValue AS numberOfPages
RETURN
  gds.util.asNode(sourceNodeId).name AS person,
  gds.util.asNode(targetNodeId).name AS book,
  numberOfPages
ORDER BY numberOfPages DESC, person
Table 14. Results
person book numberOfPages

"Florentin"

"The Hobbit"

46.0

"Adam"

"The Hobbit"

30.0

"Veselin"

"Frankenstein"

0.0

We can see, that the two READ relationships between Florentin and the Hobbit sum up to 46 numberOfReads.

Validate relationships flag

As mentioned in the syntax section, the validateRelationships flag controls whether an error will be raised when attempting to project a relationship where either the source or target node is not present in the node projection. Note that even if the flag is set to false such a relationship will still not be projected but the loading process will not be aborted.

We can simulate such a case with the graph present in the Neo4j database:

Project READ and KNOWS relationships but only Person nodes, with validateRelationships set to true:
CALL gds.graph.project(
  'danglingRelationships',
  'Person',
  ['READ', 'KNOWS'],
  {
    validateRelationships: true
  }
)
YIELD
  graphName AS graph,
  relationshipProjection AS readProjection,
  nodeCount AS nodes,
  relationshipCount AS rels
Results
org.neo4j.graphdb.QueryExecutionException: Failed to invoke procedure `gds.graph.project`: Caused by: java.lang.IllegalArgumentException: Failed to load a relationship because its target-node with id 3 is not part of the node query or projection. To ignore the relationship, set the configuration parameter `validateRelationships` to false.

We can see that the above query resulted in an exception being thrown. The exception message will provide information about the specific node id that was missing, which will help debugging underlying problems.

Graph with all the node labels

You can use the wildcard operator * to select all the node labels for the projection. However, this does not retain the label information on the projected nodes.

Use the db.labels() instead to retrieve the list of all the labels, and use it as a value for the nodeProjection parameter as in the following example:

Project all the labels:
CALL db.labels() YIELD label
WITH collect(label) AS allLabels
CALL gds.graph.project(
  'allLabelsGraph',
  allLabels,
  ['KNOWS', 'READ']
)
YIELD graphName, nodeProjection, nodeCount AS nodes, relationshipCount AS rels
RETURN *
Table 15. Results
allLabels graphName nodeProjection nodes rels

[Person, Book]

"allLabelsGraph"

{Book={label=Book, properties={}}, Person={label=Person, properties={}}}

5

6

In a similar fashion, you can select all the relationship types for the projection by using db.relationshipTypes() as a value for the relationshipProjection parameter in place of ['KNOWS', 'READ'].