Virtual Nodes/Rels

Virtual Nodes and Relationships don’t exist in the graph, they are only returned to the UI/user for representing a graph projection. They can be visualized or processed otherwise. Please note that they have negative id’s.

Function Overview

CALL apoc.create.vNode(['Label'], {key:value,…​}) YIELD node

returns a virtual node

apoc.create.vNode(['Label'], {key:value,…​})

function returns a virtual node

CALL apoc.create.vNodes(['Label'], [{key:value,…​}])

returns virtual nodes

apoc.create.virtual.fromNode(node, [propertyNames])

function returns a virtual node built from an existing node with only the requested properties

CALL apoc.create.vRelationship(nodeFrom,'KNOWS',{key:value,…​}, nodeTo) YIELD rel

returns a virtual relationship

apoc.create.vRelationship(nodeFrom,'KNOWS',{key:value,…​}, nodeTo)

function returns a virtual relationship

CALL apoc.create.vPattern({_labels:['LabelA'],key:value},'KNOWS',{key:value,…​}, {_labels:['LabelB'],key:value})

returns a virtual pattern

CALL apoc.create.vPatternFull(['LabelA'],{key:value},'KNOWS',{key:value,…​},['LabelB'],{key:value})

returns a virtual pattern

Virtual Nodes/Rels Example

Simple example aggregate Relationships
MATCH (from:Account)-[:SENT]->(p:Payment)-[:RECEIVED]->(to:Account)
RETURN from, to, apoc.create.vRelationship(from,'PAID',{amount:sum(p.amount)},to) as rel;
Example with virtual node lookups, people grouped by their countries
MATCH (p:Person) WITH collect(distinct as countries
WITH [cName IN countries | apoc.create.vNode(['Country'],{name:cName})] as countryNodes
WITH apoc.coll.groupBy(countryNodes,'name') as countries
MATCH (p1:Person)-[:KNOWS]->(p2:Person)
WITH as cFrom, as cTo, count(*) as count, countries
RETURN countries[cFrom] as from, countries[cTo] as to, apoc.create.vRelationship(countries[cFrom],'KNOWS',{count:count},countries[cTo]) as rel;

That’s of course easier with

From a simple dataset


We can create a virtual copy, adding as attribute name the labels value

MATCH (a)-[r]->(b)
WITH head(labels(a)) AS l, head(labels(b)) AS l2, type(r) AS rel_type, count(*) as count
CALL apoc.create.vNode([l],{name:l}) yield node as a
CALL apoc.create.vNode([l2],{name:l2}) yield node as b
CALL apoc.create.vRelationship(a,rel_type,{count:count},b) yield rel
Virtual nodes and virtual relationships have always a negative id

Virtual nodes can also be built from existing nodes, filtering the properties in order to get a subset of them. In this case, the Virtual node keeps the id of the original node.

MATCH (node:Person {name:'neo', age:'42'})
return apoc.create.virtual.fromNode(node, ['name']) as person
Virtual pattern vPattern
CALL apoc.create.vPattern({_labels:['Person'],name:'Mary'},'KNOWS',{since:2012},{_labels:['Person'],name:'Michael'})

We can add more labels, just adding them on _labels

CALL apoc.create.vPattern({_labels:['Person', 'Woman'],name:'Mary'},'KNOWS',{since:2012},{_labels:['Person', 'Man'],name:'Michael'})
Virtual pattern full vPatternFull
CALL apoc.create.vPatternFull(['British','Person'],{name:'James', age:28},'KNOWS',{since:2009},['Swedish','Person'],{name:'Daniel', age:30})

We can create a virtual pattern from an existing one

CREATE(a:Person {name:'Daniel'})-[r:KNOWS]->(b:Person {name:'John'})

From this dataset we can create a virtual pattern

MATCH (a)-[r]->(b)
WITH head(labels(a)) AS labelA, head(labels(b)) AS labelB, type(r) AS rel_type, AS aName, AS bName
CALL apoc.create.vPatternFull([labelA],{name: aName},rel_type,{since:2009},[labelB],{name: bName}) yield from, rel, to