apoc.neighbors.byhop.count
Syntax |
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Description |
Returns the count of all |
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Input arguments |
Name |
Type |
Description |
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The starting node for the algorithm. |
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A list of relationship types to follow. Relationship types are represented using APOC’s rel-direction-pattern syntax; |
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The max number of hops to take. The default is: |
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Return arguments |
Name |
Type |
Description |
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A list of neighbor counts for each distinct hop distance. |
Usage Examples
The examples in this section are based on the following sample graph:
MERGE (mark:Person {name: "Mark"})
MERGE (praveena:Person {name: "Praveena"})
MERGE (joe:Person {name: "Joe"})
MERGE (lju:Person {name: "Lju"})
MERGE (michael:Person {name: "Michael"})
MERGE (emil:Person {name: "Emil"})
MERGE (ryan:Person {name: "Ryan"})
MERGE (ryan)-[:FOLLOWS]->(joe)
MERGE (joe)-[:FOLLOWS]->(mark)
MERGE (mark)-[:FOLLOWS]->(emil)
MERGE (michael)-[:KNOWS]-(emil)
MERGE (michael)-[:KNOWS]-(lju)
MERGE (michael)-[:KNOWS]-(praveena)
MERGE (emil)-[:FOLLOWS]->(joe)
MERGE (praveena)-[:FOLLOWS]->(joe)
This procedure computes a node’s neighborhood at multiple hop counts.
The following returns the number of people that Emil KNOWS
and the number that have FOLLOWS
relationships to him, at up to 3 hops:
MATCH (p:Person {name: "Emil"})
CALL apoc.neighbors.byhop.count(p, "KNOWS|<FOLLOWS", 3)
YIELD value
RETURN value
value |
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[2, 3, 1] |
And as expected we have a count of 2 at level 1, 3 at level 2, and 1 at level 3.
We could even turn that list of numbers into a map with the key being the number of hops and the value the neighborhood size.
The following query shows how to do this using the apoc.map.fromLists
function:
MATCH (p:Person {name: "Emil"})
CALL apoc.neighbors.byhop.count(p, "KNOWS|<FOLLOWS", 3)
YIELD value
RETURN apoc.map.fromLists(
[value in range(1, size(value)) | toString(value)],
value) AS value
value |
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{ |
If we also want to know which nodes are in our neighborhood, we can do that as well. See apoc.neighbors.byhop.