CODEWITHSUNDEEP
neo4jcypher
JeffProd
JeffProd

Reputation: 3148

Neo4j Cypher : listing edges

Having this data for example :

CREATE
(p1:Person {name:"p1"}),
(p2:Person {name:"p2"}),
(p3:Person {name:"p3"}),
(p4:Person {name:"p4"}),
(p5:Person {name:"p5"}),
(p1)-[:KNOWS]->(p2),
(p1)-[:KNOWS]->(p3),
(p1)-[:KNOWS]->(p4),
(p5)-[:KNOWS]->(p3),
(p5)-[:KNOWS]->(p4)

I want to get common relationships between p1 and p5 :

MATCH (p1:Person {name:"p1"})-[r1:KNOWS]-(p:Person)-[r2:KNOWS]-(p5:Person {name:"p5"})
RETURN p, p1, p5

This returns 4 nodes : p1, p3, p4, p5 and 4 edges.

My aim is to get edges with direction as table rows : from and to. So this seems to works :

MATCH (p1:Person {name:"p1"})-[r1:KNOWS]-(p:Person)-[r2:KNOWS]-(p5:Person {name:"p5"})
RETURN startNode(r1).name AS from, endNode(r1).name AS to
UNION
MATCH (p1:Person {name:"p1"})-[r1:KNOWS]-(p:Person)-[r2:KNOWS]-(p5:Person {name:"p5"})
RETURN startNode(r2).name AS from, endNode(r2).name AS to

The result is a table :

from | to
-----|----
p1   | p3
p1   | p4
p5   | p3
p5   | p4

My questions are :

Upvotes: 0

Views: 111

Answers (1)

Christophe Willemsen
Christophe Willemsen

Reputation: 20185

The best way to check performance is to PROFILE your queries.

Is it correct ?

I'm not sure why you do a UNION, you can easily use a path check : 

PROFILE MATCH (p1:Person {name:"p1"}), (p5:Person {name:"p5"})
MATCH path=(p1)-[*..2]-(p5)
UNWIND rels(path) AS r
RETURN startNode(r).name AS from, endNode(r).name AS to

Is it the best way to do it ? I mean about performance when there will be thousands of nodes.

Generally you would match first the start and end nodes of the path you want with single lookups (make sure you have an index/constraint on the label/property pair for the Person nodes). Depending on your graph degree this can be an extensive operation, you can fine tune by limiting the max depth of the paths *..15 for example.

And what if i want common nodes to 3 persons ?

There are multiple ways depending on the size of your graph :

a) if not too many nodes :

Match the 3 nodes and find Persons that have at least one connection to ALL 3:

PROFILE MATCH (p:Person) WHERE p.name IN ["p1","p4","p3"]
WITH collect(p) AS persons
MATCH (p:Person) WHERE ALL(x IN persons WHERE EXISTS((x)--(p)))
RETURN p

b) some tuning, assume one common will be directly connected to the first node in the 3

PROFILE MATCH (p:Person) WHERE p.name IN ["p1","p4","p3"]
WITH collect(p) AS persons
WITH persons, persons[0] as p
MATCH (p)-[:KNOWS]-(other)
WHERE ALL (x IN persons WHERE EXISTS((x)--(other)))
RETURN other

c) if you need the commons in a multiple depth path :

PROFILE MATCH (p:Person) WHERE p.name IN ["p1","p4","p3"]
WITH collect(p) AS persons
WITH persons, persons[0] as p1, persons[1] as p2
MATCH path=(p1)-[*..15]-(p2)
WHERE ANY(x IN nodes(path) WHERE x = persons[2])
UNWIND rels(path) AS commonRel
WITH distinct commonRel AS r
RETURN startNode(r) AS from, endNode(r) AS to

I would suggest to grow your graph and try/tune your use cases

Upvotes: 2

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