Based on a slideshow by Max De Marzi:
http://www.slideshare.net/maxdemarzi/cypher-12154713
Updated for Neo4j 2.x (removed `START` clauses and `?` syntax for relationships). I also removed some slides to make it more appropriate an a simply Cypher introduction
19. MATCH
SELECT *
FROM people
WHERE people.firstName = “Max”
MATCH (max:Person {firstName: ‘Max’})
RETURN max
MATCH (max:Person)
WHERE max.firstName = ‘Max’
RETURN max
20. MATCH
SELECT skills.*
FROM users
JOIN skills ON users.id = skills.user_id
WHERE users.first_name = ‘Max’
MATCH (user:User {firstName: ‘Max’}) -->
(skill:Skill)
RETURN skill
21. OPTIONAL MATCH
SELECT skills.*
FROM users
LEFT JOIN skills ON users.id = skills.user_id
WHERE users.first_name = ‘Max’
MATCH (user:User {firstName: ‘Max’})
OPTIONAL MATCH user –-> (skill:Skill)
RETURN skill
22. SELECT skills.*, user_skill.*
FROM users
JOIN user_skill ON users.id = user_skill.user_id
JOIN skills ON user_skill.skill_id = skill.id
WHERE users.first_name = ‘Max’
24. Indexes
Used as multiple starting points, not to
speed up any traversals
CREATE INDEX ON :User(name);
MATCH (a:User {name: ‘Max’})-[r:KNOWS]-b
RETURN ID(a), ID(b), r.weight;
25. Complicated Match
Some UGLY recursive self join on the
groups table
MATCH group <-[:BELONGS_TO*]- (max:Person
{name: ‘Max’})
RETURN group
26. Where
SELECT person.*
FROM person
WHERE person.age >32
OR person.hair = "bald"
MATCH (person:Person)
WHERE person.age > 32 OR person.hair =
"bald"
RETURN person
27. Return
SELECT people.name, count(*)
FROM people
GROUP BY people.name
ORDER BY people.name
MATCH (person:Person)
RETURN person.name, count(*)
ORDER BY person.name
28. Order By, Parameters
Same as SQL
{node_id} expected as part of request
MATCH (me)-[:follows]->(friends)-[:follows]->(fof)-[:follows]->(fofof)-
[:follows]->others
WHERE ID(me) = {node_id}
RETURN me.name, friends.name, fof.name, fofof.name, count(others)
ORDER BY friends.name, fof.name, fofof.name, count(others) DESC
29. Graph Functions
Some UGLY multiple recursive self and inner joins
on the user and all related tables
MATCH p = shortestPath( lucy-[*]-kevin )
WHERE ID(lucy) = 1000 AND ID(kevin) = 759
RETURN p
30. Aggregate Functions
ID: get the neo4j assigned identifier
Count: add up the number of occurrences
Min: get the lowest value
Max: get the highest value
Avg: get the average of a numeric value
Distinct: remove duplicates
MATCH (me:User)-[r:wrote]-()
RETURN ID(me), me.name, count(r), min(r.date), max(r.date)
ORDER BY ID(me)
31. Functions
Collect: put aggregated values in a list
MATCH (a:User)-[:follows]->b
RETURN a.name, collect(b.name)
Each result row contains a name for each user
and a list of names which that user follows
32. Combine Functions
Collect the ID of friends
MATCH (me:User)<-[r:wrote]-(friends)
RETURN ID(me), me.name, collect(ID(friends)), collect(r.date)
ORDER BY ID(me)
34. Uses
Six Degrees of Kevin Bacon
MATCH path = allShortestPaths( me-[*]->them )
WHERE ID(me) = {start_node_id}
AND ID(them) = {destination_node_id}
RETURN length(path),
extract(person in nodes(path) : person.name)
Length: counts the number of nodes along a path
Extract: gets the nodes/relationships from a path
35. http://thought-bytes.blogspot.com/2012/02/similarity-
based-recommendations-with.html
MATCH (me:User {id: {me_id}}), (similarUser:User),
(similarUsers)-[r:RATED]->(item)
WHERE ID(similarUser) IN {previousResult) AND
r.rating > 7 AND NOT((me)-[:RATED]->(item))
RETURN item
Items with a rating > 7 that similar users rated, but I have not
And: this and that are true
Or: this or that is true
Not: this is false
Boolean Operations
36. START london = node(1), moscow = node(2)
MATCH path = london -[*]-> moscow
WHERE all(city in nodes(path) where city.capital = true)
Predicates
ALL: closure is true for all items
ANY: closure is true for any item
NONE: closure is true for no items
SINGLE: closure is true for exactly 1 item