Neo4j语句

 传统数据库一行就是neo4j数据库的一个节点。
  传统数据库的一个表就是neo4j 的一个标签名。

1、

[/code]
All Nodes Query

MATCH (n)

RETURN n;

2、Returning a Property

MATCH (person)-->()
RETURN person.name;

3、

MATCH (tom:Person)
WHERE tom.name = "Tom Hanks"
RETURN tom;

4、

MATCH (movie:Movie)
WHERE movie.title="Mystic River"
SET movie.released = 2003
RETURN movie;

5、

MATCH (me:Person), (movie:Movie)
WHERE me.name="My Name" AND
movie.title="Mystic River"
CREATE (me)-[:REVIEWED {rating:80, summary:"tragic character movie"}]->(movie);

acted_in = (:Person)-[:ACTED_IN]->(:Movie)

6、

MERGE (m:Movie { title:"Cloud Atlas" }) ON CREATE SET m.released = 2012 RETURN m

7、输出：（as后面是列名，输出的结果命一个名s）

MATCH (p:Person) 
RETURN p, p.name AS name, upper(p.name), coalesce(p.nickname,"n/a") AS nickname, { name: p.name,   label:head(labels(p))}
AS person

8、union语句
MATCH (actor:Person)-[r:ACTED_IN]->(movie:Movie) RETURN actor.name AS name,
type(r) AS acted_in, movie.title AS title 
UNION
MATCH (director:Person)-[r:DIRECTED]->(movie:Movie) RETURN director.name AS name, type(r) AS acted_in, movie.title
AS title

9、限制条件

MATCH (user)-[:friend]->(follower) 
WHERE user.name IN ['Joe', 'John', 'Sara', 'Maria', 'Steve'] AND follower.name =~ 'S.*' 
RETURN user.name, follower.name

10、Single shortest path

MATCH (martin:Person { name:"Martin Sheen" }),(oliver:Person { name:"Oliver Stone" }), p = shortestPath((martin)-[*..15]-(oliver)) RETURN p

11、All shortest paths

MATCH (martin:Person { name:"Martin Sheen" }),(michael:Person { name:"Michael Douglas" }), p = allShortestPaths((martin)-[*]-(michael)) RETURN p

12、Relationship by id

1）MATCH ()-[r]->() WHERE id(r)= 0 RETURN r 

2）MATCH (n) WHERE id(n) IN [0,3,5] RETURN n 

13

match (a:Entity{name:"山东省财金投资有限公司"})-[*1]->(b)  return a, b
(a)-[*3..]->(b)
(a)-[*..5]->(b)
(a)-[*]->(b) 

MATCH (me)-[:KNOWS*1..2]-(remote_friend) WHERE me.name = "Filipa"
RETURN remote_friend.name
 

14  Order by 

MATCH (n) RETURN n ORDER BY n.name 

RETURN [x IN range(0,10) WHERE x % 2 = 0] AS result

15 limit

MATCH (n) RETURN n ORDER BY n.name LIMIT 3 

16 skip(从三开始输出)

MATCH (n) RETURN n ORDER BY n.name SKIP 3 

MATCH (n) WITH n ORDER BY n.name DESC LIMIT 3 RETURN collect(n.name)

Query MATCH (david { name: "David" })--(otherPerson)-->() WITH otherPerson, count(*) AS foaf WHERE foaf > 1 RETURN otherPerson 

17Combine two queries

MATCH (n:Actor) RETURN n.name AS name
 UNION ALL 
MATCH (n:Movie) RETURN n.title AS name 

18   Combine two queries and remove duplicates
MATCH (n:Actor) RETURN n.name AS name 
UNION
 MATCH (n:Movie) RETURN n.title AS name 

19 Matching on a bound relationship

MATCH (a)-[r]-(b) WHERE id(r)= 0 RETURN a,b

20 Single shortest path

MATCH (martin:Person { name:"Martin Sheen" }),(oliver:Person
{ name:"Oliver Stone" }), p = shortestPath((martin)-[*..15]-(oliver))
RETURN p

21  All shortest paths

MATCH (martin:Person { name:"Martin Sheen" }),(michael:Person { name:"Michael
Douglas" }), p = allShortestPaths((martin)-[*]-(michael)) RETURN p 

22  Multiple nodes by id

MATCH (n) WHERE id(n) IN [0,3,5] RETURN
n 

23  Properties on optional elements
MATCH (a:Movie { title: 'Wall Street'
}) OPTIONAL MATCH (a)-->(x) RETURN x, x.name 

24
MATCH (n) WHERE n.age < 30 RETURN n 

25 exists
MATCH (n) WHERE exists(n.belt) RETURN
n 

MATCH (n) WHERE n.name STARTS WITH
'Pet' RETURN n 

26 ENDS WITH
MATCH (n) WHERE n.name ENDS WITH 'ter'
RETURN n 

27CONTAINS
MATCH (n) WHERE n.name CONTAINS 'ete'
RETURN n 

28 =~ "regexp"
MATCH (n) WHERE n.name =~ 'Tob.*' RETURN
n

29  Using path patterns in WHERE
MATCH (tobias { name: 'Tobias' }),(others)
WHERE others.name IN ['Andres', 'Peter'] AND (tobias)<--(others) RETURN others 

30 Filter on patterns using NOT
MATCH (persons),(peter { name: 'Peter'
})
WHERE NOT (persons)-->(peter) 
RETURN persons

31
MATCH (n)-[r]->() WHERE n.name='Andres' AND type(r)=~ 'K.*' RETURN r

32 in

MATCH (a) WHERE a.name IN ["Peter", "Tobias"] RETURN a

33
START n=node:nodes(name = "A") RETURN n 
   | Node[0]{name:"A"} 

33 avg

MATCH (n:Person) RETURN avg(n.property)

34 The 40th percentile of the values in the property property is returned by the example query, calculated with
a weighted average.

MATCH (n:Person) RETURN percentileCont(n.property, 0.4) 

35  Import data from a CSV file

LOAD CSV FROM 'http://neo4j.com/docs/3.0.1/csv/artists.csv' AS line CREATE (:Artist
{ name: line[1], year: toInt(line[2])})   

36删除所有节点： 

match (n:Entity) -[f]-(p:Entity)  delete f,n,p