1.图数据库安装与配置

1.1安装与配置

配置path = %NEO4J_HOME%\bin

启动命令：neo4j console

web访问： http://localhost:7474

1.2权限管理

:server change-password 修改密码

:server user list 可视化界面管理用户权限

:server disconnect 退出当前用户

2.从csv导入数据

（1）停掉服务

（2）删除 graph.db 目录

（3）报错，解决办法：将bin/neo4j-import.ps1文件的相对路径改为绝对路径

（4）准备CSV文件。举例如下，记录为电影，明星 以及其中存在的一个扮演角色关系。CSV格式为：

movies.csv

movieId:ID,title,year:int,:LABEL

tt0133093,"The Matrix",1999,Movie

tt0234215,"The Matrix Reloaded",2003,Movie;Sequel

tt0242653,"The Matrix Revolutions",2003,Movie;Sequel

actors.csv

personId:ID,name,:LABEL

keanu,"Keanu Reeves",Actor

laurence,"Laurence Fishburne",Actor

carrieanne,"Carrie-Anne Moss",Actor

roles.csv

:START_ID,role,:END_ID,:TYPE

keanu,"Neo",tt0133093,ACTED_IN

keanu,"Neo",tt0234215,ACTED_IN

keanu,"Neo",tt0242653,ACTED_IN

laurence,"Morpheus",tt0133093,ACTED_IN

laurence,"Morpheus",tt0234215,ACTED_IN

laurence,"Morpheus",tt0242653,ACTED_IN

carrieanne,"Trinity",tt0133093,ACTED_IN

carrieanne,"Trinity",tt0234215,ACTED_IN

carrieanne,"Trinity",tt0242653,ACTED_IN

（5） 导入命令：neo4j-import --into graph.db --nodes <节点1.csv> --nodes <节点2.csv> --relationships <关系.csv>

3.常见的CQL命令

以Movie、Actors、Roles 为例，图形如下：

 

3.1查询

• 查询整个图形

match(n) return n

• 查询year小于2000的电影

match (n)

where n.year < 2000

return n

• 查询带有movie标签的节点

match(n:Movie)

return n

• 查询名字叫Keanu Reeves的演员

match (n{name:'Keanu Reeves'})

return n

• 查询与带Movie标签的节点相关的所有节点

match(n) -- (m:Movie)

return n

• 查询“Keanu Reeves”所有参演过的电影

match (n) -[r:ACTED_IN]-> (m:Movie)

where n.name = 'Keanu Reeves'

return m

match (n{name:'Keanu Reeves'}) -[r:ACTED_IN]-> (m:Movie)

return m

• 查询与“Keanu Reeves”同演过的人

match (a) -[:ACTED_IN]->(m)<-[:ACTED_IN]- (b)

return distinct b

3.2.创建

• 增加拍摄于2010年名叫“super man”的电影

create (n:Movie{title:'super man',year:2010})

return n

• 增加名叫“Jone”的演员

create (n:Actor{name:'Jone'})

return n

• 增加“Jone”和“super man”之间类型为ACTED_IN的关系

match (a{name:'Jone'}),(b{name:'super man'})

create (a) -[r:ACTED_IN]->(b)

return r

3.3更新

• 给“Jone”增加属性age = 40

match(n{name:'Jone'})

set n.age = 40

return n

• 给“super man”增加description = “Hot”

match(n{name:'super man'})

set n.description = 'Hot'

return n

• 给“Jone”和“super man”之间的关系增加description=“first”

match (a{name:'Jone'})-[r]->(b{name:'super man'})

set r.description = 'first'

return r

3.4删除

• 删除id不同，名字相同的重复的演员实体

match (a:Actor),(b:Actor)

where id(a) <> id(b) and a.name = b.name

delete b

return b

3.5函数

• 查询name=“Jone”的节点的ID

match (n{name:'Jone'})

return id(n)

• 查询“Jone”和“super man”之间关系类型

match (a{name:'Jone'})-[r]->(b{name:'super man'})

return type(r)

• 查询name=“Jone”的节点的所有属性名

match (n{name:'Jone'})

return keys(n)

• 查询name=“Jone”的节点的所有属性名及值

match (n{name:'Jone'})

return properties(n)

• 统计带标签“Movie”的节点数量

match (n:Movie)

with count(*) as f

return f

• 给所有节点增加时间戳

match (n)

set n.timestamp = timestamp()

3.6路径

• 查询与“Keanu Reeves”距离1-3度的节点

match (n{name:'Keanu Reeves'}) -[*1..3]- (m)

return m

• 查询“Laurence Fishburne”和“Keanu Reeves”的最短路径

match p = shortestPath ((a{name:'Laurence Fishburne'})-[*]-(b{name:'Keanu Reeves'}))

return p

4.Python实现neo4j的访问

from py2neo import Database, Graph, Node, Relationship

# 建立连接
db = Database("http://127.0.0.1:7474")
graph = Graph("bolt://127.0.0.1:7687", username="neo4j", password="123456")

try:
    for node in graph.nodes:
        print(node)
except:
    print("key error!")
    
# 匹配
n = graph.nodes.match("Keanu Reeves")
for i in n:
    print(i)
try:
    for r in graph.relationships:
        print(r)
except:
    print("key error!")
    
# 提交任务
tx = graph.begin()
a = Node("Actor", name="张鹤伦")
tx.create(a)
b = Node("Actor", name="杨九郎")
ab = Relationship(a, "师兄弟", b)
tx.create(ab)
tx.commit()

# 判断是否存在
isExists = graph.exists(ab)
print("is Exists=" + str(isExists))

# 执行CQL命令
graph.run('create(p:Actor{name:"周九良"})')
ans = graph.run('match(p:Actor) return p.name,p.born').to_ndarray()
print(ans)

参考资料：

  https://segmentfault.com/a/1190000014488430

  https://www.jianshu.com/p/27edc7572193