246 lines
5.2 KiB
Markdown
246 lines
5.2 KiB
Markdown
Neo4j 备忘清单
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===
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这个 [neo4j](https://neo4j.com/docs/) 快速参考备忘单显示了它的常用命令
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入门
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---
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### Neo4J 安装
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当开始使用 Neo4j 时，首先需要从[官网下载页面](https://neo4j.com/download/)下载 Neo4j。Neo4j 分为社区版和企业版。尽管企业版在横向扩展、权限控制、运行性能和高可用性等方面更优秀，适合正式的生产环境，但对于普通的学习和开发，免费的社区版就足够了。
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#### 运行
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```shell
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$ bin/neo4j start
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```
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在 Mac 或者 Linux 中，安装好 JDK 后，直接解压下载好的 Neo4j 包，然后运行上面命令即可。
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### Neo4J 使用
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Neo4J 提供了一个用户友好的 web 界面，可以进行各项配置、写入、查询等操作，并且提供了可视化功能。类似ElasticSearch 一样，我个人非常喜欢这种开箱即用的设计。
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#### 进入管理页面
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打开浏览器，输入下面网址，可以进入管理页面
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```url
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http://127.0.0.1:7474/browser/
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```
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Neo4j 示例
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---
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### 创建
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创建多个节点
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```cypher
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CREATE (n:Person {name:'Sally'}) RETURN n;
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CREATE (n:Person {name:'Steve'}) RETURN n;
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```
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创建 `FRIENDS` 关系
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```cypher
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MATCH (a:Person {name:'Sally'}),
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(b:Person {name:'Steve'})
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MERGE (a)-[:FRIENDS]->(b)
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```
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创建节点的时候就建好 `FRIENDS` 关系
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```cypher
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CREATE (a:Person {name:'Todd'})-[r:FRIENDS]->(b:Person {name:'Carlos'})
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```
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为创建完成的关系增加 `since` 属性
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```cypher
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MATCH (a:Person {name:'Sally'}),
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(b:Person {name:'Steve'})
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MERGE (a)-[:FRIENDS {since:2001}]->(b)
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```
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### 删除
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<!--rehype:wrap-class=col-span-2-->
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删除所有节点
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```cypher
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MATCH (n) DETACH DELETE n
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```
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删除 `Person`中 `name`为 `Mike`节点的 `test`属性
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```cypher
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MATCH (a:Person {name:'Mike'}) SET a.test='test'
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MATCH (a:Person {name:'Mike'}) REMOVE a.test
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```
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删除 `Location` 中 `city` 为 `Portland` 的节点
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```cypher
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MATCH (a:Location {city:'Portland'}) DELETE a
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```
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删除有关系的节点（此处rel是写死的，指的是所有关系）
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```cypher
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MATCH (a:Person {name:'Todd'})-[rel]-(b:Person) DELETE a,b,rel
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```
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### 查询
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<!--rehype:wrap-class=row-span-3-->
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查询所有在 `Boston` 出生的人物
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```cypher
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MATCH (a:Person)-[:BORN_IN]->(b:Location {city:'Boston'}) RETURN a,b
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```
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查询所有对外有关系的节点
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```cypher
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MATCH (a)-->() RETURN a
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```
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查询所有有关系的节点
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```cypher
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MATCH (a)--() RETURN a
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```
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查询所有对外有关系的节点，以及关系类型
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```cypher
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MATCH (a)-[r]->() RETURN a.name, type(r)
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```
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查询所有有结婚关系的节点
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```cypher
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MATCH (n)-[:MARRIED]-() RETURN n
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```
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查找某人的朋友的朋友
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```cypher
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MATCH (a:Person {name:'Mike'})-[r1:FRIENDS]-()-[r2:FRIENDS]-(friend_of_a_friend) RETURN friend_of_a_friend.name AS fofName
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```
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### 创建节点和关系
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<!--rehype:wrap-class=col-span-2-->
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```cypher
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// 创建节点
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CREATE (n:Person {name: 'Alice', age: 30})
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CREATE (n:Person {name: 'Bob', age: 25})
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// 创建关系
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MATCH (alice:Person {name: 'Alice'}), (bob:Person {name: 'Bob'})
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CREATE (alice)-[:FRIENDS]->(bob)
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```
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### 增加/修改节点的属性
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```cypher
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MATCH (a:Person {name:'Liz'}) SET a.age=34
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MATCH (a:Person {name:'Shaw'}) SET a.age=32
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MATCH (a:Person {name:'John'}) SET a.age=44
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MATCH (a:Person {name:'Mike'}) SET a.age=25
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```
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### 查询节点和关系
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<!--rehype:wrap-class=row-span-2-->
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```cypher
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// 查询所有节点和关系
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MATCH (n)
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RETURN n
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// 查询特定节点
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MATCH (n:Person)
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WHERE n.name = 'Alice'
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RETURN n
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// 查询节点的关系
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MATCH (n:Person)-[r]->()
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WHERE n.name = 'Alice'
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RETURN r
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```
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### 更新节点和关系
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```cypher
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// 更新节点属性
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MATCH (n:Person {name: 'Alice'})
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SET n.age = 31
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RETURN n
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// 删除节点
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MATCH (n:Person {name: 'Bob'})
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DELETE n
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```
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### 更复杂的查询
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<!--rehype:wrap-class=col-span-2-->
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```cypher
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// 查找 Alice 的朋友的朋友
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MATCH (alice:Person {name: 'Alice'})-[:FRIENDS]->()-[:FRIENDS]->(fof)
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RETURN fof
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// 查找共同朋友，这里的“,”相当于 AND 条件
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MATCH (alice:Person {name: 'Alice'})-[:FRIENDS]->(friend),
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(bob:Person {name: 'Bob'})-[:FRIENDS]->(friend)
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RETURN friend
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```
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通过观察`John的朋友`看过的电影为`John`推荐电影，并且不再推荐`John`他自己已经看过的电影。
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```cypher
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MATCH (tom:Person {name: "John Johnson"})-[:IS_FRIEND_OF]->(user)-[:HAS_SEEN]->(movie)
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WHERE NOT tom-[:HAS_SEEN]->(movie) RETURN movie.name;
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```
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找出所有标题以`Apollo`开头且发行年份早于`1996`年的电影节点
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```cypher
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MATCH (node:Movie)
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WHERE node.title =~ 'Apollo.*' AND node.released < 1996
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RETURN node
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```
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### 排序&分页
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以电影名字排序，每一网页只显示10部电影，下面的查询返回了第三页（21~30项）。
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```cypher
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match (alice:Person {name: 'Alice'})-[HAS_SEEN]->(movie)
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return movie
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order by movie.name
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skip 20
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limit 10
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```
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### 聚合函数
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计算每一部电影被观看的数量，按数量排序
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```cypher
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match (node:Movie)-[:HAS_BEEN_SEEN]->()
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return node,count(*)
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order by count(*) desc;
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```
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要求`John`所有朋友的平均年龄，可以使用以下查询
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```cypher
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match (node:users{name: "John Johnson"})-[:IS_FRIEND_OF]-(friend)
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where HAS(friend.yearOfBirth)
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return avg(2014-friend.yearOfBirth);
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```
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