在Neo4j中查找集群

嗨，我有一个neo4j数据库，类似于下面的

CREATE
  (:Person {name: 'Ryan'})-[:TRADES]->(fish:Product {name: 'Fish'}),
  (ken:Person {name: 'Ken'})-[:TRADES]->(fish),
  (mary:Person {name: 'Mary'})-[:TRADES]->(fish),
  (john:Person {name: 'John'})-[:TRADES]->(fish),
  (ken)-[:TRADES]->(book:Product {name: 'Book'}),
  (ken)-[:TRADES]->(plum:Product {name: 'Plum'}),
  (ken)-[:TRADES]->(cabbage:Product {name: 'Cabbage'}),
  (ken)-[:TRADES]->(tomato:Product {name: 'Tomato'}),
  (ken)-[:TRADES]->(pineapple:Product {name: 'Pineapple'}),
  (mary)-[:TRADES]->(Pizza:Product {name: 'Pizza'}),
  (mary)-[:TRADES]->(book),
  (mary)-[:TRADES]->(plum),
  (mary)-[:TRADES]->(cabbage),
  (mary)-[:TRADES]->(tomato),
  (ian:Person {name: 'Ian'})-[:TRADES]->(fish),
  (ian)-[:TRADES]->(pork:Product {name: 'Pork'}),
  (john)-[:TRADES]->(pork),
  (ian)-[:TRADES]->(oil:Product {name: 'Oil'}),
  (ian)-[:TRADES]->(pasta:Product {name: 'Pasta'}),
  (ian)-[:TRADES]->(rice:Product {name: 'Rice'}),
  (ian)-[:TRADES]->(milk:Product {name: 'Milk'}),
  (ian)-[:TRADES]->(orange:Product {name: 'Orange'}),
  (john)-[:TRADES]->(oil),
  (john)-[:TRADES]->(rice),
  (john)-[:TRADES]->(pasta),
  (john)-[:TRADES]->(orange),
  (john)-[:TRADES]->(milk),
  (peter:Person {name: 'Peter'})-[:TRADES]->(rice),
  (peter)-[:TRADES]->(pasta),
  (peter)-[:TRADES]->(orange),
  (peter)-[:TRADES]->(oil),
  (peter)-[:TRADES]->(milk),
  (peter)-[:TRADES]->(apple:Product {name: 'Apple'}),
  (ian)-[:TRADES]->(apple);

我想询问购买5件或更多相同物品的人的姓名。（在本例中，第一组是彼得、约翰和伊恩，第二组是肯和玛丽）。对所有可能的项目进行检查

[已编辑] 增加欲望输出

我的愿望输出类似于下面

1。第一个问题的答案 1.1创建图形 为了便于进一步回答和解决问题，我注意到我的图表创建声明：

CREATE
  (:Person {name: 'Ryan'})-[:TRADES]->(fish:Product {name: 'Fish'}),
  (:Person {name: 'Ken'})-[:TRADES]->(fish),
  (:Person {name: 'Mary'})-[:TRADES]->(fish),
  (john:Person {name: 'John'})-[:TRADES]->(fish),
  (ian:Person {name: 'Ian'})-[:TRADES]->(fish),
  (ian)-[:TRADES]->(pork:Product {name: 'Pork'}),
  (john)-[:TRADES]->(pork),
  (ian)-[:TRADES]->(oil:Product {name: 'Oil'}),
  (ian)-[:TRADES]->(pasta:Product {name: 'Pasta'}),
  (ian)-[:TRADES]->(rice:Product {name: 'Rice'}),
  (ian)-[:TRADES]->(milk:Product {name: 'Milk'}),
  (ian)-[:TRADES]->(orange:Product {name: 'Orange'}),
  (john)-[:TRADES]->(oil),
  (john)-[:TRADES]->(rice),
  (john)-[:TRADES]->(pasta),
  (john)-[:TRADES]->(orange),
  (john)-[:TRADES]->(milk),
  (peter:Person {name: 'Peter'})-[:TRADES]->(rice),
  (peter)-[:TRADES]->(pasta),
  (peter)-[:TRADES]->(orange),
  (peter)-[:TRADES]->(oil),
  (peter)-[:TRADES]->(milk),
  (peter)-[:TRADES]->(apple:Product {name: 'Apple'}),
  (ian)-[:TRADES]->(apple);

1.2解决办法

• 第一行：定义匹配模式
• 第二行：计算每人的产品数量
• 第三行：带出产品数量的过滤器
• 第四行：渲染结果

1.3结果

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2.回答新问题和要求 2.1解决方案 2.3注

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显示的结果与您的预期略有不同，因为对于关系

Ian->ApplePorkFishHi，感谢您的回答，但是，如果我想为购买任意5件相同商品的人找到交叉点，我将向您表示感谢。是否可以查询人员和项目节点？（在本例中，是Ian、John和Peter，项目包括大米、橙子、意大利面、牛奶和油？）嗨@口渴者感谢我更新了我的问题。谢谢你，我用两种不同的解决方案（第二章和第三章）扩展了我的答案。谢谢你的帮助！不过，我有两个跟进问题。1.）是否可以在解决方案2中显示节点？2.）当我将解决方案3放入实际数据集中时，产品列表中的某些行少于5行。是否可以将产品列表的长度限制为至少5种产品？再次感谢你的帮助是的。如果删除第二行中的
.name
部分以及最后一行中出现的两个部分，您将获得节点。
MATCH (person:Person)-[:TRADES]->(product:Product)
WITH person.name AS personName, count(product) AS amount
WHERE amount >=5
RETURN personName, amount;

╒════════════╤════════╕
│"personName"│"amount"│
╞════════════╪════════╡
│"John"      │7       │
├────────────┼────────┤
│"Ian"       │8       │
├────────────┼────────┤
│"Peter"     │6       │
└────────────┴────────┘

MATCH path=(sourcePerson:Person)-[:TRADES]->(product:Product)<-[:TRADES]-(targetPerson:Person)
WITH sourcePerson, targetPerson, count(path) AS pathAmount, collect(product.name) AS products
  WHERE pathAmount >= 5 AND id(sourcePerson) > id(targetPerson)
RETURN DISTINCT products, collect(sourcePerson.name) AS sourcePersons, collect(targetPerson.name) AS targetPersons;

╒════════════════════════════════════════════════════╤═══════════════╤═══════════════╕
│"products"                                          │"sourcePersons"│"targetPersons"│
╞════════════════════════════════════════════════════╪═══════════════╪═══════════════╡
│["Tomato","Cabbage","Plum","Book","Fish"]           │["Mary"]       │["Ken"]        │
├────────────────────────────────────────────────────┼───────────────┼───────────────┤
│["Milk","Orange","Pasta","Rice","Oil"]              │["Peter"]      │["John"]       │
├────────────────────────────────────────────────────┼───────────────┼───────────────┤
│["Milk","Orange","Pasta","Rice","Oil","Pork","Fish"]│["Ian"]        │["John"]       │
├────────────────────────────────────────────────────┼───────────────┼───────────────┤
│["Apple","Orange","Milk","Rice","Pasta","Oil"]      │["Peter"]      │["Ian"]        │
└────────────────────────────────────────────────────┴───────────────┴───────────────┘

CALL algo.louvain.stream('', '', {})
YIELD nodeId, community
WITH algo.getNodeById(nodeId) AS node, community
  ORDER BY community
WITH community, collect(node) AS nodes
WITH
  community,
  [x IN nodes WHERE ('Person' IN labels(x)) | x.name] AS persons,
  [x IN nodes WHERE ('Product' IN labels(x)) | x.name] AS products
RETURN community, persons, products;

╒═══════════╤══════════════════════╤═════════════════════════════════════════════════════════════╕
│"community"│"persons"             │"products"                                                   │
╞═══════════╪══════════════════════╪═════════════════════════════════════════════════════════════╡
│0          │["Ryan","Ken","Mary"] │["Fish","Book","Plum","Cabbage","Tomato","Pineapple","Pizza"]│
├───────────┼──────────────────────┼─────────────────────────────────────────────────────────────┤
│1          │["John","Ian","Peter"]│["Pork","Oil","Pasta","Rice","Milk","Orange","Apple"]        │
└───────────┴──────────────────────┴─────────────────────────────────────────────────────────────┘