最近，我阅读了Michal Bachman关于 Neo4j中双向关系的文章 ，他建议对于某些关系类型，我们对关系的方向不那么感兴趣，因此可以在查询时忽略它。 他使用以下示例显示了Neo Technology和GraphAware之间的合作关系：

两家公司都是彼此的合作伙伴，但是由于我们可以尽快找到传入和传出的关系，因此我们最好在两家公司/节点之间只有一种关系。

当我们想使图中的隐式关系明确时，经常会出现这种模式。 例如，我们可能有以下图形描述了他们所从事的人员和项目：

我们可以使用以下密码语法在Neo4j 2.0中创建该图：

CREATE (mark:Person {name: "Mark"})
CREATE (dave:Person {name: "Dave"})
CREATE (john:Person {name: "John"})CREATE (projectA:Project {name: "Project A"})
CREATE (projectB:Project {name: "Project B"})
CREATE (projectC:Project {name: "Project C"})CREATE (mark)-[:WORKED_ON]->(projectA)
CREATE (mark)-[:WORKED_ON]->(projectB)
CREATE (dave)-[:WORKED_ON]->(projectA)
CREATE (dave)-[:WORKED_ON]->(projectC)
CREATE (john)-[:WORKED_ON]->(projectC)
CREATE (john)-[:WORKED_ON]->(projectB)

如果我们想弄清楚哪些人彼此认识，我们可以编写以下查询：

MATCH (person1:Person)-[:WORKED_ON]-()<-[:WORKED_ON]-(person2)
RETURN person1, person2==> +-------------------------------------------------------+
==> | person1                   | person2                   |
==> +-------------------------------------------------------+
==> | Node[500363]{name:"Mark"} | Node[500364]{name:"Dave"} |
==> | Node[500363]{name:"Mark"} | Node[500365]{name:"John"} |
==> | Node[500364]{name:"Dave"} | Node[500363]{name:"Mark"} |
==> | Node[500364]{name:"Dave"} | Node[500365]{name:"John"} |
==> | Node[500365]{name:"John"} | Node[500364]{name:"Dave"} |
==> | Node[500365]{name:"John"} | Node[500363]{name:"Mark"} |
==> +-------------------------------------------------------+
==> 6 rows

我们可能要在每对人之间创建一个KNOWS关系：

MATCH (person1:Person)-[:WORKED_ON]-()<-[:WORKED_ON]-(person2)
CREATE UNIQUE (person1)-[:KNOWS]->(person2)
RETURN person1, person2

现在，如果我们运行一个查询（忽略关系方向）以找出哪些人彼此认识，我们将得到很多重复的结果：

MATCH path=(person1:Person)-[:KNOWS]-(person2)
RETURN person1, person2, path==> +--------------------------------------------------------------------------------------------------------------------------------+
==> | person1                   | person2                   | path                                                                   |
==> +--------------------------------------------------------------------------------------------------------------------------------+
==> | Node[500363]{name:"Mark"} | Node[500364]{name:"Dave"} | [Node[500363]{name:"Mark"},:KNOWS[528536]{},Node[500364]{name:"Dave"}] |
==> | Node[500363]{name:"Mark"} | Node[500365]{name:"John"} | [Node[500363]{name:"Mark"},:KNOWS[528537]{},Node[500365]{name:"John"}] |
==> | Node[500363]{name:"Mark"} | Node[500364]{name:"Dave"} | [Node[500363]{name:"Mark"},:KNOWS[528538]{},Node[500364]{name:"Dave"}] |
==> | Node[500363]{name:"Mark"} | Node[500365]{name:"John"} | [Node[500363]{name:"Mark"},:KNOWS[528541]{},Node[500365]{name:"John"}] |
==> | Node[500364]{name:"Dave"} | Node[500363]{name:"Mark"} | [Node[500364]{name:"Dave"},:KNOWS[528538]{},Node[500363]{name:"Mark"}] |
==> | Node[500364]{name:"Dave"} | Node[500365]{name:"John"} | [Node[500364]{name:"Dave"},:KNOWS[528539]{},Node[500365]{name:"John"}] |
==> | Node[500364]{name:"Dave"} | Node[500363]{name:"Mark"} | [Node[500364]{name:"Dave"},:KNOWS[528536]{},Node[500363]{name:"Mark"}] |
==> | Node[500364]{name:"Dave"} | Node[500365]{name:"John"} | [Node[500364]{name:"Dave"},:KNOWS[528540]{},Node[500365]{name:"John"}] |
==> | Node[500365]{name:"John"} | Node[500364]{name:"Dave"} | [Node[500365]{name:"John"},:KNOWS[528540]{},Node[500364]{name:"Dave"}] |
==> | Node[500365]{name:"John"} | Node[500363]{name:"Mark"} | [Node[500365]{name:"John"},:KNOWS[528541]{},Node[500363]{name:"Mark"}] |
==> | Node[500365]{name:"John"} | Node[500363]{name:"Mark"} | [Node[500365]{name:"John"},:KNOWS[528537]{},Node[500363]{name:"Mark"}] |
==> | Node[500365]{name:"John"} | Node[500364]{name:"Dave"} | [Node[500365]{name:"John"},:KNOWS[528539]{},Node[500364]{name:"Dave"}] |
==> +--------------------------------------------------------------------------------------------------------------------------------+
==> 12 rows

每对人出现4次，如果我们以Mark和Dave为例，我们可以看到原因：

MATCH path=(person1:Person)-[:KNOWS]-(person2)
WHERE person1.name = "Mark" AND person2.name = "Dave"
RETURN person1, person2, path==> +--------------------------------------------------------------------------------------------------------------------------------+
==> | person1                   | person2                   | path                                                                   |
==> +--------------------------------------------------------------------------------------------------------------------------------+
==> | Node[500363]{name:"Mark"} | Node[500364]{name:"Dave"} | [Node[500363]{name:"Mark"},:KNOWS[528536]{},Node[500364]{name:"Dave"}] |
==> | Node[500363]{name:"Mark"} | Node[500364]{name:"Dave"} | [Node[500363]{name:"Mark"},:KNOWS[528538]{},Node[500364]{name:"Dave"}] |
==> +--------------------------------------------------------------------------------------------------------------------------------+
==> 2 rows

如果我们看一下路径栏下有两个不同的KNOWS关系（与IDS 528536和528538），马克和戴夫，一个去之间从马克戴夫和其他来自Dave马克。

正如Michal在他的帖子中指出的那样，在这种情况下，不需要两个关系。 我们只需要一种关系，可以通过创建KNOWS关系时不指定方向来实现：

MATCH (person1:Person)-[:WORKED_ON]-()<-[:WORKED_ON]-(person2)
CREATE UNIQUE (person1)-[:KNOWS]-(person2)
RETURN person1, person2

现在，如果我们重新运行查询以检查Mark和Dave之间的关系，则只有一个：

MATCH path=(person1:Person)-[:KNOWS]-(person2) WHERE person1.name = "Mark" AND person2.name = "Dave" RETURN person1, person2, path==> +--------------------------------------------------------------------------------------------------------------------------------+
==> | person1                   | person2                   | path                                                                   |
==> +--------------------------------------------------------------------------------------------------------------------------------+
==> | Node[500375]{name:"Mark"} | Node[500376]{name:"Dave"} | [Node[500375]{name:"Mark"},:KNOWS[528560]{},Node[500376]{name:"Dave"}] |
==> +--------------------------------------------------------------------------------------------------------------------------------+
==> 1 row

在这种情况下，关系从Mark到Dave，可以通过执行一些考虑方向的查询来看到：

MATCH path=(person1:Person)-[:KNOWS]->(person2)
WHERE person1.name = "Mark" AND person2.name = "Dave"
RETURN person1, person2, path==> +--------------------------------------------------------------------------------------------------------------------------------+
==> | person1                   | person2                   | path                                                                   |
==> +--------------------------------------------------------------------------------------------------------------------------------+
==> | Node[500375]{name:"Mark"} | Node[500376]{name:"Dave"} | [Node[500375]{name:"Mark"},:KNOWS[528560]{},Node[500376]{name:"Dave"}] |
==> +--------------------------------------------------------------------------------------------------------------------------------+
==> 1 row

MATCH path=(person1:Person)<-[:KNOWS]-(person2)
WHERE person1.name = "Mark" AND person2.name = "Dave"
RETURN person1, person2, path==> +--------------------------+
==> | person1 | person2 | path |
==> +--------------------------+
==> +--------------------------+
==> 0 row

翻译自: https://www.javacodegeeks.com/2013/10/neo4j-making-implicit-relationships-explicit-bidirectional-relationships.html