Apache spark 火花图-FOF的实现 如何在Spark GraphX中找到FOF？

在Cypher中，我有一个疑问：

MATCH (f:Friend)-[:friend_of]-(Friend)-[:friend_of]-(c:Friend)
WHERE c.name STARTS WITH "T"
RETURN f.name AS Friend1 , c2.name as Friend2

另一个例子来自

基本内容：此查询在返回“John”和找到的任何朋友的朋友之前，先查找一个名为“John”和“John’s”的用户的朋友（尽管不是他的直接朋友）

• Spark GraphX的替代实现是什么
• 如何将此查询实现为Spark GraphX

这是火花图X中的示例：

// Create an RDD for the vertices
val users: RDD[(VertexId, (String, String))] =
  sc.parallelize(Array((3L, ("rxin", "student")), (7L, ("jgonzal", "postdoc")),
                       (5L, ("franklin", "prof")), (2L, ("istoica", "prof")),
                       (4L, ("peter", "student"))))

// Create an RDD for edges
val relationships: RDD[Edge[String]] =
  sc.parallelize(Array(Edge(3L, 7L, "friend_of"),   Edge(5L, 3L, "friend_of"),
                       Edge(2L, 5L, "friend_of"),   Edge(5L, 7L, "friend_of"),
                       Edge(4L, 0L, "friend_of"),   Edge(5L, 0L, "friend_of")))

// Define a default user in case there are relationship with missing user
val defaultUser = ("John Doe", "Missing")

// Build the initial Graph
val graph = Graph(users, relationships, defaultUser)


// Where do we go, Where do we go now..?!

---

我看到的图形中的所有示例都在相同的概念中

Node->Rel->Node

。但是如何做

Node->Rel->Node->Rel->Node

你能详细说明你的

Cypher

查询到底做什么吗？基本上它是什么：我的查询返回所有朋友的朋友，他们的名字以T.dupe开头。对不起，它没有重复，在它只有两个步骤FoF，我需要实现三个步骤FoF。区别在于，图中的所有示例都位于同一个概念节点->关系节点->节点中。但是如何使Node->Rel->Node->Rel->Node具有类似的功能，称为motif finding。

// Create an RDD for the vertices
val users: RDD[(VertexId, (String, String))] =
  sc.parallelize(Array((3L, ("rxin", "student")), (7L, ("jgonzal", "postdoc")),
                       (5L, ("franklin", "prof")), (2L, ("istoica", "prof")),
                       (4L, ("peter", "student"))))

// Create an RDD for edges
val relationships: RDD[Edge[String]] =
  sc.parallelize(Array(Edge(3L, 7L, "friend_of"),   Edge(5L, 3L, "friend_of"),
                       Edge(2L, 5L, "friend_of"),   Edge(5L, 7L, "friend_of"),
                       Edge(4L, 0L, "friend_of"),   Edge(5L, 0L, "friend_of")))

// Define a default user in case there are relationship with missing user
val defaultUser = ("John Doe", "Missing")

// Build the initial Graph
val graph = Graph(users, relationships, defaultUser)


// Where do we go, Where do we go now..?!