I've created a directed graph, using graphx.
#src->dest
a -> b 34
a -> c 23
b -> e 10
c -> d 12
d -> c 12
c -> d 11
I want to get all two hop neighbors like this:
a -> e 44
a -> d 34
My graph is very large, so I would like to do it elegantly and efficiently. Does anyone have any advice on what will be the best way to do that over a graph instance?
You can succinctly express this using GraphFrames library. First you have to include required package. For with Spark 2.0 and Scala 2.11 you can add
graphframes:graphframes:0.2.0-spark2.0-s_2.11
to spark.jars.packages in conf/spark-defaults.conf or pass it as --packages argument for spark-submit.
Next you should convert Graph to GraphFrame. You can use fromGraphX method:
import org.graphframes.GraphFrame
import org.apache.spark.graphx._
val nodes = sc.parallelize(Seq(
(1L, "a"), (2L, "b"), (3L, "c"), (4L, "d"), (5L, "e")))
val edges = sc.parallelize(Seq(
Edge(1L, 2L, 34), Edge(1L, 3L, 23), Edge(2L, 5L, 10),
Edge(3L, 4L, 12), Edge(3L, 3L, 12), Edge(3L, 5L, 11)))
val graph = Graph(nodes, edges)
val graphFrame = GraphFrame.fromGraphX(graph)
GraphFrame provides find method which takes a pattern in a language similar to Cypher. Two-hops can be expressed as:
val pattern = "(x1) - [a] -> (x2); (x2) - [b] -> (x3)"
where (_) represents nodes, and [_] edges. You paths matching the pattern:
val paths = graphFrame.find(pattern)
and select fields:
paths.select($"x1.attr", $"x3.attr", $"a.attr" + $"b.attr").show()
