Scala Spark GraphX：通过在三元组中传递顶点值进行过滤

我正在Windows 10上使用Spark 2.1.0。因为我是Spark的新手，所以我一直在关注这一点

在本教程中，作者使用以下代码打印图形的所有三元组：

graph.triplets.sortBy(_.attr, ascending=false).map(triplet =>
"There were " + triplet.attr.toString + " flights from " + triplet.srcAttr + " to " + triplet.dstAttr + ".").take(10)

问题：我想提供一个输入（例如ATL），我想查看ATL的所有出站航班及其计数，如下所示：

res60: Array[String] = Array(There were 1388 flights from ATL to LAX.,
There were 1330 flights from ATL to SFO., There were 1283 flights from ATL to HNL., 
There were 1205 flights from ATL to BOS., There were 1229 flights from ATL to LGA., 
There were 1214 flights from ATL to OGG., There were 1173 flights from ATL to LAS., 
There were 1157 flights from ATL to SAN.)

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代码如下：

// Selecting the desired airport
val input = "ATL"
// filtering the edges of the desired airport (here "ATL") from the `graph`(which is built on the full data)
val TEMPEdge = graph.edges.filter { case Edge(src, dst, prop) => src == MurmurHash3.stringHash(input) }
// Creating a new graph with the filtered edges
val TEMPGraph = Graph(airportVertices, TEMPEdge, defaultAirport)
// Printing the top 10
TEMPGraph.triplets.sortBy(_.attr, ascending=false).map(triplet => "There were " + triplet.attr.toString + " flights from " + triplet.srcAttr + " to " + triplet.dstAttr + "\n").take(10)

或者，我们可以使用过滤器

graph.triplets.sortBy(_.attr, ascending=false).filter {_.dstAttr == input }.map(triplet => "There were " + triplet.attr.toString + " flights from " + triplet.srcAttr + " to " + triplet.dstAttr + "\n").take(3)