Spark组件之GraphX学习16–最短路径ShortestPaths

更多代码请见:​​https://github.com/xubo245/SparkLearning​​

1解释

求图中的最短路径,更多的请见参考【3】,这篇写的很详细

2.代码:

/**
* @author xubo
* ref http://.graphx.learning

import org.apache.spark.SparkConf
import org.apache.spark.SparkContext
import org.apache.spark.graphx.Graph
import org.apache.spark.graphx.Graph.graphToGraphOps
import org.apache.spark.graphx.lib.ShortestPaths

object ShortPaths {

def main(args: Array[String]): Unit = {
val conf = new SparkConf().setAppName("ShortPaths").setMaster("local[4]")
val sc = new SparkContext(conf)

// 测试的真实结果,后面用于对比
val shortestPaths = Set(
(1, Map(1 -> 0, 4 -> 2)), (2, Map(1 -> 1, 4 -> 2)), (3, Map(1 -> 2, 4 -> 1)),
(4, Map(1 -> 2, 4 -> 0)), (5, Map(1 -> 1, 4 -> 1)), (6, Map(1 -> 3, 4 -> 1)))

// 构造无向图的边序列
val edgeSeq = Seq((1, 2), (1, 5), (2, 3), (2, 5), (3, 4), (4, 5), (4, 6)).flatMap {
case e => Seq(e, e.swap)
}

// 构造无向图
val edges = sc.parallelize(edgeSeq).map { case (v1, v2) => (v1.toLong, v2.toLong) }
val graph = Graph.fromEdgeTuples(edges, 1)

// 要求最短路径的点集合
val landmarks = Seq(1, 4).map(_.toLong)

// 计算get="_blank">最短路径
val results = ShortestPaths.run(graph, landmarks).vertices.collect.map {
case (v, spMap) => (v, spMap.mapValues(i => i))
}

val shortestPath1 = ShortestPaths.run(graph, landmarks)
// 与真实结果对比
println("\ngraph edges");
println("edges:");
graph.edges.collect.foreach(println)
// graph.edges.collect.foreach(println)
println("vertices:");
graph.vertices.collect.foreach(println)
// println("triplets:");
// graph.triplets.collect.foreach(println)
println();

println("\n shortestPath1");
println("edges:");
shortestPath1.edges.collect.foreach(println)
println("vertices:");
shortestPath1.vertices.collect.foreach(println)
// println("vertices:")

assert(results.toSet == shortestPaths)
println("results.toSet:" + results.toSet);
println("end");

sc.stop()
}
}

图分析:其实是无向图,但是存储的时候GraphX存的是有向图

3.结果:

分析:返回的是

(1,Map(1 -> 0, 4 -> 2))
(5,Map(1 -> 1, 4 -> 1))
(6,Map(4 -> 1, 1 -> 3))

节点的属性存的是到某几点的最短路径,比如

(1,Map(1 -> 0, 4 -> 2))

表明的是1节点到1节点路径为0,到4节点为2

同理

(6,Map(4 -> 1, 1 -> 3))

6号节点到4为1,到1为3,途中可以看得出来

全部结果:

graph edges
edges:
Edge(1,2,1)
Edge(1,5,1)
Edge(2,1,1)
Edge(2,3,1)
Edge(2,5,1)
Edge(3,2,1)
Edge(5,1,1)
Edge(3,4,1)
Edge(4,3,1)
Edge(5,2,1)
Edge(4,5,1)
Edge(4,6,1)
Edge(5,4,1)
Edge(6,4,1)
vertices:
(4,1)
(1,1)
(5,1)
(6,1)
(2,1)
(3,1)


shortestPath1
edges:
Edge(1,2,1)
Edge(1,5,1)
Edge(2,1,1)
Edge(2,3,1)
Edge(2,5,1)
Edge(3,2,1)
Edge(5,1,1)
Edge(3,4,1)
Edge(4,3,1)
Edge(5,2,1)
Edge(4,5,1)
Edge(4,6,1)
Edge(5,4,1)
Edge(6,4,1)
vertices:
(4,Map(4 -> 0, 1 -> 2))
(1,Map(1 -> 0, 4 -> 2))
(5,Map(1 -> 1, 4 -> 1))
(6,Map(4 -> 1, 1 -> 3))
(2,Map(1 -> 1, 4 -> 2))
(3,Map(4 -> 1, 1 -> 2))
results.toSet:Set((1,Map(1 -> 0, 4 -> 2)), (5,Map(1 -> 1, 4 -> 1)), (2,Map(1 -> 1, 4 -> 2)), (6,Map(4 -> 1, 1 -> 3)), (4,Map(4 -> 0, 1 -> 2)), (3,Map(4 -> 1, 1 -> 2)))
end

如果改为全部节点,则为:

vertices:
(4,Map(5 -> 1, 1 -> 2, 6 -> 1, 2 -> 2, 3 -> 1, 4 -> 0))
(1,Map(5 -> 1, 1 -> 0, 6 -> 3, 2 -> 1, 3 -> 2, 4 -> 2))
(5,Map(5 -> 0, 1 -> 1, 6 -> 2, 2 -> 1, 3 -> 2, 4 -> 1))
(6,Map(5 -> 2, 1 -> 3, 6 -> 0, 2 -> 3, 3 -> 2, 4 -> 1))
(2,Map(5 -> 1, 1 -> 1, 6 -> 3, 2 -> 0, 3 -> 1, 4 -> 2))
(3,Map(5 -> 2, 1 -> 2, 6 -> 2, 2 -> 1, 3 -> 0, 4 -> 1))
results.toSet:Set((6,Map(5 -> 2, 1 -> 3, 6 -> 0, 2 -> 3, 3 -> 2, 4 -> 1)), (4,Map(5 -> 1, 1 -> 2, 6 -> 1, 2 -> 2, 3 -> 1, 4 -> 0)), (3,Map(5 -> 2, 1 -> 2, 6 -> 2, 2 -> 1, 3 -> 0, 4 -> 1)), (2,Map(5 -> 1, 1 -> 1, 6 -> 3, 2 -> 0, 3 -> 1, 4 -> 2)), (1,Map(5 -> 1, 1 -> 0, 6 -> 3, 2 -> 1, 3 -> 2, 4 -> 2)), (5,Map(5 -> 0, 1 -> 1, 6 -> 2, 2 -> 1, 3 -> 2, 4 -> 1)))

参考

【1】http://spark.apache.org/docs/1.5.2/graphx-programming-guide.html

【2】​​https://github.com/xubo245/SparkLearning​​