GraphX中Pregel单源点最短路径（转）

package myclass.GraphX  
  
import org.apache.spark.graphx._  
import org.apache.spark.SparkContext  
  
// Import random graph generation library  
  
import org.apache.spark.graphx.util.GraphGenerators  
  
/**  
 * Created by jack on 3/4/14.  
 */  
object Pregel {  
    def main(args: Array[String]) {  
        val sc = new SparkContext("local", "pregel test", System.getenv("SPARK_HOME"), SparkContext.jarOfClass(this.getClass))  
        // A graph with edge attributes containing distances  
        //初始化一个随机图，节点的度符合对数正态分布,边属性初始化为1  
        val graph: Graph[Int, Double] =  
            GraphGenerators.logNormalGraph(sc, numVertices = 10).mapEdges(e => e.attr.toDouble)  
graph.edges.foreach(println)  
        val sourceId: VertexId = 4 // The ultimate source  
  
        // Initialize the graph such that all vertices except the root have distance infinity.  
        //初始化各节点到原点的距离  
        val initialGraph = graph.mapVertices((id, _) => if (id == sourceId) 0.0 else Double.PositiveInfinity)  
  
        val sssp = initialGraph.pregel(Double.PositiveInfinity)(  
            // Vertex Program，节点处理消息的函数，dist为原节点属性（Double），newDist为消息类型（Double）  
            (id, dist, newDist) => math.min(dist, newDist),  
  
            // Send Message，发送消息函数，返回结果为（目标节点id，消息（即最短距离））  
            triplet => {  
                if (triplet.srcAttr + triplet.attr < triplet.dstAttr) {  
                    Iterator((triplet.dstId, triplet.srcAttr + triplet.attr))  
                } else {  
                    Iterator.empty  
                }  
            },  
            //Merge Message，对消息进行合并的操作，类似于Hadoop中的combiner  
            (a, b) => math.min(a, b)  
        )  
  
        println(sssp.vertices.collect.mkString("\n"))  
    }  
}