Spark GraphX 聚合操作

package Spark_GraphXimport org.apache.spark.{SparkConf, SparkContext}
import org.apache.spark.graphx._
import org.apache.spark.graphx.util.GraphGenerators/*** 计算每一个用户的追随者数量和追随者的平均年龄*/
object Graphx_聚合操作 {def main(args: Array[String]): Unit = {val conf=new SparkConf().setAppName("聚合操作").setMaster("local[2]")val sc=new SparkContext(conf)//随机生成具有100个顶点的图,图的结构也随机val graph:Graph[Double,Int]=GraphGenerators.logNormalGraph(sc,numVertices =100).mapVertices((id,_)=>id.toDouble)graph.vertices.foreach(println)graph.edges.foreach(println)val olderFollowers:VertexRDD[(Int,Double)]=graph.aggregateMessages[(Int,Double)](triplet=>{if(triplet.srcAttr>triplet.dstAttr){    //如果源顶点的属性大于目的顶点的属性triplet.sendToDst(1,triplet.srcAttr)   //源-->目的 发送个数1 和源顶点的属性
        }},(a,b)=>(a._1+b._1,a._2+b._2)     //累加统计结果
    )olderFollowers.values.foreach(println)val avgAgeOfOlderFollowers:VertexRDD[Double]=olderFollowers.mapValues((id,value)=>value match {case (count,totalAge)=>totalAge/count})println("*********************")avgAgeOfOlderFollowers.foreach(println)}}

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...........................     省略
...........................     省略
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*********************
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