原创：自定义spark GraphX中的collectNeighborIds方法

/**
  * 自定义收集VertexId的neighborIds
  * @author TongXueQiang
  */
def collectNeighborIds[T,U](edgeDirection:EdgeDirection,graph:Graph[T,U])(implicit m:scala.reflect.ClassTag[T],n:scala.reflect.ClassTag[U]):VertexRDD[Array[VertexId]] = {
  val nbrs = graph.mapReduceTriplets[Array[VertexId]](
    //map函数
    edgeTriplets => {
      val msgTosrc = (edgeTriplets.srcId,Array(edgeTriplets.dstId));
      val msgTodst = (edgeTriplets.dstId,Array(edgeTriplets.srcId));
      edgeDirection match {
        case EdgeDirection.Either =>Iterator(msgTosrc,msgTodst)
        case EdgeDirection.Out => Iterator(msgTosrc)
        case EdgeDirection.In => Iterator(msgTodst)
        case EdgeDirection.Both =>  throw new SparkException("It doesn't make sense to collect neighbors without a " + "direction.(EdgeDirection.Both is not supported.use EdgeDirection.Either instead.)")
      }
    },_ ++ _)//reduce函数
  nbrs
}
测试：
object Test {
　　

　　System.setProperty("hadoop.home.dir","D://hadoop-2.6.2");
　　val conf = new SparkConf().setMaster("local").setAppName("SparkGraph");
　　val sc = new SparkContext(conf);

　　def main(args:Array[String]):Unit = {
　　　　val graph = GraphGenerators.logNormalGraph(sc,numVertices = 100).map((id,_) => id.toDouble);

　　　 collectNeighborIds(EdgeDirection.In,graph).foreach(line => {print(line._1+":"); for (elem <- line._2) {print(elem + " ")};println;});

}



}