直接上代码：
1 package horizon.graphx.util
2
3 import java.security.InvalidParameterException
4
5 import horizon.graphx.util.CollectionUtil.CollectionHelper
6 import org.apache.spark.graphx._
7 import org.apache.spark.rdd.RDD
8 import org.apache.spark.storage.StorageLevel
9
10 import scala.collection.mutable.ArrayBuffer
11 import scala.reflect.ClassTag
12
13 /**
14 * Created by yepei.ye on 2017/1/19.
15 * Description:用于在图中为指定的节点计算这些节点的N度关系节点，输出这些节点与源节点的路径长度和节点id
16 */
17 object GraphNdegUtil {
18 val maxNDegVerticesCount = 10000
19 val maxDegree = 1000
20
21 /**
22 * 计算节点的N度关系
23 *
24 * @param edges
25 * @param choosedVertex
26 * @param degree
27 * @tparam ED
28 * @return
29 */
30 def aggNdegreedVertices[ED: ClassTag](edges: RDD[(VertexId, VertexId)], choosedVertex: RDD[VertexId], degree: Int): VertexRDD[Map[Int, Set[VertexId]]] = {
31 val simpleGraph = Graph.fromEdgeTuples(edges, 0, Option(PartitionStrategy.EdgePartition2D), StorageLevel.MEMORY_AND_DISK_SER, StorageLevel.MEMORY_AND_DISK_SER)
32 aggNdegreedVertices(simpleGraph, choosedVertex, degree)
33 }
34
35 def aggNdegreedVerticesWithAttr[VD: ClassTag, ED: ClassTag](graph: Graph[VD, ED], choosedVertex: RDD[VertexId], degree: Int, sendFilter: (VD, VD) => Boolean = (_: VD, _: VD) => true): VertexRDD[Map[Int, Set[VD]]] = {
36 val ndegs: VertexRDD[Map[Int, Set[VertexId]]] = aggNdegreedVertices(graph, choosedVertex, degree, sendFilter)
37 val flated: RDD[Ver[VD]] = ndegs.flatMap(e => e._2.flatMap(t => t._2.map(s => Ver(e._1, s, t._1, null.asInstanceOf[VD])))).persist(StorageLevel.MEMORY_AND_DISK_SER)
38 val matched: RDD[Ver[VD]] = flated.map(e => (e.id, e)).join(graph.vertices).map(e => e._2._1.copy(attr = e._2._2)).persist(StorageLevel.MEMORY_AND_DISK_SER)
39 flated.unpersist(blocking = false)
40 ndegs.unpersist(blocking = false)
41 val grouped: RDD[(VertexId, Map[Int, Set[VD]])] = matched.map(e => (e.source, ArrayBuffer(e))).reduceByKey(_ ++= _).map(e => (e._1, e._2.map(t => (t.degree, Set(t.attr))).reduceByKey(_ ++ _).toMap))
42 matched.unpersist(blocking = false)
43 VertexRDD(grouped)
44 }
45
46 def aggNdegreedVertices[VD: ClassTag, ED: ClassTag](graph: Graph[VD, ED],
47 choosedVertex: RDD[VertexId],
48 degree: Int,
49 sendFilter: (VD, VD) => Boolean = (_: VD, _: VD) => true
50 ): VertexRDD[Map[Int, Set[VertexId]]] = {
51 if (degree < 1) {
52 throw new InvalidParameterException("度参数错误:" + degree)
53 }
54 val initVertex = choosedVertex.map(e => (e, true)).persist(StorageLevel.MEMORY_AND_DISK_SER)
55 var g: Graph[DegVertex[VD], Int] = graph.outerJoinVertices(graph.degrees)((_, old, deg) => (deg.getOrElse(0), old))
56 .subgraph(vpred = (_, a) => a._1 <= maxDegree)
57 //去掉大节点
58 .outerJoinVertices(initVertex)((id, old, hasReceivedMsg) => {
59 DegVertex(old._2, hasReceivedMsg.getOrElse(false), ArrayBuffer((id, 0))) //初始化要发消息的节点
60 }).mapEdges(_ => 0).cache() //简化边属性
61
62 choosedVertex.unpersist(blocking = false)
63
64 var i = 0
65 var prevG: Graph[DegVertex[VD], Int] = null
66 var newVertexRdd: VertexRDD[ArrayBuffer[(VertexId, Int)]] = null
67 while (i < degree + 1) {
68 prevG = g
69 //发第i+1轮消息
70 newVertexRdd = prevG.aggregateMessages[ArrayBuffer[(VertexId, Int)]](sendMsg(_, sendFilter), (a, b) => reduceVertexIds(a ++ b)).persist(StorageLevel.MEMORY_AND_DISK_SER)
71 g = g.outerJoinVertices(newVertexRdd)((vid, old, msg) => if (msg.isDefined) updateVertexByMsg(vid, old, msg.get) else old.copy(init = false)).cache()
72 prevG.unpersistVertices(blocking = false)
73 prevG.edges.unpersist(blocking = false)
74 newVertexRdd.unpersist(blocking = false)
75 i += 1
76 }
77 newVertexRdd.unpersist(blocking = false)
78
79 val maped = g.vertices.join(initVertex).mapValues(e => sortResult(e._1)).persist(StorageLevel.MEMORY_AND_DISK_SER)
80 initVertex.unpersist()
81 g.unpersist(blocking = false)
82 VertexRDD(maped)
83 }
84
85 private case class Ver[VD: ClassTag](source: VertexId, id: VertexId, degree: Int, attr: VD = null.asInstanceOf[VD])
86
87 private def updateVertexByMsg[VD: ClassTag](vertexId: VertexId, oldAttr: DegVertex[VD], msg: ArrayBuffer[(VertexId, Int)]): DegVertex[VD] = {
88 val addOne = msg.map(e => (e._1, e._2 + 1))
89 val newMsg = reduceVertexIds(oldAttr.degVertices ++ addOne)
90 oldAttr.copy(init = msg.nonEmpty, degVertices = newMsg)
91 }
92
93 private def sortResult[VD: ClassTag](degs: DegVertex[VD]): Map[Int, Set[VertexId]] = degs.degVertices.map(e => (e._2, Set(e._1))).reduceByKey(_ ++ _).toMap
94
95 case class DegVertex[VD: ClassTag](var attr: VD, init: Boolean = false, degVertices: ArrayBuffer[(VertexId, Int)])
96
97 case class VertexDegInfo[VD: ClassTag](var attr: VD, init: Boolean = false, degVertices: ArrayBuffer[(VertexId, Int)])
98
99 private def sendMsg[VD: ClassTag](e: EdgeContext[DegVertex[VD], Int, ArrayBuffer[(VertexId, Int)]], sendFilter: (VD, VD) => Boolean): Unit = {
100 try {
101 val src = e.srcAttr
102 val dst = e.dstAttr
103 //只有dst是ready状态才接收消息
104 if (src.degVertices.size < maxNDegVerticesCount && (src.init || dst.init) && dst.degVertices.size < maxNDegVerticesCount && !isAttrSame(src, dst)) {
105 if (sendFilter(src.attr, dst.attr)) {
106 e.sendToDst(reduceVertexIds(src.degVertices))
107 }
108 if (sendFilter(dst.attr, dst.attr)) {
109 e.sendToSrc(reduceVertexIds(dst.degVertices))
110 }
111 }
112 } catch {
113 case ex: Exception =>
114 println(s"==========error found: exception:${ex.getMessage}," +
115 s"edgeTriplet:(srcId:${e.srcId},srcAttr:(${e.srcAttr.attr},${e.srcAttr.init},${e.srcAttr.degVertices.size}))," +
116 s"dstId:${e.dstId},dstAttr:(${e.dstAttr.attr},${e.dstAttr.init},${e.dstAttr.degVertices.size}),attr:${e.attr}")
117 ex.printStackTrace()
118 throw ex
119 }
120 }
121
122 private def reduceVertexIds(ids: ArrayBuffer[(VertexId, Int)]): ArrayBuffer[(VertexId, Int)] = ArrayBuffer() ++= ids.reduceByKey(Math.min)
123
124 private def isAttrSame[VD: ClassTag](a: DegVertex[VD], b: DegVertex[VD]): Boolean = a.init == b.init && allKeysAreSame(a.degVertices, b.degVertices)
125
126 private def allKeysAreSame(a: ArrayBuffer[(VertexId, Int)], b: ArrayBuffer[(VertexId, Int)]): Boolean = {
127 val aKeys = a.map(e => e._1).toSet
128 val bKeys = b.map(e => e._1).toSet
129 if (aKeys.size != bKeys.size || aKeys.isEmpty) return false
130
131 aKeys.diff(bKeys).isEmpty && bKeys.diff(aKeys).isEmpty
132 }
133 }
其中sortResult方法里对Traversable[(K,V)]类型的集合使用了reduceByKey方法，这个方法是自行封装的，使用时需要导入，代码如下：
/**
* Created by yepei.ye on 2016/12/21.
* Description:
*/
object CollectionUtil {
/**
* 对具有Traversable[(K, V)]类型的集合添加reduceByKey相关方法
*
* @param collection
* @param kt
* @param vt
* @tparam K
* @tparam V
*/
implicit class CollectionHelper[K, V](collection: Traversable[(K, V)])(implicit kt: ClassTag[K], vt: ClassTag[V]) {
def reduceByKey(f: (V, V) => V): Traversable[(K, V)] = collection.groupBy(_._1).map { case (_: K, values: Traversable[(K, V)]) => values.reduce((a, b) => (a._1, f(a._2, b._2))) }
/**
* reduceByKey的同时，返回被reduce掉的元素的集合
*
* @param f
* @return
*/
def reduceByKeyWithReduced(f: (V, V) => V)(implicit kt: ClassTag[K], vt: ClassTag[V]): (Traversable[(K, V)], Traversable[(K, V)]) = {
val reduced: ArrayBuffer[(K, V)] = ArrayBuffer()
val newSeq = collection.groupBy(_._1).map {
case (_: K, values: Traversable[(K, V)]) => values.reduce((a, b) => {
val newValue: V = f(a._2, b._2)
val reducedValue: V = if (newValue == a._2) b._2 else a._2
val reducedPair: (K, V) = (a._1, reducedValue)
reduced += reducedPair
(a._1, newValue)
})
}
(newSeq, reduced.toTraversable)
}
}
}