initial version of LPA

Author: haroldsultan

graphx/src/main/scala/org/apache/spark/graphx/lib/LPA.scala

@@ -0,0 +1,65 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.graphx.lib
+
+import scala.reflect.ClassTag
+import org.apache.spark.graphx._
+
+/** LPA algorithm. */
+object LPA {
+  /**
+   * Run LPA (label propogation algorithm) for detecting communities in networks using the pregel framework.
+   * 
+   * Each node in the network is initially assigned to its own community.  At every super step 
+   * nodes send their community affiliation to all neighbors and update their state to the mode 
+   * community affiliation of incomming messages.  
+   *
+   * LPA is a standard community detection algorithm for graphs.  It is very inexpensive 
+   * computationally, although (1) convergence is not guaranteed and (2) one can end up with
+   * trivial solutions (all nodes are identified into a single community).
+   *
+   * @tparam VD the vertex attribute type (discarded in the computation)
+   * @tparam ED the edge attribute type (not used in the computation)
+   *
+   * @param graph the graph for which to compute the community affiliation
+   * @param maxSteps the number of supersteps of LPA to be performed
+   *
+   * @return a graph with vertex attributes containing the label of community affiliation
+   */
+  def run[VD: ClassTag, ED: ClassTag](graph: Graph[VD, ED], maxSteps: Int): Graph[VertexId, Long]{
+    val lpaGraph = graph.mapVertices { case (vid, _) => vid }
+    def sendMessage(edge: EdgeTriplet[VertexId, ED]) = {
+      Iterator((e.srcId, Map(e.dstAttr -> 1L)),(e.dstId, Map(e.srcAttr -> 1L)))
+    }
+    def mergeMessage(count1: Map[VertexId, Long], count2: Map[VertexId, Long]): Map[VertexId, Long] = {
+      (count1.keySet ++ count2.keySet).map { i =>
+        val count1Val = count1.getOrElse(i,0L)
+        val count2Val = count2.getOrElse(i,0L)
+	i -> (count1Val +count2Val)
+	}.toMap
+    }
+    def vertexProgram(vid: VertexId, attr: Long, message: Map[VertexId, Long])={
+      if (message.isEmpty) attr else message.maxBy{_._2}._1),
+    }
+    val initialMessage = Map[VertexId,Long]()
+    Pregel(lpaGraph, initialMessage, maxIterations = maxSteps)(
+      vprog = vertexProgram,
+      sendMsg = sendMessage,
+      mergeMsg = mergeMessage)
+  }
+}