
org.apache.spark.examples.graphx.AggregateMessagesExample.scala Maven / Gradle / Ivy
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SnappyData distributed data store and execution engine
/*
* 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.
*/
// scalastyle:off println
package org.apache.spark.examples.graphx
// $example on$
import org.apache.spark.graphx.{Graph, VertexRDD}
import org.apache.spark.graphx.util.GraphGenerators
// $example off$
import org.apache.spark.sql.SparkSession
/**
* An example use the [`aggregateMessages`][Graph.aggregateMessages] operator to
* compute the average age of the more senior followers of each user
* Run with
* {{{
* bin/run-example graphx.AggregateMessagesExample
* }}}
*/
object AggregateMessagesExample {
def main(args: Array[String]): Unit = {
// Creates a SparkSession.
val spark = SparkSession
.builder
.appName(s"${this.getClass.getSimpleName}")
.getOrCreate()
val sc = spark.sparkContext
// $example on$
// Create a graph with "age" as the vertex property.
// Here we use a random graph for simplicity.
val graph: Graph[Double, Int] =
GraphGenerators.logNormalGraph(sc, numVertices = 100).mapVertices( (id, _) => id.toDouble )
// Compute the number of older followers and their total age
val olderFollowers: VertexRDD[(Int, Double)] = graph.aggregateMessages[(Int, Double)](
triplet => { // Map Function
if (triplet.srcAttr > triplet.dstAttr) {
// Send message to destination vertex containing counter and age
triplet.sendToDst(1, triplet.srcAttr)
}
},
// Add counter and age
(a, b) => (a._1 + b._1, a._2 + b._2) // Reduce Function
)
// Divide total age by number of older followers to get average age of older followers
val avgAgeOfOlderFollowers: VertexRDD[Double] =
olderFollowers.mapValues( (id, value) =>
value match { case (count, totalAge) => totalAge / count } )
// Display the results
avgAgeOfOlderFollowers.collect.foreach(println(_))
// $example off$
spark.stop()
}
}
// scalastyle:on println
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