PageRank.scala

/**
 * Copyright (C) 2015 Baifendian Corporation
 *
 * Licensed 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.examples

import org.apache.spark.{SparkConf, SparkContext}

object PageRank {
  def showWarning() {
    System.err.println(
      """WARN: This is a naive implementation of PageRank and is given as an example!
        |Please use the PageRank implementation found in org.apache.spark.graphx.lib.PageRank
        |for more conventional use.
      """.stripMargin)
  }

  def main(args: Array[String]) {
    if (args.length < 1) {
      System.err.println("Usage: <file> <iter>")
      System.exit(1)
    }

    showWarning()

    val sparkConf = new SparkConf().setAppName("PageRank")
    val iters = if (args.length > 1) args(1).toInt else 10
    val ctx = new SparkContext(sparkConf)
    val lines = ctx.textFile(args(0), 10)

    val links = lines.map { s =>
      val parts = s.split("\\s+")
      (parts(0), parts(1))
    }.distinct().groupByKey().cache()

    var ranks = links.mapValues(v => 1.0)

    for (i <- 1 to iters) {
      val contribs = links.join(ranks).values.flatMap { case (urls, rank) =>
        val size = urls.size
        urls.map(url => (url, rank / size))
      }
      ranks = contribs.reduceByKey(_ + _).mapValues(0.15 + 0.85 * _)
    }

    val output = ranks.sortBy(t => t._2, false).take(100)
    output.foreach(tup => println(tup._1 + " has rank: " + tup._2 + "."))

    ctx.stop()
  }
}