org.apache.spark.examples.mllib.RandomRDDGeneration.scala Maven / Gradle / Ivy

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/*
 * 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.mllib

import org.apache.spark.{SparkConf, SparkContext}
import org.apache.spark.mllib.random.RandomRDDs
import org.apache.spark.rdd.RDD

/**
 * An example app for randomly generated RDDs. Run with
 * {{{
 * bin/run-example org.apache.spark.examples.mllib.RandomRDDGeneration
 * }}}
 * If you use it as a template to create your own app, please use `spark-submit` to submit your app.
 */
object RandomRDDGeneration {

  def main(args: Array[String]): Unit = {

    val conf = new SparkConf().setAppName(s"RandomRDDGeneration")
    val sc = new SparkContext(conf)

    val numExamples = 10000 // number of examples to generate
    val fraction = 0.1 // fraction of data to sample

    // Example: RandomRDDs.normalRDD
    val normalRDD: RDD[Double] = RandomRDDs.normalRDD(sc, numExamples)
    println(s"Generated RDD of ${normalRDD.count()}" +
      " examples sampled from the standard normal distribution")
    println("  First 5 samples:")
    normalRDD.take(5).foreach( x => println(s"    $x") )

    // Example: RandomRDDs.normalVectorRDD
    val normalVectorRDD = RandomRDDs.normalVectorRDD(sc, numRows = numExamples, numCols = 2)
    println(s"Generated RDD of ${normalVectorRDD.count()} examples of length-2 vectors.")
    println("  First 5 samples:")
    normalVectorRDD.take(5).foreach( x => println(s"    $x") )

    println()

    sc.stop()
  }

}
// scalastyle:on println