Spark中组件Mllib的学习21之随机数-RandomRDD产生

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更多代码请见：https://github.com/xubo245/SparkLearning
Spark中组件Mllib的学习之基础概念篇
1解释
在org.apache.spark.mllib.random下RandomRDDs对象，处理生成RandomRDD，还可以生成uniformRDD、poissonRDD、exponentialRDD、gammaRDD等

2.代码：

/**  * @author xubo  *         ref:Spark MlLib机器学习实战  *         more code:https://github.com/xubo245/SparkLearning  *         more blog:http://blog.csdn.net/xubo245  */package org.apache.spark.mllib.learning.basicimport org.apache.spark.mllib.random.RandomRDDs._import org.apache.spark.{SparkConf, SparkContext}/**  * Created by xubo on 2016/5/23.  */object RandomRDDLearning {  def main(args: Array[String]) {    val conf = new SparkConf().setMaster("local[4]").setAppName(this.getClass().getSimpleName().filter(!_.equals('$')))    val sc = new SparkContext(conf)    println("normalRDD:")    val randomNum = normalRDD(sc, 10)    randomNum.foreach(println)    println("uniformRDD:")    uniformRDD(sc, 10).foreach(println)    println("poissonRDD:")    poissonRDD(sc, 5,10).foreach(println)    println("exponentialRDD:")    exponentialRDD(sc,7, 10).foreach(println)    println("gammaRDD:")    gammaRDD(sc, 3,3,10).foreach(println)    sc.stop  }}

3.结果：

normalRDD:0.191393420574446550.428476258336029260.4326761507664112.031243580737701-1.6210366564577097-0.57363909681589380.51189509173918260.36612870444413614-0.78413875851109050.11439913262616007uniformRDD:0.24384505520726240.70035227040537410.242355582637477250.497019501428857650.466523685334232830.9808276770733540.68255580701965460.48179498391395170.99650176517887550.7568845648015728poissonRDD:2.02.04.06.04.02.04.02.03.09.0exponentialRDD:12.2140821933074694.6825545782205040.97587395347809471.02280727085471655.8446975369232581.1171819168884318.30011694047783.02542195747269641.98070473884031347.218371820752084gammaRDD:15.36294549067940112.5083414307616916.2845826850396092.73128432161181919.03245473181052514.5083951240687738.6848807854229513.532995666035520615.8526251484698284.284198644233831

参考
【1】http://spark.apache.org/docs/1.5.2/mllib-guide.html
【2】http://spark.apache.org/docs/1.5.2/programming-guide.html
【3】https://github.com/xubo245/SparkLearning

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