spark 2.2.0学习笔记2之LocalWordCountDemo

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spark 2.2.0学习笔记2之LocalWordCountDemo

Info

底层—-集群管理器

• local
• 独立调度器—-Spark自带/默认
• Hadoop YARN
• Apache Mesos

大致源码

• org.apache.spark.SparkContext#createTaskScheduler
  
  • 根据master创建TaskScheduler与SchedulerBackend
  • 创建DAGScheduler
  • 启动_taskScheduler.start
  • 通知一系列监听器

Code

package spark30.basic

import org.apache.spark.SparkConf

/**
  * @description
  * @author zhangwu
  * @date 2017-11-06-21:21
  * @version 1.0.0
  */
object LocalWordCountDemo {
  def main(args: Array[String]) {
    val inputFile = "README.md"
    val outputFile = "./countWord"
    // 创建一个Scala版本的Spark Context
    val sc = SparkContextUtil.getSparkContext("wordCount")
    // 读取我们的输入数据
    val input = sc.textFile(inputFile)
    // 把它切分成一个个单词
    val words = input.flatMap(line => line.split(" "))
    // 转换为键值对并计数
    val counts = words.map(word => (word, 1)).reduceByKey { case (x, y) => x + y }
    // 将统计出来的单词总数存入一个文本文件，引发求值
    counts.saveAsTextFile(outputFile)
    sc.stop()
  }
}

package spark30.basic

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

/**
  * ${Description}
  * SparkContext 工具类,以函数式编程的思维思考问题
  * 集群管理器
  *- local
  *- 独立调度器----Spark自带/默认
  *- Hadoop YARN
  *- Apache Mesos
  *
  * @author zhangwu
  * @date 2017-12-19-13:57
  * @version 1.0.0
  */


object SparkContextUtil {

  val master: String = "local"

  def getSparkContext(appName: String): SparkContext = {
    getSparkContext(appName, master)
  }

  def getSparkContext(appName: String
                      , master: String
                     ): SparkContext = {
    val conf = new SparkConf().setAppName(appName).setMaster(master)
    val sc = new SparkContext(conf)
    sc
  }

}

Code

• https://github.com/undergrowthlinear/bigdata-learn.git
  
  • spark30.basic.LocalWordCountDemo