Spark基本操作WordCountDemo编写 打包 提交 运行

Spark操作之Demo编写及提交任务

1 运行spark自带测试程序包

计算pi值

yarn模式提交任务（CDH采用此方式）

bin/spark-submit \
--class org.apache.spark.examples.SparkPi \
--master yarn \
--deploy-mode client \
/opt/cloudera/parcels/CDH/lib/spark/examples/jars/spark-examples_2.11-2.2.0-cdh6.0.1.jar \
100

2 创建sparkdemo项目WordCount

2.1 主要依赖

 <dependencies>
    <dependency>
      <groupId>org.scala-langgroupId>
      <artifactId>scala-libraryartifactId>
      <version>${scala.version}version>
    dependency>
    <dependency>
      <groupId>org.apache.sparkgroupId>
      <artifactId>spark-core_2.11artifactId>
      <version>${spark.version}version>
    dependency>
  dependencies>

2.2 WordCount代码

package com.nml
import org.apache.spark.{SparkConf, SparkContext}
object WordCount {
  def main(args: Array[String]): Unit = {
    val conf = new SparkConf().setMaster("local[*]").setAppName("WordCount")
    val sc = new SparkContext(conf)
    //file://表示读取本地文件
    // 在node3本地新建文件/opt/nml/wc.txt，写入几个单词
    val lines = sc.textFile("file:///opt/nml/wc.txt")
    val words = lines.flatMap(_.split(" "))
    val wordOne = words.map((_,1))
    val wordSum = wordOne.reduceByKey(_+_)
    val result = wordSum.collect()
    result.foreach(println)
  }
}

2.3 maven打包代码

package

Spark01-1.0-SNAPSHOT.jar

Xftp向node3传文件

2.4 提交任务执行代码

在[root@node3 ~]# 下

spark-submit \
--class com.nml.WordCount \
--master yarn \
--deploy-mode client \
/opt/nml/Spark01-1.0-SNAPSHOT.jar

或者

spark-submit \
--class com.nml.WordCount \
--num-executors 3 \
--driver-memory 1G \
--executor-memory 1G \
--executor-cores 3 \
/opt/nml/Spark01-1.0-SNAPSHOT.jar

2.5 执行结果

20/05/25 15:12:32 INFO scheduler.DAGScheduler: ResultStage 1 (collect at WordCount.scala:15) finished in 0.055 s
20/05/25 15:12:32 INFO scheduler.DAGScheduler: Job 0 finished: collect at WordCount.scala:15, took 0.397266 s
(scala,2)
(waterdrop,1)
(spark,3)
(hadoop,2)
20/05/25 15:12:32 INFO spark.SparkContext: Invoking stop() from shutdown hook