0 Spark完成WordCount操作

先看下结果：

pom.xml:

<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd">
  <modelVersion>4.0.0</modelVersion>
  <groupId>com.chenjj</groupId>
  <artifactId>sparkDemo</artifactId>
  <version>1.0-SNAPSHOT</version>
  <properties>
    <spark.version>2.2.0</spark.version>
  </properties>

  <repositories>
    <repository>
      <id>nexus-aliyun</id>
      <name>Nexus aliyun</name>
      <url>http://maven.aliyun.com/nexus/content/groups/public</url>
    </repository>
  </repositories>

  <dependencies>
    <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-core_2.10 -->
    <dependency>
      <groupId>org.apache.spark</groupId>
      <artifactId>spark-core_2.11</artifactId>
      <version>${spark.version}</version>
    </dependency>
    <dependency>
      <groupId>org.apache.spark</groupId>
      <artifactId>spark-mllib_2.10</artifactId>
      <version>1.6.0</version>
    </dependency>
  </dependencies>

  <build>
    <plugins>
      <plugin>
        <artifactId>maven-assembly-plugin</artifactId>
        <version>2.3</version>
        <configuration>
          <classifier>dist</classifier>
          <appendAssemblyId>true</appendAssemblyId>
          <descriptorRefs>
            <descriptor>jar-with-dependencies</descriptor>
          </descriptorRefs>
        </configuration>
        <executions>
          <execution>
            <id>make-assembly</id>
            <phase>package</phase>
            <goals>
              <goal>single</goal>
            </goals>
          </execution>
        </executions>
      </plugin>
    </plugins>
  </build>
</project>

 

1、项目目录下新建aa.txt文件

我们 都是 好人
我们 好人 你们 他们
好人 坏人 他们

 

2、scala版本---WordCount3.scala

package com.chenjj
import org.apache.spark.{SparkConf, SparkContext}

object WordCount3 {
  def main(args: Array[String]): Unit = {
　　//conf 可以设置SparkApplication 的名称，设置Spark 运行的模式
    val conf = new SparkConf().setMaster("local").setAppName("wordcount")
　　//SparkContext 是通往spark 集群的唯一通道
    val sc = new SparkContext(conf)
    val rdd = sc.textFile("aa.txt")
      .flatMap(_.split(" "))
      .map((_, 1)).reduceByKey(_ + _)
    rdd.foreach(println)
    rdd.saveAsTextFile("result")
  }
}

3、运行结果：