十分钟sparkstreaming简单入门测试(2018-04-19)

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idea编辑器安装

参考笔记：http://www.aboutyun.com/thread-22320-1-1.html

给大家准备了资料包：
下载地址：
https://pan.baidu.com/s/1auAjP4npWDD0oGfNjXlySQ

下载spark安装包和scala的安装包

http://mirrors.hust.edu.cn/apache/spark/spark-1.6.3/

https://www.scala-lang.org/download/all.html

添加环境变量

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我的地址是D:\linghit\lingghit_soft\spark-2.2.0-bin-hadoop2.6\spark-2.2.0-bin-hadoop2.6

我的地址是：D:\linghit\lingghit_soft\scala-2.11.8\scala-2.11.8

最后Path里面也要添加

idea中新建项目

添加：

<spark.version>1.6.3</spark.version>
<hadoop.version>2.6.4</hadoop.version>


<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-streaming_2.11</artifactId>
  <version>${spark.version}</version>
</dependency>

最终的pom.xml文件是这样的

<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.linghit.sparklearning</groupId>
  <artifactId>MySpark</artifactId>
  <version>1.1-SNAPSHOT</version>
  <inceptionYear>2008</inceptionYear>
  <properties>
    <scala.version>2.11.8</scala.version>
    <spark.version>1.6.3</spark.version>
    <hadoop.version>2.6.4</hadoop.version>

  </properties>

  <repositories>
    <repository>
      <id>scala-tools.org</id>
      <name>Scala-Tools Maven2 Repository</name>
      <url>http://scala-tools.org/repo-releases</url>
    </repository>
  </repositories>

  <pluginRepositories>
    <pluginRepository>
      <id>scala-tools.org</id>
      <name>Scala-Tools Maven2 Repository</name>
      <url>http://scala-tools.org/repo-releases</url>
    </pluginRepository>
  </pluginRepositories>

  <dependencies>
    <dependency>
      <groupId>org.scala-lang</groupId>
      <artifactId>scala-library</artifactId>
      <version>${scala.version}</version>
    </dependency>
    <dependency>
      <groupId>junit</groupId>
      <artifactId>junit</artifactId>
      <version>4.4</version>
      <scope>test</scope>
    </dependency>
    <dependency>
      <groupId>org.specs</groupId>
      <artifactId>specs</artifactId>
      <version>1.2.5</version>
      <scope>test</scope>
    </dependency>

    <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-streaming_2.11</artifactId>
      <version>${spark.version}</version>
    </dependency>

  </dependencies>

  <build>
    <sourceDirectory>src/main/scala</sourceDirectory>
    <testSourceDirectory>src/test/scala</testSourceDirectory>
    <plugins>
      <plugin>
        <groupId>org.scala-tools</groupId>
        <artifactId>maven-scala-plugin</artifactId>
        <executions>
          <execution>
            <goals>
              <goal>compile</goal>
              <goal>testCompile</goal>
            </goals>
          </execution>
        </executions>
        <configuration>
          <scalaVersion>${scala.version}</scalaVersion>
          <args>
            <arg>-target:jvm-1.5</arg>
          </args>
        </configuration>
      </plugin>
      <plugin>
        <groupId>org.apache.maven.plugins</groupId>
        <artifactId>maven-eclipse-plugin</artifactId>
        <configuration>
          <downloadSources>true</downloadSources>
          <buildcommands>
            <buildcommand>ch.epfl.lamp.sdt.core.scalabuilder</buildcommand>
          </buildcommands>
          <additionalProjectnatures>
            <projectnature>ch.epfl.lamp.sdt.core.scalanature</projectnature>
          </additionalProjectnatures>
          <classpathContainers>
            <classpathContainer>org.eclipse.jdt.launching.JRE_CONTAINER</classpathContainer>
            <classpathContainer>ch.epfl.lamp.sdt.launching.SCALA_CONTAINER</classpathContainer>
          </classpathContainers>
        </configuration>
      </plugin>
    </plugins>
  </build>
  <reporting>
    <plugins>
      <plugin>
        <groupId>org.scala-tools</groupId>
        <artifactId>maven-scala-plugin</artifactId>
        <configuration>
          <scalaVersion>${scala.version}</scalaVersion>
        </configuration>
      </plugin>
    </plugins>
  </reporting>
</project>

启动nc -lk

import org.apache.log4j.{Level, Logger}
import org.apache.spark.SparkConf
import org.apache.spark.streaming.{Seconds, StreamingContext}
import org.slf4j.LoggerFactory

/**
  * Created by Administrator on 2018/4/19.
  */
object TestNetworkWordCount {
  def main(args: Array[String]): Unit = {
    var logger = LoggerFactory.getLogger(TestNetworkWordCount.getClass)
    Logger.getLogger("org.apache.spark").setLevel(Level.ERROR)
    val conf =  new SparkConf().setMaster("local[2]").setAppName("wordcountonline")
    val ssc  = new StreamingContext(conf,Seconds(5))
    val lines = ssc.socketTextStream("120.27.251.175", 9991)
    //按空格分割
    val words = lines.flatMap { line => line.split(" ") }
    //把单个的word变成tuple
    val wordCount  = words.map { word => (word,1) }
    /**
      * (key1,1) (key1,1)
      * key相同的累加。
      */
    wordCount.reduceByKey(_+_)
    wordCount.print()
    ssc.start()
    /**
      * 等待程序结束
      */
    ssc.awaitTermination()
    ssc.stop(true)

  }

}

启动流计算程序

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