《IDEA创建Spark工程并submit执行》

  1、创建时在Scala中选择IDEA项目
        
  2、设置JAVA JDK 和Scala的JDK，其中Project SDK需要通过“New…”设置为JDK的路径；Scala SDK需要通过“Create…”设置为Scala的路径，同时命名项目
        
  3、在弹出的窗口中单击“Modules”命令，在对应的右侧窗口中，选中“src”文件夹并单击右键，选择“New Folder…”命令，创建“main”文件夹，如下图。同样的步骤，再选中“main”，在其中分别创建“java”、“resources”、"scala"文件夹，然后通过“Mark as”设置文件夹属性，目录结构如下图。
      
  4、在项目目录下添加pom.xml文件
         
  pom.xml文件中的内容为：很多暂时没用到的依赖也先放进来了，根据自己版本和需要更改

<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>zjut</groupId>
    <artifactId>NeutralNet</artifactId>
    <version>1.0</version>
    <inceptionYear>2008</inceptionYear>
    <properties>
        <scala.version>2.11.8</scala.version>
        <kafka.version>0.9.0.0</kafka.version>
        <spark.version>2.2.0</spark.version>
        <hadoop.version>2.6.0-cdh5.7.0</hadoop.version>
        <hbase.version>1.2.0-cdh5.7.0</hbase.version>
    </properties>

    <!--添加cloudera的repository-->
    <repositories>
        <repository>
            <id>cloudera</id>
            <url>https://repository.cloudera.com/artifactory/cloudera-repos</url>
        </repository>
    </repositories>

    <dependencies>
        <dependency>
            <groupId>org.scala-lang</groupId>
            <artifactId>scala-library</artifactId>
            <version>${scala.version}</version>
        </dependency>

        <!-- Kafka 依赖-->
        <!--
        <dependency>
            <groupId>org.apache.kafka</groupId>
            <artifactId>kafka_2.11</artifactId>
            <version>${kafka.version}</version>
        </dependency>
        -->

        <!-- Hadoop 依赖-->
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-client</artifactId>
            <version>${hadoop.version}</version>
        </dependency>

        <!-- HBase 依赖
        <dependency>
            <groupId>org.apache.hbase</groupId>
            <artifactId>hbase-client</artifactId>
            <version>${hbase.version}</version>
        </dependency>

        <dependency>
            <groupId>org.apache.hbase</groupId>
            <artifactId>hbase-server</artifactId>
            <version>${hbase.version}</version>
        </dependency>
        -->
        <!-- Spark Streaming 依赖
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming_2.11</artifactId>
            <version>${spark.version}</version>
        </dependency>
        -->

        <!-- Spark Streaming整合Flume 依赖-->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming-flume_2.11</artifactId>
            <version>${spark.version}</version>
        </dependency>

        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming-flume-sink_2.11</artifactId>
            <version>${spark.version}</version>
        </dependency>

        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming-kafka-0-8_2.11</artifactId>
            <version>${spark.version}</version>
        </dependency>

        <dependency>
            <groupId>org.apache.commons</groupId>
            <artifactId>commons-lang3</artifactId>
            <version>3.5</version>
        </dependency>

        <!-- Spark SQL 依赖-->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-sql_2.11</artifactId>
            <version>${spark.version}</version>
        </dependency>


        <dependency>
            <groupId>com.fasterxml.jackson.module</groupId>
            <artifactId>jackson-module-scala_2.11</artifactId>
            <version>2.6.5</version>
        </dependency>

        <dependency>
            <groupId>net.jpountz.lz4</groupId>
            <artifactId>lz4</artifactId>
            <version>1.3.0</version>
        </dependency>

        <dependency>
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
            <version>5.1.38</version>
        </dependency>

        <dependency>
            <groupId>org.apache.flume.flume-ng-clients</groupId>
            <artifactId>flume-ng-log4jappender</artifactId>
            <version>1.6.0</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.mortbay.jetty/jetty-util -->

    </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>
                <artifactId>maven-assembly-plugin</artifactId>
                <version>3.1.0</version>
                <configuration>
                    <descriptorRefs>
                        <descriptorRef>jar-with-dependencies</descriptorRef>
                    </descriptorRefs>
                    <archive>
                        <manifest>
                            <mainClass>com.immoc.spark.project.spark.ImmocStatStreamingApp</mainClass>
                        </manifest>

                    </archive>

                </configuration>
                <executions>
                    <execution>
                        <id>make-assembly</id> <!-- this is used for inheritance merges -->
                        <phase>package</phase> <!-- bind to the packaging phase -->
                        <goals>
                            <goal>single</goal>
                        </goals>
                    </execution>
                </executions>
            </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>

  5、右键Pom文件，add as maven project。
              
  6、依赖文件pom.xml报错，需要自己重新指定仓库位置与配置文件，enable auto change

  7、在scala包下，新建FirstTest类

  FirstTest内容：/etc/profile是我centos下的环境变量配置文件，/software/wordcount是我指定输出在/software目录下，输出wordcount

package scala
import org.apache.spark.{SparkContext,SparkConf}
object FirstTest {
  def main(args: Array[String]): Unit = {
    val conf = new SparkConf().setAppName("wordcount")
    val sc = new SparkContext(conf)
    val input = sc.textFile("/etc/profile")
    val lines = input.flatMap(line=>line.split(" "))
    val count = lines.map(word=>(word,1)).reduceByKey{case(x,y)=>x+y}
    val output = count.saveAsTextFile("/software/wordcount")
  }
}

  8、指定生成的artifact版本，注意指定打包的入口类
    
    
      
  9、双击右侧maven project中的Lifecycle中的install

  finish后，将NeutralNet-1.0-jar-with-dependencies.jar上传至spark环境下：

  10、将打包好的jar拷贝至spark环境下，启动spark集群，提交。最常出现的问题，提示没有出现的类

  你会打开自己打包的jar，会发现确实没有scala.FirstTest的类

解决办法：尝试在build中选择build artifacts，rebuild，而不是直接install
你可以看到此时NeturalNet1-1.0.jar中有FirstTest.class文件

重新提交指令：./spark-submit --class “scala.FirstTest” /software/spark-2.2.0-bin-2.6.0-cdh5.7.0/user_jar/NeutralNet1-1.0-jar-with-dependencies.jar 其中， /software/spark-2.2.0-bin-2.6.0-cdh5.7.0/user_jar/放着我的jar。开始运行，如下图：

10、在我的wordcount下，你可以看到我的输出结果：