Spark_scala_Maven项目创建

IDEA创建WordCount Maven项目

创建WordCount源文件

words.text 内容

this is one line
this is two line

WordCount源码

说明参考： https://www.cnblogs.com/studyNotesSL/p/11367751.html

import org.apache.log4j.{Level, Logger}
import org.apache.spark.{SparkConf, SparkContext}

object WordCount {
  def main(args: Array[String]) {
    Logger.getLogger("org.apache.spark").setLevel(Level.WARN)
    // 本地 /words.txt 文件
    val inputFile = "file:///words.txt"
    // hdfs上 /words.txt 文件
    // val inputFile =  "hdfs://master:9000/words.txt" 
    
    val conf = new SparkConf().setAppName("WordCount").setMaster("local")
    val sc = new SparkContext(conf)
    val textFile = sc.textFile(inputFile)
    val wordCount = textFile.flatMap(line => line.split(",")).map(word => (word, 1)).reduceByKey((a, b) => a + b)
    wordCount.foreach(println)
  }
}

pom.xml源码

<?xml version="1.0" encoding="UTF-8"?>
<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/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>

    <groupId>dblab</groupId>
    <artifactId>WordCount</artifactId>
    <version>1.0-SNAPSHOT</version>

    <properties>
        <spark.version>2.2.0</spark.version>
        <scala.version>2.11</scala.version>
    </properties>


    <dependencies>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-core_${scala.version}</artifactId>
            <version>${spark.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming_${scala.version}</artifactId>
            <version>${spark.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-sql_${scala.version}</artifactId>
            <version>${spark.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-hive_${scala.version}</artifactId>
            <version>${spark.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-mllib_${scala.version}</artifactId>
            <version>${spark.version}</version>
        </dependency>

    </dependencies>

    <build>
        <plugins>

            <plugin>
                <groupId>org.scala-tools</groupId>
                <artifactId>maven-scala-plugin</artifactId>
                <version>2.15.2</version>
                <executions>
                    <execution>
                        <goals>
                            <goal>compile</goal>
                            <goal>testCompile</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>

            <plugin>
                <artifactId>maven-compiler-plugin</artifactId>
                <version>3.6.0</version>
                <configuration>
                    <source>1.8</source>
                    <target>1.8</target>
                </configuration>
            </plugin>

            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-surefire-plugin</artifactId>
                <version>2.19</version>
                <configuration>
                    <skip>true</skip>
                </configuration>
            </plugin>

        </plugins>
    </build>

</project>

选择 Enables Auto-Import

打包spark程序

删除多余jar包只留下如下图的文件（Ctrl+A全选，Ctrl+鼠标左键选择需要留下的文件）

以本地文件运行

上传数据文件words.txt文件到Linux的 / 目录

运行提交运行spark程序

以local模式运行
/opt/spark/spark2.2/bin/spark-submit --class WordCount /mnt/hgfs/环境搭建/onf/WordCount.jar 

以伪分布式方式读取hdfs文件运行

启动Hadoop

上传文件

启动spark

进入SPARK HOME
cd /opt/spark/spark2.2/
启动spark
./sbin/start-all.sh 

修改WordCount代码

重写打包代码

运行程序

/opt/spark/spark2.2/bin/spark-submit --master spark://slave2:7077 --class WordCount /mnt/hgfs/环境搭建/conf/WordCount.jar 

查看结果

参考：

http://dblab.xmu.edu.cn/blog/1327/

原文地址：https://www.cnblogs.com/studyNotesSL/p/11377099.html