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用idea编写并运行第一个spark scala处理程序

article 2024/11/15 0:23:25

1、用idea创建工程，类别为：Scala，选IDEA类型，下一步选择JDK 1.8和Scala SDK：scala-sdk-2.12.20(scala安装位置)。
2、点右键，添加框架支持（Add Framework Support），选择Maven支持。
3、pom.xml的内容：

<?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>groupId</groupId>
    <artifactId>scala01</artifactId>
    <version>1.0-SNAPSHOT</version>

    <properties>
        <maven.compiler.source>8</maven.compiler.source>
        <maven.compiler.target>8</maven.compiler.target>
    </properties>
    <dependencies>
        <dependency>
            <groupId>net.alchim31.maven</groupId>
            <artifactId>scala-maven-plugin</artifactId>
            <version>3.2.2</version>
        </dependency>
        <dependency>
            <groupId>org.scala-lang</groupId>
            <artifactId>scala-library</artifactId>
            <version>2.12.20</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-core_2.12</artifactId>
            <version>3.5.2</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-common-utils_2.13</artifactId>
            <version>3.5.2</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-network-common_2.13</artifactId>
            <version>3.5.2</version>
        </dependency>

    </dependencies>
</project>

刷新maven工程。
4、创建包：com.rainpet
包下新建Scala文件Hello.scala，内容如下：

package com.rainpet

import org.apache.spark.{SparkConf, SparkContext}

object Hello {
  def main(args: Array[String]): Unit = {
    val conf = new SparkConf().setAppName("educoder").setMaster("local")
    val sc = new SparkContext(conf)
    //var file1=sc: SparkContext.textFile("hdfs://master:9000/user/input/1.txt")
    //ci'pin'tong'ji
    var file1 = sc.textFile("hdfs://master:8020/user/input/1.txt")
    var wordCounts = file1.flatMap(line => line.split(" ")).map(word => (word, 1)).reduceByKey(_ + _)
    wordCounts.collect().foreach(println)
  }

}