如何用idea编写并运行第一个spark scala处理程序

<?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>

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)
  }
}