1.新建一个maven项目

2.填写GroupId和ArtifactId,然后点击Next

3.开启Auto-Import

4.编辑pom.xml

<?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>com.symsimmy</groupId>
    <artifactId>sparklearning</artifactId>
    <version>1.0-SNAPSHOT</version>

    <properties>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <spark.version>2.2.0</spark.version>
        <scala.version>2.11</scala.version>
        <hadoop.version>2.9.0</hadoop.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-sql_${scala.version}</artifactId>
            <version>${spark.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming_${scala.version}</artifactId>
            <version>${spark.version}</version>
        </dependency>
        <dependency>
            <groupId>junit</groupId>
            <artifactId>junit</artifactId>
            <version>4.12</version>
        </dependency>
    </dependencies>

    <build>
        <sourceDirectory>src/main/scala</sourceDirectory>
        <testSourceDirectory>src/test/scala</testSourceDirectory>

        <plugins>
            <plugin>
                <!-- MAVEN 编译使用的JDK版本 -->
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <version>3.7</version>
                <configuration>
                    <source>1.8</source>
                    <target>1.8</target>
                    <encoding>UTF-8</encoding>
                </configuration>
            </plugin>
        </plugins>
    </build>

</project>

5.添加scala SDK

这里经过我的验证,在spark-2.2.0版本下,scala-2.12.4会出错,这是一个坑,所以我推荐官方2.2.0文档中出现的2.11.8,实测可以用.
进入Project Structure->Library,点击+号,选择Scala SDK.

6.配置环境

• src目录下面添加scala目录,并设置为Source Folders
• test目录下面添加scala目录和resources目录,并分别设置为Source Folders和Test Resource Folders
  

7.运行spark实例SparkPi

在src/scala目录下,右键New一个Scala Class,命名为ScalaPi,类型选择为Object

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

// scalastyle:off println
package scala

import scala.math.random

import org.apache.spark.sql.SparkSession

/** Computes an approximation to pi */
object SparkPi {
  def main(args: Array[String]) {
    val spark = SparkSession
      .builder()
      .appName("Spark Pi")
      .getOrCreate() 
    val slices = if (args.length > 0) args(0).toInt else 2
    val n = math.min(100000L * slices, Int.MaxValue).toInt // avoid overflow
    val count = spark.sparkContext.parallelize(1 until n, slices).map { i =>
      val x = random * 2 - 1
      val y = random * 2 - 1
      if (x*x + y*y <= 1) 1 else 0
    }.reduce(_ + _)
    println("Pi is roughly " + 4.0 * count / (n - 1))
    spark.stop()
  }
}
// scalastyle:on println

报错,如何解决

17/12/06 10:10:14 ERROR SparkContext: Error initializing SparkContext.
org.apache.spark.SparkException: A master URL must be set in your configuration
    at org.apache.spark.SparkContext.<init>(SparkContext.scala:376)
    at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2509)
    at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:909)
    at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:901)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:901)
    at SparkPi$.main(SparkPi.scala:31)
    at SparkPi.main(SparkPi.scala)
17/12/06 10:10:14 INFO SparkContext: Successfully stopped SparkContext
Exception in thread "main" org.apache.spark.SparkException: A master URL must be set in your configuration
    at org.apache.spark.SparkContext.<init>(SparkContext.scala:376)
    at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2509)
    at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:909)
    at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:901)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:901)
    at SparkPi$.main(SparkPi.scala:31)
    at SparkPi.main(SparkPi.scala)

Process finished with exit code 1

首先,必须说明,直接运行是一定会出错的,我们知道spark有几种运行模式.如果想本地运行,必须设置为local
我们可以在Edit Configurations中添加VM Options,-Dspark.master=local

• 点击ok,之后就正确运行了

  
  

8.设置环境,打jar包

• 设置Artifacts,选择From modules with dependencies...
  

• 选择Main Class为SparkPi
  

• 最后为这样,可以自定义生成的jar包的位置,点击ok即可

  
  

• 点击build->build Artifacts
  

• 在屏幕中间出现该菜单,点击Build
  

• build成功后,会在out目录下面生成一个jar包
  

使用spark-shell运行生成的jar包

参考文章

• 基于IntelliJ IDEA开发Spark的Maven项目——Scala语言