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



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

1、Maven管理项目在JavaEE普遍使用，开发Spark项目也不例外，而Scala语言开发Spark项目的首选。因此需要构建Maven-Scala项目来开发Spark项目，本文采用的工具是IntelliJ IDEA 2016，IDEA工具越来越被大家认可，开发Java,Python ,scala 支持都非常好

下载链接 ： https://www.jetbrains.com/idea/download/

安装直接下一步即可

2、安装scala插件，File->Settings->Editor->Plugins,搜索scala即可安装

可能由于网络的原因下载不了，可以采取离线安装的方式，例如：

提示下载失败后，根据提示的地址下载离线安装包 http://plugins.jetbrains.com/files/631/24825/python-145.86.zip

在界面选择离线安装即可：

3、创建Maven工程，File->New Project->Maven

选择相应的JDK版本，直接下一步

设定Maven项目的GroupId及ArifactId

创建项目的工程名称，点击完成即可

创建Maven工程完毕，默认是Java的，没关系后面我们再添加scala与spark的依赖

4、修改Maven项目的pom.xml文件，增加scala与spark的依赖

[java] view plain copy print?

1. <?xml version="1.0" encoding="UTF-8"?>  
2. <project xmlns="http://maven.apache.org/POM/4.0.0"  
3.          xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"  
4.          xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">  
5.     <modelVersion>4.0.0</modelVersion>  
6.   
7.     <groupId>com.ganymede</groupId>  
8.     <artifactId>sparkplatformstudy</artifactId>  
9.     <version>1.0-SNAPSHOT</version>  
10.   
11.     <properties>  
12.         <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>  
13.         <spark.version>1.6.0</spark.version>  
14.         <scala.version>2.10</scala.version>  
15.         <hadoop.version>2.6.0</hadoop.version>  
16.     </properties>  
17.   
18.     <dependencies>  
19.         <dependency>  
20.             <groupId>org.apache.spark</groupId>  
21.             <artifactId>spark-core_${scala.version}</artifactId>  
22.             <version>${spark.version}</version>  
23.         </dependency>  
24.         <dependency>  
25.             <groupId>org.apache.spark</groupId>  
26.             <artifactId>spark-sql_${scala.version}</artifactId>  
27.             <version>${spark.version}</version>  
28.         </dependency>  
29.         <dependency>  
30.             <groupId>org.apache.spark</groupId>  
31.             <artifactId>spark-hive_${scala.version}</artifactId>  
32.             <version>${spark.version}</version>  
33.         </dependency>  
34.         <dependency>  
35.             <groupId>org.apache.spark</groupId>  
36.             <artifactId>spark-streaming_${scala.version}</artifactId>  
37.             <version>${spark.version}</version>  
38.         </dependency>  
39.         <dependency>  
40.             <groupId>org.apache.hadoop</groupId>  
41.             <artifactId>hadoop-client</artifactId>  
42.             <version>2.6.0</version>  
43.         </dependency>  
44.         <dependency>  
45.             <groupId>org.apache.spark</groupId>  
46.             <artifactId>spark-streaming-kafka_${scala.version}</artifactId>  
47.             <version>${spark.version}</version>  
48.         </dependency>  
49.         <dependency>  
50.             <groupId>org.apache.spark</groupId>  
51.             <artifactId>spark-mllib_${scala.version}</artifactId>  
52.             <version>${spark.version}</version>  
53.         </dependency>  
54.         <dependency>  
55.             <groupId>mysql</groupId>  
56.             <artifactId>mysql-connector-java</artifactId>  
57.             <version>5.1.39</version>  
58.         </dependency>  
59.         <dependency>  
60.             <groupId>junit</groupId>  
61.             <artifactId>junit</artifactId>  
62.             <version>4.12</version>  
63.         </dependency>  
64.     </dependencies>  
65.   
66.     <!-- maven官方 http://repo1.maven.org/maven2/  或 http://repo2.maven.org/maven2/ （延迟低一些） -->  
67.     <repositories>  
68.         <repository>  
69.             <id>central</id>  
70.             <name>Maven Repository Switchboard</name>  
71.             <layout>default</layout>  
72.             <url>http://repo2.maven.org/maven2</url>  
73.             <snapshots>  
74.                 <enabled>false</enabled>  
75.             </snapshots>  
76.         </repository>  
77.     </repositories>  
78.   
79.     <build>  
80.         <sourceDirectory>src/main/scala</sourceDirectory>  
81.         <testSourceDirectory>src/test/scala</testSourceDirectory>  
82.   
83.         <plugins>  
84.             <plugin>  
85.                 <!-- MAVEN 编译使用的JDK版本 -->  
86.                 <groupId>org.apache.maven.plugins</groupId>  
87.                 <artifactId>maven-compiler-plugin</artifactId>  
88.                 <version>3.3</version>  
89.                 <configuration>  
90.                     <source>1.7</source>  
91.                     <target>1.7</target>  
92.                     <encoding>UTF-8</encoding>  
93.                 </configuration>  
94.             </plugin>  
95.         </plugins>  
96.     </build>  
97. </project>  

<?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.ganymede</groupId>    <artifactId>sparkplatformstudy</artifactId>    <version>1.0-SNAPSHOT</version>    <properties>        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>        <spark.version>1.6.0</spark.version>        <scala.version>2.10</scala.version>        <hadoop.version>2.6.0</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-hive_${scala.version}</artifactId>            <version>${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.hadoop</groupId>            <artifactId>hadoop-client</artifactId>            <version>2.6.0</version>        </dependency>        <dependency>            <groupId>org.apache.spark</groupId>            <artifactId>spark-streaming-kafka_${scala.version}</artifactId>            <version>${spark.version}</version>        </dependency>        <dependency>            <groupId>org.apache.spark</groupId>            <artifactId>spark-mllib_${scala.version}</artifactId>            <version>${spark.version}</version>        </dependency>        <dependency>            <groupId>mysql</groupId>            <artifactId>mysql-connector-java</artifactId>            <version>5.1.39</version>        </dependency>        <dependency>            <groupId>junit</groupId>            <artifactId>junit</artifactId>            <version>4.12</version>        </dependency>    </dependencies>    <!-- maven官方 http://repo1.maven.org/maven2/  或 http://repo2.maven.org/maven2/ （延迟低一些） -->    <repositories>        <repository>            <id>central</id>            <name>Maven Repository Switchboard</name>            <layout>default</layout>            <url>http://repo2.maven.org/maven2</url>            <snapshots>                <enabled>false</enabled>            </snapshots>        </repository>    </repositories>    <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>3.3</version>                <configuration>                    <source>1.7</source>                    <target>1.7</target>                    <encoding>UTF-8</encoding>                </configuration>            </plugin>        </plugins>    </build></project>

5、删除项目的java目录，新建scala并设置源文件夹

添加scala的SDK

添加scala的SDK成功

6、开发Spark实例

测试案例来自spark官网的mllib例子 http://spark.apache.org/docs/latest/mllib-data-types.html

[java] view plain copy print?

1. import org.apache.spark.{SparkConf, SparkContext}  
2.   
3. /** 
4.   * Created by wuke on 2016/7/5. 
5.   */  
6. object LoadLibSVMFile extends App{  
7.   import org.apache.spark.mllib.regression.LabeledPoint  
8.   import org.apache.spark.mllib.util.MLUtils  
9.   import org.apache.spark.rdd.RDD  
10.   
11.   val conf = new SparkConf().setAppName("LogisticRegressionMail").setMaster("local")  
12.   
13.   val sc = new SparkContext(conf)  
14.   val examples: RDD[LabeledPoint] = MLUtils.loadLibSVMFile(sc, "data/mllib/sample_libsvm_data.txt")  
15.   
16.   println(examples.first)  
17. }  

import org.apache.spark.{SparkConf, SparkContext}/**  * Created by wuke on 2016/7/5.  */object LoadLibSVMFile extends App{  import org.apache.spark.mllib.regression.LabeledPoint  import org.apache.spark.mllib.util.MLUtils  import org.apache.spark.rdd.RDD  val conf = new SparkConf().setAppName("LogisticRegressionMail").setMaster("local")  val sc = new SparkContext(conf)  val examples: RDD[LabeledPoint] = MLUtils.loadLibSVMFile(sc, "data/mllib/sample_libsvm_data.txt")  println(examples.first)}

测试通过

7、打包编译，线上发布

注意选择依赖包