Inteliij IDEA 配置CDH5.11.0版本spark本地开发环境
1、 IDEA创建maven项目
注意配置图上红框的版本号，配成1.6版本，主要解决scala,junit版本报错问题：
http://blog.csdn.net/u012551524/article/details/78967646
2、 然后下一步
定义项目基本属性
3、 下一步
配置maven版本，及依赖路径，配置文件路径
4、 下一步，定义项目路径
5、 建完项目后配置pom文件
修改pom文件内容如下：
<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/4.0.0http://maven.apache.org/maven-v4_0_0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>spark.learning</groupId>
<artifactId>spark</artifactId>
<version>1.0-SNAPSHOT</version>
<name>${project.artifactId}</name>
<description>My wonderfull scala app</description>
<inceptionYear>2015</inceptionYear>
<licenses>
<license>
<name>My License</name>
<url>http://....</url>
<distribution>repo</distribution>
</license>
</licenses>
<properties>
<maven.compiler.source>1.6</maven.compiler.source>
<maven.compiler.target>1.6</maven.compiler.target>
<encoding>UTF-8</encoding>
<scala.version>2.10.5</scala.version>
<scala.compat.version>2.10</scala.compat.version>
<spark.version>1.6.0-cdh5.11.0</spark.version>
<spark.artifact>2.10</spark.artifact>
<hbase.version>1.2.0-cdh5.11.0</hbase.version>
<dependency.scope>compile</dependency.scope>
</properties>
<!--构建cloudera远程仓库-->
<repositories>
<repository>
<id>cloudera</id>
<url>https://repository.cloudera.com/artifactory/cloudera-repos/</url>
</repository>
</repositories>
<dependencies>
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-library</artifactId>
<version>${scala.version}</version>
</dependency>
<!-- Test -->
<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<version>4.11</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.specs2</groupId>
<artifactId>specs2-core_${scala.compat.version}</artifactId>
<version>2.4.16</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.scalatest</groupId>
<artifactId>scalatest_${scala.compat.version}</artifactId>
<version>2.2.4</version>
<scope>test</scope>
</dependency>
<!-- CDH !-->
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-lang3</artifactId>
<version>3.0</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-hdfs</artifactId>
<version>2.6.0-cdh5.11.0</version>
<exclusions>
<exclusion>
<groupId>javax.servlet</groupId>
<artifactId>*</artifactId>
</exclusion>
<exclusion>
<groupId>javax.servlet.jsp</groupId>
<artifactId>*</artifactId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-common</artifactId>
<version>2.6.0-cdh5.11.0</version>
<exclusions>
<exclusion>
<groupId>javax.servlet</groupId>
<artifactId>*</artifactId>
</exclusion>
<exclusion>
<groupId>javax.servlet.jsp</groupId>
<artifactId>*</artifactId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-mapreduce-client-core</artifactId>
<version>2.6.0-cdh5.11.0</version>
<exclusions>
<exclusion>
<groupId>javax.servlet</groupId>
<artifactId>*</artifactId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>org.apache.hbase</groupId>
<artifactId>hbase-client</artifactId>
<version>${hbase.version}</version>
<exclusions>
<exclusion>
<groupId>*</groupId>
<artifactId>javax.servlet</artifactId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>org.apache.hbase</groupId>
<artifactId>hbase-common</artifactId>
<version>${hbase.version}</version>
<exclusions>
<exclusion>
<groupId>javax.servlet</groupId>
<artifactId>*</artifactId>
</exclusion>
<exclusion>
<groupId>javax.servlet.jsp</groupId>
<artifactId>*</artifactId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>org.apache.hbase</groupId>
<artifactId>hbase-spark</artifactId>
<version>${hbase.version}</version>
</dependency>
<dependency>
<groupId>org.apache.hbase</groupId>
<artifactId>hbase-server</artifactId>
<version>${hbase.version}</version>
<exclusions>
<exclusion>
<groupId>*</groupId>
<artifactId>javax.servlet</artifactId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_${spark.artifact}</artifactId>
<version>${spark.version}</version>
<scope>${dependency.scope}</scope>
<exclusions>
<exclusion>
<groupId>org.eclipse.jetty.orbit</groupId>
<artifactId>javax.servlet</artifactId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_${spark.artifact}</artifactId>
<version>${spark.version}</version>
<scope>${dependency.scope}</scope>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-hive_${spark.artifact}</artifactId>
<version>${spark.version}</version>
<scope>${dependency.scope}</scope>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-mllib_${spark.artifact}</artifactId>
<version>${spark.version}</version>
<scope>${dependency.scope}</scope>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming-kafka_${spark.artifact}</artifactId>
<version>${spark.version}</version>
<scope>${dependency.scope}</scope>
</dependency>
<!--注释掉所有javax.servlet的依赖，重新下载-->
<dependency>
<groupId>javax.servlet</groupId>
<artifactId>javax.servlet-api</artifactId>
<version>3.0.1</version>
<scope>${dependency.scope}</scope>
</dependency>
</dependencies>
<build>
<sourceDirectory>src/main/scala</sourceDirectory>
<testSourceDirectory>src/test/scala</testSourceDirectory>
<plugins>
<plugin>
<!-- see http://davidb.github.com/scala-maven-plugin-->
<groupId>net.alchim31.maven</groupId>
<artifactId>scala-maven-plugin</artifactId>
<version>3.3.1</version>
<executions>
<execution>
<goals>
<goal>compile</goal>
<goal>testCompile</goal>
</goals>
<configuration>
<args>
<arg>-make:transitive</arg>
<arg>-dependencyfile</arg>
<arg>${project.build.directory}/.scala_dependencies</arg>
</args>
</configuration>
</execution>
</executions>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-surefire-plugin</artifactId>
<version>2.18.1</version>
<configuration>
<useFile>false</useFile>
<disableXmlReport>true</disableXmlReport>
<!-- If you have classpath issue likeNoDefClassError,... -->
<!--useManifestOnlyJar>false</useManifestOnlyJar -->
<includes>
<include>**/*Test.*</include>
<include>**/*Suite.*</include>
</includes>
</configuration>
</plugin>
</plugins>
</build>
</project>
修改pom注意事项：
a) CDH spark版本依赖配置可参考cloudera官网说明:
b) 如上配置注意一点
这里要注视掉含有javax.servlet所有依赖中的相关依赖包，避免版本冲突，然后重新配置下载
注释方式如下：
如果不注释的话，会报jar包冲突问题，如下：
“javax.servlet.FilterRegistration”‘s signer information does not match signer information of otherclasses in the same package
寻找冲突依赖可以通过maven helper插件：
安装maven helper:
http://blog.csdn.net/difffate/article/details/76279005
使用该插件找到冲突的依赖，然后用上边方式注掉：
6、 测试
7、 import
org.apache.spark.{SparkConf, SparkContext}
object Demo {
def main(args:Array[String]) {
System.setProperty("hadoop.home.dir",
"C:\\hadoop-2.6.0-cdh5.11.0")
// 设置Spark的序列化方式
System.setProperty("spark.serializer",
"org.apache.spark.serializer.KryoSerializer")
// 初始化Spark
val sparkConf=
new SparkConf().setAppName("CountDemo").setMaster("local")
val sc =
new SparkContext(sparkConf)
// 读取文件
val rdd =sc.textFile("C:\\1.txt")
println("文件的行数为："
+rdd.count())
val re=rdd.map(x=>(x,x)).collect()
re.foreach(x => println("num="
+ x._1+",name="
+x._2))
val age=rdd.map(x=>(x,"30岁"))
age.collect().foreach(x => println("num="+x._1+",age="+x._2))
val joinRDD= sc.makeRDD(re).join(age).collect.foreach(println)
sc.stop()
}
}
注：System.setProperty("hadoop.home.dir","C:\\hadoop-2.6.0-cdh5.11.0")
1、 本地hadoop,spark开发，都要配一下本地的Hadoop环境，windows环境下只需要下载hadoop的tar包，在代码中指定目录位置即可
2、 单单第一步执行时还是会报错
java.io.IOException:Could not locate executablenull\bin\winutils.exe in the Hadoop binaries.
这里要下载winutils.exe插件
https://github.com/srccodes/hadoop-common-2.2.0-bin/blob/master/bin/winutils.exe
最后执行成功：