引言
通过Java编写Spark应用程序的HelloWorld，虽然有点寒碜，没用Scala简洁明了，但还是得尝试和记录下。
环境
Windows7
Eclipse+Maven
Jdk1.7
Ubuntu 14.04
步骤一：在eclipse中创建maven工程，过程很简单，不详述。
pom文件为：
<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">
<groupId>edu.berkeley</groupId>
<artifactId>SparkProj</artifactId>
<modelVersion>4.0.0</modelVersion>
<name>Spark Project</name>
<packaging>jar</packaging>
<version>1.0</version>
<dependencies>
<dependency> <!-- Spark dependency -->
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.10</artifactId>
<version>1.3.0</version>
</dependency>
</dependencies>
</project>
步骤二：编写核心逻辑代码
功能很简单，统计集群中Spark根目录下README.md中有多少行包含a，多少行包含b。
说实话该功能用Scala编写十分简单，Java实在是恶心。
package edu.berkeley.SparkProj;
/* SimpleApp.java */
import org.apache.spark.api.java.*;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.function.Function;
public class SimpleApp {
public static void main(String[] args) {
String logFile = "file:///home/fulong/Spark/spark-1.3.0-bin-hadoop2.4/README.md"; // Should be some file on your system
SparkConf conf = new SparkConf().setAppName("Simple Application");
JavaSparkContext sc = new JavaSparkContext(conf);
JavaRDD<String> logData = sc.textFile(logFile).cache();
long numAs = logData.filter(new Function<String, Boolean>() {
public Boolean call(String s) { return s.contains("a"); }
}).count();
long numBs = logData.filter(new Function<String, Boolean>() {
public Boolean call(String s) { return s.contains("b"); }
}).count();
System.out.println("Lines with a: " + numAs + ", lines with b: " + numBs);
}
}
步骤三：Windows下CMD中进入到工程根目录下打包
D:\WorkSpace2015\SparkProj>mvn package
生成jar包：
D:\WorkSpace2014\SparkProj\target\SparkProj-1.0.jar
步骤四：将该包通过WinSCP工具拷贝到集群某节点的目录下
/home/fulong/Workspace/Spark/SparkProj-1.0.jar
最后一步：通过spark-submit提交程序到Spark集群
[email protected]:~/Spark/spark-1.3.0-bin-hadoop2.4$ ./bin/spark-submit --class edu.berkeley.SparkProj.SimpleApp --master yarn-client /home/fulong/Workspace/Spark/SparkProj-1.0.jar
运行结果，包含a的有60行，包含b的有29行：
