1. 开发环境
   Intellij idea 14
   jdk: 1.7.71
   spark: 1.1.0
   hadoop: 2.4.0
   scala: 2.11.1
   maven: 3.2.5
2. 创建maven工程
   在src目录下创建main/java的source文件（在File –> Project Structure…–>Modules–>Sources右键添加目录和修改目录为source类型）
   

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在File –> Project Structure…–>Libraries添加spark-assembly-1.1.0-hadoop2.4.0的依赖包

3. java目录下编写Wordcount例子程序

import org.apache.spark.SparkConf;import org.apache.spark.api.java.JavaPairRDD;import org.apache.spark.api.java.JavaRDD;import org.apache.spark.api.java.JavaSparkContext;import org.apache.spark.api.java.function.FlatMapFunction;import org.apache.spark.api.java.function.Function2;import org.apache.spark.api.java.function.PairFunction;import scala.Tuple2;import java.util.Arrays;import java.util.List;import java.util.regex.Pattern;public class JavaWordCount {    private static final Pattern SPACE = Pattern.compile(" ");    public static void main(String[] args)throws Exception {        SparkConf sparkConf = new SparkConf().setAppName("JavaWordCount");        String srcPath = null;        String desPath = "/apps/ca/yanh/output";        if (args.length == 1) {            srcPath = args[0];        } else if(args.length == 2) {            srcPath = args[0];            desPath = args[1];        }        else {            System.out.println("Usage: java -jar jarName 
     
       [des]");            System.exit(1);        }        JavaSparkContext jsc = new JavaSparkContext(sparkConf);        JavaRDD
      
        lines = jsc.textFile(srcPath, 1);        System.out.println("Begin to split!");        JavaRDD
       
         words = lines.flatMap(new FlatMapFunction
        
         () {            @Override            public Iterable
         
           call(String s) throws Exception {                return Arrays.asList(SPACE.split(" "));            }        });        System.out.println("Begin to map!");        JavaPairRDD
          
            ones = words.mapToPair(new PairFunction
           
            () { @Override public Tuple2
            
              call(String s) throws Exception { return new Tuple2
             
              (s, 1); } }); System.out.println("Begin to reduce!"); JavaPairRDD
              
                counts = ones.reduceByKey(new Function2
               
                () { @Override public Integer call(Integer i1, Integer i2) throws Exception { return i1 + i2; } }); System.out.println("Begin to save!"); /*List
                
                 
                  > output = counts.collect(); for(Tuple2
                   tuple: output) { System.out.println(tuple._1() + ": " + tuple._2()); }*/ counts.saveAsTextFile(desPath); jsc.stop(); }}
                 
                
               
              
             
            
           
          
         
        
       
      
     

1. 打包成jar包
   在File –> Project Structure…–>Artifacts点击绿色“+”，Add–>JAR–>From Modules with Dependencies
   

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输入main class入口函数名，将Output Layout下所有jar包删掉（因为spark运行环境已经包含了这些包），然后Apply

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编译程序：Build–>Build Artifacts…，然后选择要编译的项目进行编译

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在当前工程生成的out目录下就可以找到输出的jar包

1. 运行程序
   将jar包上传至spark集群，然后使用spark-submit进行提交运行（spark-submit具体参数自行查看）
   提交命令：spark-submit –class JavaWordCount ~/JavaWordCount.jar /apps/ca/yanh/data/README.md
   

这是由于缺少本地库依赖和压缩包引起。

在此提供了这个包： spark-submit命令: spark-submit –driver-library-path :/usr/lib/hadoop/lib/native/ –jars /usr/lib/hadoop/lib/hadoop-lzo-0.6.0.jar –class JavaWordCount ~/JavaWordCount.jar /apps/ca/yanh/data/README.md

来自yhao2014