在Windows下的Eclipse中如何将WordCount程序提交到集群运行,能调试

参考内容: http://blog.csdn.net/deng2012web/article/details/51931686

java程序：

package com.hq;

import org.apache.hadoop.conf.Configuration;
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.Iterator;
import java.util.List;
import java.util.regex.Pattern;

public final class JavaWordCount {
  private static final Pattern SPACE = Pattern.compile(" ");

  public static void main(String[] args) throws Exception {

    if (args.length < 1) {
      System.err.println("Usage: JavaWordCount ");
      System.exit(1);
    }
   
    Configuration conf = new Configuration();
    conf.set("fs.defaultFS", "hdfs://master:9000");
    conf.set("mapreduce.jobtracker.address", "master:9001");
    conf.set("yarn.resourcemanager.address", "master:8032");
    conf.set("mapreduce.framework.name", "yarn");
    conf.set("mapreduce.opp-submission.cross-platform", "true");
    conf.set("yarn.resourcemanager.scheduler.address", "master:8030");

    SparkConf sparkConf = new SparkConf().setAppName("JavaWordCount");
    JavaSparkContext ctx = new JavaSparkContext(sparkConf);
    JavaRDD lines = ctx.textFile(args[0], 1);

    JavaRDD words = lines.flatMap(new FlatMapFunction() {
      @Override
      public Iterator call(String s) {
          return Arrays.asList(SPACE.split(s)).iterator();
        }
    });

    JavaPairRDD ones = words.mapToPair(new PairFunction() {
      @Override
      public Tuple2 call(String s) {
        return new Tuple2(s, 1);
      }
    });

    JavaPairRDD counts = ones.reduceByKey(new Function2() {
      @Override
      public Integer call(Integer i1, Integer i2) {
        return i1 + i2;
      }
    });

    List> output = counts.collect();
    for (Tuple2 tuple : output) {
      System.out.println(tuple._1() + ": " + tuple._2());
    }
    ctx.stop();
  }
}

有关脚本：

spark-submit --master spark://master:7077 --name WordCountByscala --class com.hq.WordCount --executor-memory 1G --total-executor-cores 2 jars/spark-wordcount-in-scala.jar hdfs://master:9000/user/word.txt
spark-submit --master spark://master:7077 --name JavaWordCountByHQ --class com.hq.JavaWordCount --executor-memory 1G --total-executor-cores 2 jars/spark-wordcount-in-scala.jar hdfs://master:9000/user/word.txt

spark-submit --master spark://192.168.0.76:7077 --name JavaWordCountByHQ --class com.hq.JavaWordCount --executor-memory 1G --total-executor-cores 2 spark-wordcount-in-scala.jar hdfs://192.168.0.76:9000/user/word.txt

spark-submit --master spark://master --name JavaWordCountByHQ --class com.hq.JavaWordCount --executor-memory 1G --total-executor-cores 2 spark-wordcount-in-scala.jar hdfs://master:9000/user/word.txt