[Hadoop] 50030/jobtracker.jsp监控不到eclipse提交的作业

 搭建好eclipse hadoop开发环境后，一般会用hadoop自带的WordCount做个测试，其自带的WordCount.java如下：

package org.apache.hadoop.examples;import java.io.IOException;import java.util.StringTokenizer;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.fs.Path;import org.apache.hadoop.io.IntWritable;import org.apache.hadoop.io.Text;import org.apache.hadoop.mapreduce.Job;import org.apache.hadoop.mapreduce.Mapper;import org.apache.hadoop.mapreduce.Reducer;import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;import org.apache.hadoop.util.GenericOptionsParser;import org.apache.log4j.PropertyConfigurator;public class WordCount {  public static class TokenizerMapper        extends Mapper<Object, Text, Text, IntWritable>{        private final static IntWritable one = new IntWritable(1);    private Text word = new Text();          public void map(Object key, Text value, Context context                    ) throws IOException, InterruptedException {      StringTokenizer itr = new StringTokenizer(value.toString());      while (itr.hasMoreTokens()) {        word.set(itr.nextToken());        context.write(word, one);      }    }  }    public static class IntSumReducer        extends Reducer<Text,IntWritable,Text,IntWritable> {    private IntWritable result = new IntWritable();    public void reduce(Text key, Iterable<IntWritable> values,                        Context context                       ) throws IOException, InterruptedException {      int sum = 0;      for (IntWritable val : values) {        sum += val.get();      }      result.set(sum);      context.write(key, result);    }  }  public static void main(String[] args) throws Exception {    Configuration conf = new Configuration();        //set inpath,outpath    Path inpath=new Path("/test/input/file1");    Path outpath=new Path("/test/output/output4");        Job job = new Job(conf, "mango");    job.setInputFormatClass(TextInputFormat.class);    job.setOutputFormatClass(TextOutputFormat.class);    job.setJarByClass(WordCount.class);    job.setMapperClass(TokenizerMapper.class);    //job.setCombinerClass(IntSumReducer.class);    job.setReducerClass(IntSumReducer.class);    job.setOutputKeyClass(Text.class);    job.setOutputValueClass(IntWritable.class);         FileInputFormat.addInputPath(job, inpath);    FileOutputFormat.setOutputPath(job,outpath);    System.out.println("开始执行");    System.exit(job.waitForCompletion(true) ? 0 : 1);      }}

如果此时你run java aplication,你的程序只会在eclipse中虚拟的一个云环境中运行，而不会跑上云端去运行，所以无法再master:50070/jobtracker.jsp页面中监控到该作业；需要在main方法中添加几行代码，代码附录如下：

//在你的文件地址前自动添加：hdfs://master:9000/  conf.set("fs.default.name", "hdfs://master:9000/");  conf.set("hadoop.job.user","mango");    //指定jobtracker的ip和端口号，master在/etc/hosts中可以配置  conf.set("mapred.job.tracker","master:9001");