hadoop 在eclipse中输出日志

import java.io.File;
import java.io.IOException;
import java.util.StringTokenizer;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
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.output.FileOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;

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 {
			System.out.println("StringTokenizer:" + value.toString());
			StringTokenizer itr = new StringTokenizer(value.toString());
			while (itr.hasMoreTokens()) {
				word.set(itr.nextToken());
				context.write(word, one);
			}
			//hadoop 在eclipse中输出日志 
			org.apache.hadoop.mapreduce.Counter count = context.getCounter(
					"map 中的值value", value.toString());
			count.increment(1);
		}
	}

	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);		
			//在eclipse中输出日志 
			org.apache.hadoop.mapreduce.Counter count= context.getCounter("reduce中的值key",
					key.toString());
			count.increment(1);
			
			context.write(key, result);
		}
	}

	public static void main(String[] args) throws Exception {
		Configuration conf = new Configuration();
		//conf.set("mapred.job.tracker", "192.168.0.58:9001");
		//conf.set("mapreduce.job.counters.limit", "1400");
		//Error: Exceeded limits on number of counters 的解决方法
		/**
		 ./conf/mapred-site.xml 追加：如果是使用eclipse的话，修改hadoop-core-1.1.2.jar下的mapred-default.xml 
		 <property> 
		 <name>mapreduce.job.counters.limit</name>
		 <value>14000</value>
		 </property>
		 */
		System.out.println(new File(".").getAbsolutePath());
		String[] otherArgs = new GenericOptionsParser(conf, args)
				.getRemainingArgs();
		if (otherArgs.length != 2) {
			System.err.println("Usage: wordcount <in> <out>");
			System.exit(2);
		}
		Job job = new Job(conf, "word count");
		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, new Path(otherArgs[0]));
		Path outputPath=new Path(otherArgs[1]);
		FileSystem fs=outputPath.getFileSystem(conf);
		if(fs.exists(outputPath))
		{
			fs.delete(outputPath);
		}
		FileOutputFormat.setOutputPath(job, outputPath);
		System.exit(job.waitForCompletion(true) ? 0 : 1);
	}
}