Hadoop MapReduce 编写例子

编写一个简单的WordCount例子


WordCount.java

/**
 * 简单的单词计数器
 */

/**
 *
 * @author Neo neosfung_gmail_com
 * @version 1.0 2012-11-11
 */
import java.io.IOException;
import java.util.Iterator;
import java.util.StringTokenizer;

import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.FileInputFormat;
import org.apache.hadoop.mapred.FileOutputFormat;
import org.apache.hadoop.mapred.JobClient;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.MapReduceBase;
import org.apache.hadoop.mapred.Mapper;
import org.apache.hadoop.mapred.OutputCollector;
import org.apache.hadoop.mapred.Reducer;
import org.apache.hadoop.mapred.Reporter;
import org.apache.hadoop.mapred.TextInputFormat;
import org.apache.hadoop.mapred.TextOutputFormat;

public class WordCount {

	public static class Map extends MapReduceBase implements
			Mapper<LongWritable, Text, Text, IntWritable> {
		private final static IntWritable one = new IntWritable(1);
		private final Text word = new Text();

		/**
		 * map函数继承自MapReduceBase, 并且实现了Mapper接口, 此接口是一个泛型类型,它有4种形式的参数,
		 * 分别用来指定map的输入key类型, 输入value值类型, 输出key值类型和输出value值类型.
		 * 在本例中,输入使用的是TextInputFormat, 它的输出key值是LongWritable类型, 输出value值是Text类型.
		 * 根据本例, 需要输出的是<Text, IntWritable>的形式, 所以输出的key值类型是Text,
		 * 输出的value类型是IntWritable.
		 */
		@Override
		public void map(LongWritable key, Text value,
				OutputCollector<Text, IntWritable> output, Reporter reporter)
				throws IOException {
			String line = value.toString();
			StringTokenizer tokenizer = new StringTokenizer(line);
			while (tokenizer.hasMoreTokens()) {
				word.set(tokenizer.nextToken());
				output.collect(word, one);
			}

		}
	}

	public static class Reduce extends MapReduceBase implements
			Reducer<Text, IntWritable, Text, IntWritable> {

		/**
		 * reduce函数的输入以map的输出作对应, 因此reduce的输入类型是<Text, IntWritable>.
		 */
		@Override
		public void reduce(Text key, Iterator<IntWritable> values,
				OutputCollector<Text, IntWritable> output, Reporter reporter)
				throws IOException {
			int sum = 0;
			while (values.hasNext()) {
				sum += values.next().get();

			}
			output.collect(key, new IntWritable(sum));

		}
	}

	/**
	 * @param args
	 * @throws IOException
	 */
	public static void main(String[] args) throws IOException {
		// TODO Auto-generated method stub
		JobConf conf = new JobConf(WordCount.class);
		conf.setJobName("wordcount");

		// 设定输出的key和value类型
		conf.setOutputKeyClass(Text.class);
		conf.setOutputValueClass(IntWritable.class);

		// 设定各个作业的类
		conf.setMapperClass(Map.class);
		conf.setCombinerClass(Reduce.class);
		conf.setReducerClass(Reduce.class);

		// 设定输入输出的格式
		conf.setInputFormat(TextInputFormat.class);
		conf.setOutputFormat(TextOutputFormat.class);

		FileInputFormat.setInputPaths(conf, new Path(args[0]));
		FileOutputFormat.setOutputPath(conf, new Path(args[1]));

		JobClient.runJob(conf);
	}

}



编译:

javac -classpath ~/hadoop/hadoop-core-1.0.3.jar WordCount.java

打包:

jar -cvf WordCount.jar -C ./ .

运行,其中input为hdfs上的输入文件夹:

hadoop jar WordCount.jar WordCount input output



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