搭个新环境时总要折腾一下,于是干脆记下来。
程序:
package com.my; 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 Text word = new Text(); 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>
{
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));
}
} public static void main(String[] args) throws Exception
{
JobConf conf = new JobConf(WordCount. class );
conf.setJobName("wordcount" ); conf.setOutputKeyClass(Text.class );
conf.setOutputValueClass(IntWritable.class ); conf.setMapperClass(Map.class );
conf.setCombinerClass(Reduce.class );
conf.setReducerClass(Reduce.class ); 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);
}
}
编译命令:
mkdir Myjava javac -classpath hadoop-core-1.1.2.jar -d Myjava WordCount.java jar -cvf WordCount.jar -C Myjava .
运行命令:
bin/hadoop jar WordCount.jar com.my.WordCount /src/test.txt /output
这一次的是基于hadoop 1.1.2程序。