1、WordCount源码

  将源码文件WordCount.java放到Hadoop2.6.0文件夹中。

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.output.FileOutputFormat; 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();
Job job = Job.getInstance(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(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}

2、编译源码

$ bin/hadoop com.sun.tools.javac.Main WordCount.java  #将WordCount.java编译成三个.class文件
$ jar cf wc.jar WordCount*.class #将三个.class文件打包成jar文件

  初学Hadoop之WordCount词频统计-LMLPHP

3、运行

  新建input文件夹,用于存放需要统计的文本。

cd /opt/hadoop-2.6.0
mkdir input

  复制hadoop-2.6.0文件夹下的txt文件到input文件夹下。

cp *.txt /opt/hadoop-2.6.0/input

  初学Hadoop之WordCount词频统计-LMLPHP

  运行命令。

bin/hadoop jar wc.jar WordCount /opt/hadoop-2.6.0/input /opt/hadoop-2.6.0/output #自动生成output文件夹,用于存放分词统计结果。

  初学Hadoop之WordCount词频统计-LMLPHP

  初学Hadoop之WordCount词频统计-LMLPHP

4、查看结果

bin/hdfs dfs -cat /opt/hadoop-2.6.0/output/part-r-00000

  初学Hadoop之WordCount词频统计-LMLPHP

  至此,WordCount词频统计运行成功,Hadoop单机模式环境搭建成功。

05-08 15:47