1.写完计数程序打包成jar
只要class文件即可
2.上传到node1上
3.hadoop jar wordcount.jar com.hadoop.mr.WordCount
hdfs dfs -ls /data/output
hdfs dfs -cat /data/output/part-r-00000
也可以把内容copy到当前的目录
hdfs dfs -get /data/output/* ./
package com.hadoop.mr.count;
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 void main(String[] args) throws Exception {
Configuration configuration = new Configuration(true);
Job job = Job.getInstance(configuration);
job.setJarByClass(WordCount.class);
job.setJobName("wordcount");
Path input = new Path("/data/test3.txt");
FileInputFormat.addInputPath(job, input);
Path output = new Path("/data/output2");
FileOutputFormat.setOutputPath(job, output);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(IntWritable.class);
job.setMapperClass(MyMapper.class);
job.setReducerClass(MyReducer.class);
// Submit the job, then poll for progress until the job is complete
job.waitForCompletion(true);
}
}
class MyMapper 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);
}
}
}
class MyReducer 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);
}
}
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