Hadoop版Helloworld之wordcount运行示例

Posted 2020-08-27 向前展望，倒后推理

1.编写一个统计单词数量的java程序，并命名为wordcount.java，代码如下：

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.声明java环境变量：

export JAVA_HOME=/usr/java/default
export PATH=${JAVA_HOME}/bin:${PATH}
export HADOOP_CLASSPATH=${JAVA_HOME}/lib/tools.jar

其中JAVA_HOME根据自己安装java的实际路径进行配置。

注意：如果不声明以上环境变量，那么在以后运行时，将会收到错误提示：

3.编译并创建jar包。

bin/hadoop com.sun.tools.javac.Main WordCount.java
jar cf wc.jar WordCount*.class

4.运行第三步骤生成的wc.jar包。此时要注意，output文件夹不要手工创建，系统运行后会自动创建。

bin/hadoop jar wc.jar WordCount /user/root/wordcount/input /user/root/wordcount/output

正常运行结束后，会在outPut文件夹下生成part-r-00000及__SUCCESS两个文件，其中part-r-00000存储分析结果。运行命令：

bin/hadoop fs -cat /user/root/wordcount/output/part-r-00000

即可查看分析结果，如下图所示：

至此，本示例完成。