由于Hadoop是一个基于Java编写的开源项目,因此其代码也是用Java编写的。以下是一个简单的Hadoop MapReduce程序示例代码:

import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
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.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<LongWritable, Text, Text, IntWritable>{

    private final static IntWritable one = new IntWritable(1);
    private Text word = new Text();

    public void map(LongWritable key, Text value, Context context
                    ) throws IOException, InterruptedException {
      String[] words = value.toString().split(" ");
      for (String w : words) {
        word.set(w);
        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);
  }
}

这个程序实现了一个简单的单词计数功能。首先,Mapper类将输入的文本数据按照空格分隔成单个单词,并将每个单词输出为一个键值对,其中键为单词,值为1。接下来,Combiner类将相同的键值对进行合并,以便在Reducer类中更高效地进行计数操作。最后,Reducer类对所有的键值对进行累加,得到最终的单词计数结果。整个程序的输入和输出都是文本文件。要运行这个程序,需要将其打包成一个jar文件,并将jar文件提交到Hadoop集群中运行

hadoop的代码

原文地址: https://www.cveoy.top/t/topic/g0ZM 著作权归作者所有。请勿转载和采集!

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