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  • 初学Hadoop之WordCount词频统计

    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

      

    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

      

      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。

      

      

    4、查看结果

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

      

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

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  • 原文地址:https://www.cnblogs.com/hehaiyang/p/4478233.html
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