hadoop platform write wordcount word frequency statistics

Hadoop platform write wordcount word frequency statistics

maven dependency

 <dependency>
        <groupId>org.apache.hadoop</groupId>
        <artifactId>hadoop-core</artifactId>
        <version>1.2.1</version>
    </dependency>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-common</artifactId>
            <version>2.7.2</version>
        </dependency>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-hdfs</artifactId>
            <version>2.7.2</version>
        </dependency>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-mapreduce-client-core</artifactId>
            <version>2.7.2</version>
        </dependency>
    <!-- https://mvnrepository.com/artifact/org.apache.hadoop/hadoop-client -->
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-client</artifactId>
            <version>2.7.2</version>
        </dependency>

map class

  package WordCount;

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.OutputCollector;
import org.apache.hadoop.mapreduce.Mapper;

import java.io.IOException;

//LongWritable 距离文件第一个差多少偏移量 为key
//值为Text
public class WordCountMapper extends Mapper<LongWritable, Text, Text, IntWritable> {
    protected void map(LongWritable key, Text value,Context context) throws IOException, InterruptedException {

        //一行数据
        String line = value.toString();

        //按照空格切分数据
        String[] words = line.split(" ");

        //遍历数组,把单词变成(word,1)形式交给框架
        for (String word : words) {
            System.out.println(word);
            context.write(new Text(word), new IntWritable(1));
            //(word,1)
        }
    }
}

reduce class

package WordCount;

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;

import java.io.IOException;

public class WordCountReducer extends Reducer<Text, IntWritable,Text,IntWritable> {
    @Override
    //key 1个key, values 很多个1
    protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
        int sum = 0;
        for(IntWritable val:values)
        {
            sum+=val.get();
        }
        context.write(key,new IntWritable(sum));
    }
}

Driver class

package WordCount;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
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.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

public class WordCount {
    public static void main(String[] args) throws Exception{

        Job job = Job.getInstance(new Configuration());

        //设置类路径
        job.setJarByClass(WordCount.class);

        job.setMapperClass(WordCountMapper.class);
        job.setReducerClass(WordCountReducer.class);

        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(IntWritable.class);

        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);

        FileInputFormat.setInputPaths(job,new Path(args[0]));
        FileOutputFormat.setOutputPath(job,new Path(args[1]));

        boolean b=job.waitForCompletion(true);
        System.out.println(b?0:1);
	}
}

Set the parameters, enter the file path, and output path (this file is not available before running) to
complete.

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Origin blog.csdn.net/WangaWen1229/article/details/105578857