大數據之Hadoop學習（十二）對數據文件中的數據進行去重基於（MapReduce編程）

一、輸入數據如下所示：

要求輸出如下所示：

二、創建相關文件

• 先在HDFS創建DateRemove文件夾

./bin/hdfs dfs -mkdir /user/hadoop/DateRemove

用ls查看文件是否創建成功

./bin/hdfs dfs -ls /user/hadoop

• 在HDFS下創建一個名稱爲DateRemove/input的目錄

./bin/hdfs dfs -mkdir /user/hadoop/DateRemove/input

• 創建file1.txt和file2.txt,並寫入數據

• 將file1.txt和file2.txt傳到hdfs的/user/hadoop/DateRemove/input文件夾中

./bin/hdfs dfs -put ./file1.txt  /user/hadoop/DateRemove/input
./bin/hdfs dfs -ls  /user/hadoop/DateRemove/input

在用ls查看：

上圖說明確實存在file1.txt和file2.txt。

三、JAVA代碼

①DedupMapper.java

package Data_De_duplication;

import java.io.IOException;

import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;

public class DedupMapper extends Mapper<LongWritable, Text, Text, NullWritable> {

    private static Text field = new Text();  

    @Override  
    protected void map(LongWritable key, Text value, Context context)  
            throws IOException, InterruptedException {  

        field = value;  
        context.write(field, NullWritable.get());  

    }  

}

②DedupReducer.java

package Data_De_duplication;

import java.io.IOException;

import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;

public class DedupMapper extends Mapper<LongWritable, Text, Text, NullWritable> {

    private static Text field = new Text();  

    @Override  
    protected void map(LongWritable key, Text value, Context context)  
            throws IOException, InterruptedException {  

        field = value;  
        context.write(field, NullWritable.get());  

    }  

}

③DedupRunner.java

package Data_De_duplication;

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.NullWritable;
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 DedupRunner {
    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
        Configuration conf = new Configuration();
        Job job = Job.getInstance(conf);

        job.setJarByClass(DedupRunner.class);

        job.setMapperClass(DedupMapper.class);
        job.setReducerClass(DedupReducer.class);

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

        FileInputFormat.setInputPaths(job, new Path("hdfs://localhost:9000/user/hadoop/DateRemove/input"));
        
        // 指定處理完成之後的結果所保存的位置
        FileOutputFormat.setOutputPath(job, new Path("hdfs://localhost:9000/user/hadoop/DateRemove/output"));

        job.waitForCompletion(true);

    }
}

點擊剛創建的DedupRunner.java，選擇Run As -> Run Configurations，設置運行時的相關參數如下

運行結果：

確實自動生成了output文件

用cat命令查看運行完成時的part-r-00000文件，結果如下

./bin/hdfs dfs -cat  /user/hadoop/DateRemove/output/part-r-00000

對比發現，發現重複的數據已去重成功。