MapReduce 自定义partitioner

需求：将以下数据进行分开处理，其中第六个字段表示开奖结果数值，现在以15为分界点，将15以上的结果保存到一个文件，15以下的结果保存到一个文件。

（以图片数据为例）

定义mapper类：

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

import java.io.IOException;

public class MapDemo01 extends Mapper<LongWritable, Text,Text, NullWritable> {
    
    
    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
    
    

        context.write(value,NullWritable.get());
    }
}

定义reducer类：

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

import java.io.IOException;

public class ReduceDemo01 extends Reducer<Text, NullWritable,Text, NullWritable> {
    
    
    @Override
    protected void reduce(Text key, Iterable<NullWritable> values, Context context) throws IOException, InterruptedException {
    
    
        context.write(key,NullWritable.get());
    }
}

自定义partitioner类：

import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Partitioner;

public class Partition extends Partitioner<Text, NullWritable> {
    
    

    @Override
    public int getPartition(Text text, NullWritable nullWritable, int i) {
    
    

        String result = text.toString().split("\\t")[5];
        if (Integer.parseInt(result) > 15){
    
    
            return 1;
        }else{
    
    
            return 0;
        }
    }

程序main函数入口：

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 DriverDemo01 {
    
    
    public static void main(String[] args) throws Exception {
    
    

        Job job = Job.getInstance(new Configuration(), "Partitioner");

        job.setJarByClass(DriverDemo01.class);

        job.setMapperClass(MapDemo01.class);
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(NullWritable.class);

        job.setReducerClass(ReduceDemo01.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(NullWritable.class);


        job.setPartitionerClass(Partition.class);
        job.setNumReduceTasks(5);


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

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

代码编写完毕后将代码打成jar包放到服务器上面去运行

hadoop jar jar包名 main方法路径 读取路径 输出路径