mapreduce辅助排序和序列化的实例练习-CFANZ编程社区

需求

数据

0000001 Pdt_01  222.8
0000002 Pdt_06  722.4
0000001 Pdt_05  25.8
0000003 Pdt_01  222.8
0000003 Pdt_01  33.8
0000002 Pdt_03  522.8
0000002 Pdt_04  122.4

订单号 x 价格
希望的到的数据: 根据订单号得到分区，每个分区清洗出最大的价格
分区1
0000001 222.8
分区2
0000002 722.4
分区3
0000003 222.8

思路

这个每行数据可以定义一个orderbean，实现序列化接口，自定义比较器，先根据id排序，然后根据价格倒序，重写写tostring方法（这里定义输出格式）
map的key就是一个orderben，value可以为空
分组; 根据orderbean的id进行分组，因为上面一步价格倒序了，所以分组得到的第一条数据都是最大的价格，满足要求
分区，根据订单号id进行分区
reduce合并，输出key orderbean，value可以为空
自定义main函数，将map, 分组比较器，分区，reduce等写在job中，执行job任务，指定到文件夹输出即可

码代码

bean

@Setter
@Getter
public class OrderBean implements WritableComparable<OrderBean> {
    private int id;
    private double price;

    @Override
    public int compareTo(OrderBean o) {
        if (this.id > o.id) {
            return 1;
        } else if (this.id < o.id) {
            return -1;
        } else {
            return this.price - o.price >  0 ? -1 : 1;
        }
    }

    @Override
    public void write(DataOutput output) throws IOException {
        output.writeInt(this.id);
        output.writeDouble(this.price);
    }

    @Override
    public void readFields(DataInput input) throws IOException {
        this.id = input.readInt();
        this.price = input.readDouble();
    }

    @Override
    public String toString() {
        return this.id + "\t" + this.price;
    }
}

map

//0000002   Pdt_04  122.4
//mapreduce根据key进行排序，所以k2，v2的类型应该为 FlowBean, NullWritable
public class OrderMap extends Mapper<LongWritable, Text, OrderBean, NullWritable> {
    OrderBean bean = new OrderBean();

    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        String s = value.toString();
        String[] split = s.split("\t");
        bean.setId(Integer.parseInt(split[0]));
        bean.setPrice(Double.parseDouble(split[2]));
        context.write(bean, NullWritable.get());
    }

}

分组比较器（辅助排序）

import org.apache.hadoop.io.WritableComparable;
import org.apache.hadoop.io.WritableComparator;

public class GroupComparator extends WritableComparator {
    public GroupComparator() {
        //按照自定义的orderbean排序，第二个参数是辅助排序
        super(OrderBean.class, true);
    }

    @Override
    public int compare(WritableComparable a, WritableComparable b) {
        OrderBean  oa = (OrderBean)a;
        OrderBean  ob = (OrderBean)b;
         if(oa.getId() > ob.getId()){
             return 1;
         }else if(oa.getId() < ob.getId()){
             return -1;
         }else{
             return 0;
         }
    }
}

分区

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

public class OrderPartition extends Partitioner<OrderBean, NullWritable> {

    @Override
    public int getPartition(OrderBean orderBean, NullWritable nullWritable, int i) {
        return (orderBean.getId() & Integer.MAX_VALUE) % 3;
    }
}

reduce

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

import java.io.IOException;

public class OrderReduce extends Reducer<OrderBean, NullWritable, OrderBean, NullWritable> {

    @Override
    protected void reduce(OrderBean bean, Iterable<NullWritable> values, Context context) throws IOException, InterruptedException {
        context.write(bean, NullWritable.get());
    }

}

测试job任务

public class MainOrder {
    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
        args = new String[]{"F:\\input\\GroupingComparator.txt", "F:\\output\\GroupingComparator4"};
        //获取配置文件
        Configuration conf = new Configuration();
        //创建job任务
        Job job = Job.getInstance(conf);
        // 加载jar包
        job.setJarByClass(MainOrder.class);

        //指定Map类和map的输出类型 Text, NullWritable
        //关联map和reduce
        job.setMapperClass(OrderMap.class);
        job.setMapOutputKeyClass(OrderBean.class);
        job.setMapOutputValueClass(NullWritable.class);
        // 设置最终输出类型
        job.setReducerClass(OrderReduce.class);
        job.setOutputKeyClass(OrderBean.class);
        job.setOutputValueClass(NullWritable.class);

        //指定辅助排序
        job.setGroupingComparatorClass(GroupComparator.class);
        //设置分区
        job.setPartitionerClass(OrderPartition.class);
        job.setNumReduceTasks(3);

        //指定数据输入的路径和输出的路径
        FileInputFormat.setInputPaths(job, new Path(args[0]));
        FileOutputFormat.setOutputPath(job, new Path(args[1]));

        job.waitForCompletion(true);
    }
}