【Hadoop离线基础总结】MapReduce案例之自定义groupingComparator

MapReduce案例之自定义groupingComparator

---

求取Top 1的数据

• 需求
  
  求出每一个订单中成交金额最大的一笔交易

订单id			商品id	成交金额
Order_0000005	Pdt_01	222.8
Order_0000005	Pdt_05	25.8
Order_0000002	Pdt_03	322.8
Order_0000002	Pdt_04	522.4
Order_0000002	Pdt_05	822.4
Order_0000003	Pdt_01	222.8

• 代码实现

自定义一个javaBean，命名为OrderBean

package cn.itcast.demo5;

import org.apache.hadoop.io.WritableComparable;

import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;

public class OrderBean implements WritableComparable<OrderBean> {
    //定义orderId和price变量
    private String orderId;
    private Double price;

    /**
     * 重写compareTo方法
     *
     * @param o
     * @return
     */
    @Override
    public int compareTo(OrderBean o) {
        //先对orderId进行比较，如果相同，将它们的price放一起比较，不同就不比较
        int result = this.orderId.compareTo(o.orderId);
        //进行判断
        if (result == 0) {
            int i = this.price.compareTo(o.price);
            return -i;      //返回i求取最小值，返回-i求取最大值
        }
        return result;

    }

    @Override
    public void write(DataOutput out) throws IOException {
        out.writeUTF(orderId);
        out.writeDouble(price);
    }

    @Override
    public void readFields(DataInput in) throws IOException {
        this.orderId = in.readUTF();
        this.price = in.readDouble();
    }

    //生成get(),set()方法

    public String getOrderId() {
        return orderId;
    }

    public void setOrderId(String orderId) {
        this.orderId = orderId;
    }

    public double getPrice() {
        return price;
    }

    public void setPrice(Double price) {
        this.price = price;
    }

    //生成toString()方法

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

定义一个Mapper类

package cn.itcast.demo5;

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 GroupMapper extends Mapper<LongWritable, Text, OrderBean, NullWritable> {
    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        //分割获取到的数据
        String[] split = value.toString().split("\t");

        //创建orderBean对象
        OrderBean orderBean = new OrderBean();
        //给orderId赋值
        orderBean.setOrderId(split[0]);
        //给price赋值
        orderBean.setPrice(Double.valueOf(split[2]));

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

自定义分区(Partition)规则

package cn.itcast.demo5;

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

public class GroupPartitioner extends Partitioner<OrderBean, NullWritable> {
    /**
     * 重写分区方法
     *
     * @param orderBean
     * @param nullWritable
     * @param i
     * @return
     */
    @Override
    public int getPartition(OrderBean orderBean, NullWritable nullWritable, int i) {
        //参照HashPartitioner的重写方法
        return (orderBean.getOrderId().hashCode() & Integer.MAX_VALUE) % i;
    }
}

自定义分组(groupingComparator)规则

package cn.itcast.demo5;

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

public class GroupComparator extends WritableComparator {

    //重写无参构造方法，定义反射出来的对象是OrderBean类
    public GroupComparator() {
        super(OrderBean.class, true);
    }

    @Override
    public int compare(WritableComparable a, WritableComparable b) {
        OrderBean first = (OrderBean) a;
        OrderBean second = (OrderBean) b;
        //比较orderId，如果相同就认为是同一组数据
        return first.getOrderId().compareTo(second.getOrderId());
    }
}

定义一个Reducer类

package cn.itcast.demo5;

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

import java.io.IOException;

public class GroupReducer extends Reducer<OrderBean, NullWritable, OrderBean, NullWritable> {
    /**
     * 直接将收到的k2,v2的值转换为k3,v3输出
     *
     * @param key
     * @param values
     * @param context
     * @throws IOException
     * @throws InterruptedException
     */
    @Override
    protected void reduce(OrderBean key, Iterable<NullWritable> values, Context context) throws IOException, InterruptedException {
        context.write(key, values.iterator().next());
    }
}

程序main函数入口

package cn.itcast.demo5;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

public class GroupMain extends Configured implements Tool {
    @Override
    public int run(String[] args) throws Exception {
        //获取Job对象
        Job job = Job.getInstance(super.getConf(), "myGroupComparator");
        //输入数据，设置输入路径
        job.setInputFormatClass(TextInputFormat.class);
        TextInputFormat.setInputPaths(job, new Path("file:////Volumes/赵壮备份/大数据离线课程资料/5.大数据离线第五天/自定义groupingComparator/input/orders.txt"));

        //自定义Map逻辑
        job.setMapperClass(GroupMapper.class);
        //设置k2,v2输出类型
        job.setMapOutputKeyClass(OrderBean.class);
        job.setMapOutputValueClass(NullWritable.class);

        //自定义Partition逻辑
        job.setPartitionerClass(GroupPartitioner.class);

        //自定义分组逻辑
        job.setGroupingComparatorClass(GroupComparator.class);

        //自定义reduce逻辑
        job.setReducerClass(GroupReducer.class);
        //设置k3,v3输出类型
        job.setOutputKeyClass(OrderBean.class);
        job.setOutputValueClass(NullWritable.class);

        //输出数据，设置输出路径
        job.setOutputFormatClass(TextOutputFormat.class);
        TextOutputFormat.setOutputPath(job, new Path("file:////Volumes/赵壮备份/大数据离线课程资料/5.大数据离线第五天/自定义groupingComparator/output_top1"));

        //提交任务至集群
        boolean b = job.waitForCompletion(true);
        return b ? 0 : 1;
    }

    public static void main(String[] args) throws Exception {
        int run = ToolRunner.run(new Configuration(), new GroupMain(), args);
        System.exit(run);
    }
}

• 运行结果

Order_0000002	822.4
Order_0000003	222.8
Order_0000005	222.8

---

求取TopN的数据

• 需求
  
  求取Top1运用了GroupBy的规则，排序后，不需要再进行操作，就会自动输出首个数据
  
  如果要获取TopN的数据就需要在Reduce逻辑中添加循环遍历，所有的NullWritable转换为DoubleWritable，其他都不变

• 代码实现

自定义一个javaBean，命名为OrderBean

package cn.itcast.demo6;

import org.apache.hadoop.io.WritableComparable;

import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;

public class OrderBean implements WritableComparable<OrderBean> {
    //定义orderId和price变量
    private String orderId;
    private Double price;

    /**
     * 重写compareTo方法
     *
     * @param o
     * @return
     */
    @Override
    public int compareTo(OrderBean o) {
        //先对orderId进行比较，如果相同，将它们的price放一起比较，不同就不比较
        int result = this.orderId.compareTo(o.orderId);
        //进行判断
        if (result == 0) {
            int i = this.price.compareTo(o.price);
            return -i;      //返回i求取最小值，返回-i求取最大值
        }
        return result;

    }

    @Override
    public void write(DataOutput out) throws IOException {
        out.writeUTF(orderId);
        out.writeDouble(price);
    }

    @Override
    public void readFields(DataInput in) throws IOException {
        this.orderId = in.readUTF();
        this.price = in.readDouble();
    }

    //生成get(),set()方法

    public String getOrderId() {
        return orderId;
    }

    public void setOrderId(String orderId) {
        this.orderId = orderId;
    }

    public double getPrice() {
        return price;
    }

    public void setPrice(Double price) {
        this.price = price;
    }

    //生成toString()方法

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

定义一个Mapper类

package cn.itcast.demo6;

import org.apache.hadoop.io.DoubleWritable;
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 GroupMapper extends Mapper<LongWritable, Text, OrderBean, DoubleWritable> {
    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        //分割获取到的数据
        String[] split = value.toString().split("\t");

        //创建orderBean对象
        OrderBean orderBean = new OrderBean();
        //给orderId赋值
        orderBean.setOrderId(split[0]);
        //给price赋值
        orderBean.setPrice(Double.valueOf(split[2]));

        DoubleWritable doubleWritable = new DoubleWritable(Double.valueOf(split[2]));
        context.write(orderBean, doubleWritable);
    }
}

自定义分区(Partition)规则

package cn.itcast.demo6;

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

public class GroupPartitioner extends Partitioner<OrderBean, DoubleWritable> {
    /**
     * 重写分区方法
     *
     * @param orderBean
     * @param doubleWritable
     * @param i
     * @return
     */
    @Override
    public int getPartition(OrderBean orderBean, DoubleWritable doubleWritable, int i) {
        //参照HashPartitioner的重写方法
        return (orderBean.getOrderId().hashCode() & Integer.MAX_VALUE) % i;
    }
}

自定义分组(groupingComparator)规则

package cn.itcast.demo6;

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

public class GroupComparator extends WritableComparator {

    //重写无参构造方法，定义反射出来的对象是OrderBean类
    public GroupComparator() {
        super(OrderBean.class, true);
    }

    @Override
    public int compare(WritableComparable a, WritableComparable b) {
        OrderBean first = (OrderBean) a;
        OrderBean second = (OrderBean) b;
        //比较orderId，如果相同就认为是同一组数据
        return first.getOrderId().compareTo(second.getOrderId());
    }
}

定义一个Reducer类

package cn.itcast.demo6;

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

import java.io.IOException;

public class GroupReducer extends Reducer<OrderBean, DoubleWritable, OrderBean, DoubleWritable> {
    /**
     * 直接将收到的k2,v2的值转换为k3,v3输出
     *
     * @param key
     * @param values
     * @param context
     * @throws IOException
     * @throws InterruptedException
     */
    @Override
    protected void reduce(OrderBean key, Iterable<DoubleWritable> values, Context context) throws IOException, InterruptedException {
        int i = 0;
        for (DoubleWritable value : values) {
            i++;
            if (i <= 2) {
                context.write(key, value);
            } else {
                break;
            }
        }
    }
}

程序main函数入口

package cn.itcast.demo6;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

public class GroupMain extends Configured implements Tool {
    @Override
    public int run(String[] args) throws Exception {
        //获取Job对象
        Job job = Job.getInstance(super.getConf(), "myGroupComparator");
        //输入数据，设置输入路径
        job.setInputFormatClass(TextInputFormat.class);
        TextInputFormat.setInputPaths(job, new Path("file:////Volumes/赵壮备份/大数据离线课程资料/5.大数据离线第五天/自定义groupingComparator/input/orders.txt"));

        //自定义Map逻辑
        job.setMapperClass(GroupMapper.class);
        //设置k2,v2输出类型
        job.setMapOutputKeyClass(OrderBean.class);
        job.setMapOutputValueClass(DoubleWritable.class);

        //自定义Partition逻辑
        job.setPartitionerClass(GroupPartitioner.class);

        //自定义分组逻辑
        job.setGroupingComparatorClass(GroupComparator.class);

        //自定义reduce逻辑
        job.setReducerClass(GroupReducer.class);
        //设置k3,v3输出类型
        job.setOutputKeyClass(OrderBean.class);
        job.setOutputValueClass(DoubleWritable.class);

        //输出数据，设置输出路径
        job.setOutputFormatClass(TextOutputFormat.class);
        TextOutputFormat.setOutputPath(job, new Path("file:////Volumes/赵壮备份/大数据离线课程资料/5.大数据离线第五天/自定义groupingComparator/output_top2"));

        //提交任务至集群
        boolean b = job.waitForCompletion(true);
        return b ? 0 : 1;
    }

    public static void main(String[] args) throws Exception {
        int run = ToolRunner.run(new Configuration(), new GroupMain(), args);
        System.exit(run);
    }
}

• 运行结果

Order_0000002	822.4	822.4
Order_0000002	522.4	522.4
Order_0000003	222.8	222.8
Order_0000005	222.8	222.8
Order_0000005	25.8	25.8