作者：小白学习 | 来源：互联网 | 2023-09-04 04:04
GroupingComparator分组案例实操
1．需求
有如下订单数据
表4-2 订单数据
现在需要求出每一个订单中最贵的商品。
（1）输入数据
（2）期望输出数据
1 222.8
2 722.4
3 232.8
2．需求分析
（1）利用“订单id和成交金额”作为key，可以将Map阶段读取到的所有订单数据按照id升序排序，如果id相同再按照金额降序排序，发送到Reduce。
（2）在Reduce端利用groupingComparator将订单id相同的kv聚合成组，然后取第一个即是该订单中最贵商品，如图4-18所示。
图4-18 过程分析
3．代码实现
（1）定义订单信息OrderBean类
| package com.atguigu.mapreduce.order; import java.io.DataInput; import java.io.DataOutput; import java.io.IOException; import org.apache.hadoop.io.WritableComparable; public class OrderBean implements WritableComparable { private int order_id; // 订单id号 private double price; // 价格 public OrderBean() { super(); } public OrderBean(int order_id, double price) { super(); this.order_id = order_id; this.price = price; } @Override public void write(DataOutput out) throws IOException { out.writeInt(order_id); out.writeDouble(price); } @Override public void readFields(DataInput in) throws IOException { order_id = in.readInt(); price = in.readDouble(); } @Override public String toString() { return order_id + “\t” + price; } public int getOrder_id() { return order_id; } public void setOrder_id(int order_id) { this.order_id = order_id; } public double getPrice() { return price; } public void setPrice(double price) { this.price = price; } // 二次排序 @Override public int compareTo(OrderBean o) { int result; if (order_id > o.getOrder_id()) { result = 1; } else if (order_id o.getPrice() ? -1 : 1; } return result; } } |
（2）编写OrderSortMapper类
| package com.atguigu.mapreduce.order; 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 OrderMapper extends Mapper { OrderBean k = new OrderBean(); @Override protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException { // 1 获取一行 String line = value.toString(); // 2 截取 String[] fields = line.split(“\t”); // 3 封装对象 k.setOrder_id(Integer.parseInt(fields[0])); k.setPrice(Double.parseDouble(fields[2])); // 4 写出 context.write(k, NullWritable.get()); } } |
（3）编写OrderSortGroupingComparator类
| package com.atguigu.mapreduce.order; import org.apache.hadoop.io.WritableComparable; import org.apache.hadoop.io.WritableComparator; public class OrderGroupingComparator extends WritableComparator { protected OrderGroupingComparator() { super(OrderBean.class, true); } @Override public int compare(WritableComparable a, WritableComparable b) { OrderBean aBean = (OrderBean) a; OrderBean bBean = (OrderBean) b; int result; if (aBean.getOrder_id() > bBean.getOrder_id()) { result = 1; } else if (aBean.getOrder_id() |
（4）编写OrderSortReducer类
| package com.atguigu.mapreduce.order; import java.io.IOException; import org.apache.hadoop.io.NullWritable; import org.apache.hadoop.mapreduce.Reducer; public class OrderReducer extends Reducer { @Override protected void reduce(OrderBean key, Iterable values, Context context) throws IOException, InterruptedException { context.write(key, NullWritable.get()); } } |
（5）编写OrderSortDriver类
| package com.atguigu.mapreduce.order; 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.mapreduce.Job; import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; public class OrderDriver { public static void main(String[] args) throws Exception, IOException { // 输入输出路径需要根据自己电脑上实际的输入输出路径设置 args = new String[]{“e:/input/inputorder” , “e:/output1”}; // 1 获取配置信息 Configuration cOnf= new Configuration(); Job job = Job.getInstance(conf); // 2 设置jar包加载路径 job.setJarByClass(OrderDriver.class); // 3 加载map/reduce类 job.setMapperClass(OrderMapper.class); job.setReducerClass(OrderReducer.class); // 4 设置map输出数据key和value类型 job.setMapOutputKeyClass(OrderBean.class); job.setMapOutputValueClass(NullWritable.class); // 5 设置最终输出数据的key和value类型 job.setOutputKeyClass(OrderBean.class); job.setOutputValueClass(NullWritable.class); // 6 设置输入数据和输出数据路径 FileInputFormat.setInputPaths(job, new Path(args[0])); FileOutputFormat.setOutputPath(job, new Path(args[1])); // 8 设置reduce端的分组 job.setGroupingComparatorClass(OrderGroupingComparator.class); // 7 提交 boolean result = job.waitForCompletion(true); System.exit(result ? 0 : 1); } } |
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