第1关：统计每个城市的宾馆平均价格

package com.processdata;

import java.io.IOException;
import java.util.Scanner;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.client.Connection;
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.client.Result;
import org.apache.hadoop.hbase.client.Scan;
import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil;
import org.apache.hadoop.hbase.mapreduce.TableMapper;
import org.apache.hadoop.hbase.mapreduce.TableReducer;
import org.apache.hadoop.hbase.util.Bytes;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

import com.util.HBaseUtil;

/**
 * 使用MapReduce程序处理HBase中的数据并将最终结果存入到另一张表 1中
 */
public class HBaseMapReduce extends Configured implements Tool {

    public static class MyMapper extends TableMapper<Text, DoubleWritable> {
        public static final byte[] column = "price".getBytes();
        public static final byte[] family = "hotel_info".getBytes();

        @Override
        protected void map(ImmutableBytesWritable rowKey, Result result, Context context)
                throws IOException, InterruptedException {
            /********** Begin *********/


            String cityId = Bytes.toString(result.getValue("cityInfo".getBytes(), "cityId".getBytes()));
            byte[] value = result.getValue(family, column);

            //获取酒店价格
            //String cityId1 = Bytes.toString(result.getValue("hotel_info".getBytes(), "price".getBytes()));

            //将价格转换为double
            Double ho =Double.parseDouble(Bytes.toString(value));
            //将价格转换成（）类型
            DoubleWritable i = new DoubleWritable(ho);
            String key = cityId;
            //写出（城市id，酒店价格）
            context.write(new  Text(key),i);


            /********** End *********/
        }
    }

    public static class MyTableReducer extends TableReducer<Text, DoubleWritable, ImmutableBytesWritable> {
        @Override
        public void reduce(Text key, Iterable<DoubleWritable> values, Context context) throws IOException, InterruptedException {
            /********** Begin *********/


            double sum=0;
            int count=0;
            for(DoubleWritable value:values){
                count++;
                sum+=value.get();
            }
            double avePrice=sum/count;
            //创建pit对象
            Put put =new Put(Bytes.toBytes(key.toString()));
            put.addColumn("average_infos".getBytes(),"price".getBytes(),Bytes.toBytes(String.valueOf(avePrice)));

            context.write(null,put);


            /********** End *********/
        }

    }






    public int run(String[] args) throws Exception {
        //配置Job
        Configuration conf = HBaseConfiguration.create(getConf());
        conf.set("hbase.zookeeper.quorum", "127.0.0.1");  //hbase 服务地址
        conf.set("hbase.zookeeper.property.clientPort", "2181"); //端口号
        Scanner sc = new Scanner(System.in);
        String arg1 = sc.next();
        String arg2 = sc.next();
        //String arg1 = "t_city_hotels_info";
        //String arg2 = "average_table";
        try {
            HBaseUtil.createTable("average_table", new String[] {"average_infos"});
        } catch (Exception e) {
            // 创建表失败
            e.printStackTrace();
        }
        Job job = configureJob(conf,new String[]{arg1,arg2});
        return job.waitForCompletion(true) ? 0 : 1;
    }

    private Job configureJob(Configuration conf, String[] args) throws IOException {
        String tablename = args[0];
        String targetTable = args[1];
        Job job = new Job(conf,tablename);
        Scan scan = new Scan();
        scan.setCaching(300);
        scan.setCacheBlocks(false);//在mapreduce程序中千万不要设置允许缓存
        //初始化Mapreduce程序
        TableMapReduceUtil.initTableMapperJob(tablename,scan,MyMapper.class, Text.class, DoubleWritable.class,job);
        //初始化Reduce
        TableMapReduceUtil.initTableReducerJob(
                targetTable,        // output table
                MyTableReducer.class,    // reducer class
                job);
        job.setNumReduceTasks(1);
        return job;
    }
}