第1关：统计共享单车每天的平均使用时间

package com.educoder.bigData.sharedbicycle;

import java.io.IOException;
import java.text.ParseException;
import java.util.Collection;
import java.util.Date;
import java.util.HashMap;
import java.util.Locale;
import java.util.Map;
import java.util.Scanner;
import java.math.RoundingMode;
import java.math.BigDecimal;
import org.apache.commons.lang3.time.DateFormatUtils;
import org.apache.commons.lang3.time.FastDateFormat;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
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.BytesWritable;
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 com.educoder.bigData.util.HBaseUtil;

/**
 * 统计共享单车每天的平均使用时间
 */
public class AveragetTimeMapReduce extends Configured implements Tool {

	public static final byte[] family = "info".getBytes();

	public static class MyMapper extends TableMapper<Text, BytesWritable> {
		protected void map(ImmutableBytesWritable rowKey, Result result, Context context)
				throws IOException, InterruptedException {
			/********** Begin *********/
		 long beginTime = Long.parseLong(Bytes.toString(result.getValue(family, "beginTime".getBytes())));
		 long endTime = Long.parseLong(Bytes.toString(result.getValue(family, "endTime".getBytes())));
		 String format = DateFormatUtils.format(beginTime, "yyyy-MM-dd", Locale.CHINA);
		 long useTime = endTime - beginTime;
		 BytesWritable bytesWritable = new BytesWritable(Bytes.toBytes(format + "_" + useTime));
		 context.write(new Text("avgTime"), bytesWritable);

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

	public static class MyTableReducer extends TableReducer<Text, BytesWritable, ImmutableBytesWritable> {
		@Override
		public void reduce(Text key, Iterable<BytesWritable> values, Context context)
				throws IOException, InterruptedException {
			/********** Begin *********/
		     double sum = 0;
			int length = 0;
			Map<String, Long> map = new HashMap<String, Long>();
			for (BytesWritable price : values) {
				byte[] copyBytes = price.copyBytes();
				String string = Bytes.toString(copyBytes);
				String[] split = string.split("_");
				if (map.containsKey(split[0])) {
					Long integer = map.get(split[0]) + Long.parseLong(split[1]);
					map.put(split[0], integer);
				} else {
					map.put(split[0], Long.parseLong(split[1]));
				}
			}
			Collection<Long> values2 = map.values();
			for (Long i : values2) {
				length++;
				sum += i;
			}
			BigDecimal decimal = new BigDecimal(sum / length /1000);
			BigDecimal setScale = decimal.setScale(2, RoundingMode.HALF_DOWN);
			Put put = new Put(Bytes.toBytes(key.toString()));
			put.addColumn(family, "avgTime".getBytes(), Bytes.toBytes(setScale.toString()));
			context.write(null, put);
		 
		 
		 
		 
			/********** End *********/
		}

	}

	public int run(String[] args) throws Exception {
		// 配置Job
		Configuration conf = HBaseUtil.conf;
		// Scanner sc = new Scanner(System.in);
		// String arg1 = sc.next();
		// String arg2 = sc.next();
		String arg1 = "t_shared_bicycle";
		String arg2 = "t_bicycle_avgtime";
		try {
			HBaseUtil.createTable(arg2, new String[] { "info" });
		} 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, BytesWritable.class, job);
		// 初始化Reduce
		TableMapReduceUtil.initTableReducerJob(targetTable, // output table
				MyTableReducer.class, // reducer class
				job);
		job.setNumReduceTasks(1);
		return job;
	}
}