Hadoop读书笔记（一）Hadoop介绍：http://blog.csdn.net/caicongyang/article/details/39898629

Hadoop读书笔记（二）HDFS的shell操作：http://blog.csdn.net/caicongyang/article/details/41253927

Hadoop读书笔记（三）Java API操作HDFS：http://blog.csdn.net/caicongyang/article/details/41290955

Hadoop读书笔记（四）HDFS体系结构 ：http://blog.csdn.net/caicongyang/article/details/41322649

Hadoop读书笔记（五）MapReduce统计单词demo：http://blog.csdn.net/caicongyang/article/details/41453579

Hadoop读书笔记（六）MapReduce自定义数据类型demo：http://blog.csdn.net/caicongyang/article/details/41490379

1.说明

功能和上篇一样实现手机流量的统计（ps:可以与前面文章代码做对比）

2.代码：

KpiApp.java

package old;

import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import java.net.URI;
import java.util.Iterator;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.Writable;
import org.apache.hadoop.mapred.FileInputFormat;
import org.apache.hadoop.mapred.FileOutputFormat;
import org.apache.hadoop.mapred.JobClient;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.MapReduceBase;
import org.apache.hadoop.mapred.Mapper;
import org.apache.hadoop.mapred.OutputCollector;
import org.apache.hadoop.mapred.Reducer;
import org.apache.hadoop.mapred.Reporter;
import org.apache.hadoop.mapred.TextInputFormat;
import org.apache.hadoop.mapred.TextOutputFormat;
import org.apache.hadoop.mapred.lib.HashPartitioner;
/**
 *
 * <p> 
 * Title: KpiApp.java 
 * Package old 
 * </p>
 * <p>
 * Description:  hadoop版本1.x的包一般是mapreduce
 * 		 hadoop版本0.x的包一般是mapred
 * <p>
 * @author Tom.Cai
 * @created 2014-11-25 下午10:23:47 
 * @version V1.0 
 *
 */
public class KpiApp {
	private static final String INPUT_PATH = "hdfs://192.168.80.100:9000/wlan";
	private static final String OUT_PATH = "hdfs://192.168.80.100:9000/wlan_out";
	/**
	 * 改动：
	 * 1.不再使用Job，而是使用JobConf
	 * 2.类的包名不再使用mapreduce，而是使用mapred
	 * 3.不再使用job.waitForCompletion(true)提交作业，而是使用JobClient.runJob(job);
	 * 
	 */
	public static void main(String[] args) throws Exception {
		FileSystem fileSystem = FileSystem.get(new URI(INPUT_PATH), new Configuration());
		Path outPath = new Path(OUT_PATH);
		if (fileSystem.exists(outPath)) {
			fileSystem.delete(outPath, true);
		}

		JobConf job = new JobConf(new Configuration(), KpiApp.class);
		FileInputFormat.setInputPaths(job, INPUT_PATH);
		job.setInputFormat(TextInputFormat.class);

		job.setMapperClass(KpiMapper.class);
		job.setMapOutputKeyClass(Text.class);
		job.setMapOutputValueClass(KpiWite.class);

		job.setPartitionerClass(HashPartitioner.class);
		job.setNumReduceTasks(1);

		job.setReducerClass(KpiReducer.class);
		job.setOutputKeyClass(Text.class);
		job.setOutputValueClass(KpiWite.class);

		FileOutputFormat.setOutputPath(job, new Path(OUT_PATH));
		job.setOutputFormat(TextOutputFormat.class);

		JobClient.runJob(job);

	}
	/**
	 * 新api:extends Mapper
	 * 老api:extends MapRedcueBase implements Mapper
	 */
	static class KpiMapper extends MapReduceBase implements Mapper<LongWritable, Text, Text, KpiWite> {
		@Override
		public void map(LongWritable key, Text value, OutputCollector<Text, KpiWite> out, Reporter arg3) throws IOException {
			String[] splited = value.toString().split("\t");
			String num = splited[1];
			KpiWite kpi = new KpiWite(splited[6], splited[7], splited[8], splited[9]);
			out.collect(new Text(num), kpi);
		}
		
		
	}

	static class KpiReducer extends MapReduceBase implements Reducer<Text, KpiWite, Text, KpiWite> {
		@Override
		public void reduce(Text key, Iterator<KpiWite> value, OutputCollector<Text, KpiWite> out, Reporter arg3) throws IOException {
			long upPackNum = 0L;
			long downPackNum = 0L;
			long upPayLoad = 0L;
			long downPayLoad = 0L;
			while (value.hasNext()) {
				upPackNum += value.next().upPackNum;
				downPackNum += value.next().downPackNum;
				upPayLoad += value.next().upPayLoad;
				downPayLoad += value.next().downPayLoad;
			}
			out.collect(key, new KpiWite(String.valueOf(upPackNum), String.valueOf(downPackNum), String.valueOf(upPayLoad), String.valueOf(downPayLoad)));
		}
	}

}

class KpiWite implements Writable {
	long upPackNum;
	long downPackNum;
	long upPayLoad;
	long downPayLoad;

	public KpiWite() {
	}

	public KpiWite(String upPackNum, String downPackNum, String upPayLoad, String downPayLoad) {
		this.upPackNum = Long.parseLong(upPackNum);
		this.downPackNum = Long.parseLong(downPackNum);
		this.upPayLoad = Long.parseLong(upPayLoad);
		this.downPayLoad = Long.parseLong(downPayLoad);
	}

	@Override
	public void readFields(DataInput in) throws IOException {
		this.upPackNum = in.readLong();
		this.downPackNum = in.readLong();
		this.upPayLoad = in.readLong();
		this.downPayLoad = in.readLong();
	}

	@Override
	public void write(DataOutput out) throws IOException {
		out.writeLong(upPackNum);
		out.writeLong(downPackNum);
		out.writeLong(upPayLoad);
		out.writeLong(downPayLoad);
	}

}

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Hadoop读书笔记（七）MapReduce 0.x版本API使用demo