Hadoop读书笔记（八）MapReduce 打成jar包demo

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

Hadoop读书笔记（七）MapReduce 0.x版本API使用demo：http://blog.csdn.net/caicongyang/article/details/41493325

0.demo说明

与上篇文章一样实现手机流量的统计，数据文件的数据格式相同...

1.代码改造

KpiApp.java

package cmd;import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import java.net.URI;import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
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.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.mapreduce.lib.partition.HashPartitioner;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
/*** * <p> * Title: KpiApp.java * Package mapReduce * </p>* <p>* Description: 统计流量  (打包jar命令行运行) ：extends Configured implements Tool* <p>* @author Tom.Cai* @created 2014-11-25 下午10:23:33 * @version V1.0 **/
public class KpiApp extends Configured implements Tool{public static void main(String[] args) throws Exception {ToolRunner.run(new KpiApp(), args);}@Overridepublic int run(String[] arg0) throws Exception {String INPUT_PATH = arg0[0];String OUT_PATH = arg0[1];FileSystem fileSystem = FileSystem.get(new URI(INPUT_PATH), new Configuration());Path outPath = new Path(OUT_PATH);if (fileSystem.exists(outPath)) {fileSystem.delete(outPath, true);}Job job = new Job(new Configuration(), KpiApp.class.getSimpleName());FileInputFormat.setInputPaths(job, INPUT_PATH);job.setInputFormatClass(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.setOutputFormatClass(TextOutputFormat.class);job.waitForCompletion(true);return 0;}static class KpiMapper extends Mapper<LongWritable, Text, Text, KpiWite> {@Overrideprotected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {String[] splited = value.toString().split("\t");String num = splited[1];KpiWite kpi = new KpiWite(splited[6], splited[7], splited[8], splited[9]);context.write(new Text(num), kpi);}}static class KpiReducer extends Reducer<Text, KpiWite, Text, KpiWite> {@Overrideprotected void reduce(Text key, Iterable<KpiWite> value, Context context) throws IOException, InterruptedException {long upPackNum = 0L;long downPackNum = 0L;long upPayLoad = 0L;long downPayLoad = 0L;for (KpiWite kpi : value) {upPackNum += kpi.upPackNum;downPackNum += kpi.downPackNum;upPayLoad += kpi.upPayLoad;downPayLoad += kpi.downPayLoad;}context.write(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);}@Overridepublic void readFields(DataInput in) throws IOException {this.upPackNum = in.readLong();this.downPackNum = in.readLong();this.upPayLoad = in.readLong();this.downPayLoad = in.readLong();}@Overridepublic void write(DataOutput out) throws IOException {out.writeLong(upPackNum);out.writeLong(downPackNum);out.writeLong(upPayLoad);out.writeLong(downPayLoad);}}

2.打成jar

通过Eclipse的Export将上述的类打成kpi.jar

将jar包上传到Linux下通过 hadoop jar xxx.jar [parameter] [parameter]命令执行即可

例如：hadoop jar kpi.jar hdfs://192.168.80.100:9000/wlan hdfs://192.168.80.100:9000/wlan_out

即将上篇的代码完成改造可以在命令行下运行！

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