Hadoop网络课程模板程序

Text_1

/**
* Hadoop网络课程模板程序
* 编写者：James
*/

import java.io.IOException;
import java.text.DateFormat;
import java.text.SimpleDateFormat;
import java.util.Date;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapreduce.*;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

/**
* 无Reducer版本
*/
public class Test_1 extends Configured implements Tool {

/**
* 计数器
* 用于计数各种异常数据
*/
enum Counter
{
LINESKIP,    //出错的行
}

/**
* MAP任务
*/
public static class Map extends Mapper<LongWritable, Text, NullWritable, Text>
{
public void map ( LongWritable key, Text value, Context context ) throws IOException, InterruptedException
{
String line = value.toString();                //读取源数据

try
{
//数据处理
String [] lineSplit = line.split(" ");
String month = lineSplit[0];
String time = lineSplit[1];
String mac = lineSplit[6];
Text out = new Text(month + ' ' + time + ' ' + mac);

context.write( NullWritable.get(), out);    //输出
}
catch ( java.lang.ArrayIndexOutOfBoundsException e )
{
context.getCounter(Counter.LINESKIP).increment(1);    //出错令计数器+1
return;
}
}
}

@Override
public int run(String[] args) throws Exception
{
Configuration conf = getConf();

Job job = new Job(conf, "Test_1");                                //任务名
job.setJarByClass(Test_1.class);                                //指定Class

FileInputFormat.addInputPath( job, new Path(args[0]) );            //输入路径
FileOutputFormat.setOutputPath( job, new Path(args[1]) );        //输出路径

job.setMapperClass( Map.class );                                //调用上面Map类作为Map任务代码
job.setOutputFormatClass( TextOutputFormat.class );
job.setOutputKeyClass( NullWritable.class );                    //指定输出的KEY的格式
job.setOutputValueClass( Text.class );                            //指定输出的VALUE的格式

job.waitForCompletion(true);

//输出任务完成情况
System.out.println( "任务名称：" + job.getJobName() );
System.out.println( "任务成功：" + ( job.isSuccessful()?"是":"否" ) );
System.out.println( "输入行数：" + job.getCounters().findCounter("org.apache.hadoop.mapred.Task$Counter", "MAP_INPUT_RECORDS").getValue() );
System.out.println( "输出行数：" + job.getCounters().findCounter("org.apache.hadoop.mapred.Task$Counter", "MAP_OUTPUT_RECORDS").getValue() );
System.out.println( "跳过的行：" + job.getCounters().findCounter(Counter.LINESKIP).getValue() );

return job.isSuccessful() ? 0 : 1;
}

/**
* 设置系统说明
* 设置MapReduce任务
*/
public static void main(String[] args) throws Exception
{

//判断参数个数是否正确
//如果无参数运行则显示以作程序说明
if ( args.length != 2 )
{
System.err.println("");
System.err.println("Usage: Test_1 < input path > < output path > ");
System.err.println("Example: hadoop jar ~/Test_1.jar hdfs://localhost:9000/home/james/Test_1 hdfs://localhost:9000/home/james/output");
System.err.println("Counter:");
System.err.println("\t"+"LINESKIP"+"\t"+"Lines which are too short");
System.exit(-1);
}

//记录开始时间
DateFormat formatter = new SimpleDateFormat( "yyyy-MM-dd HH:mm:ss" );
Date start = new Date();

//运行任务
int res = ToolRunner.run(new Configuration(), new Test_1(), args);

//输出任务耗时
Date end = new Date();
float time =  (float) (( end.getTime() - start.getTime() ) / 60000.0) ;
System.out.println( "任务开始：" + formatter.format(start) );
System.out.println( "任务结束：" + formatter.format(end) );
System.out.println( "任务耗时：" + String.valueOf( time ) + " 分钟" );

System.exit(res);
}
}

Test_1数据
Apr 23 11:49:54 hostapd: wlan0: STA 14:7d:c5:9e:fb:84
Apr 23 11:49:52 hostapd: wlan0: STA 74:e5:0b:04:28:f2
Apr 23 11:49:50 hostapd: wlan0: STA cc:af:78:cc:d5:5d
Apr 23 11:49:44 hostapd: wlan0: STA cc:af:78:cc:d5:5d
Apr 23 11:49:43 hostapd: wlan0: STA 74:e5:0b:04:28:f2
Apr 23 11:49:42 hostapd: wlan0: STA 14:7d:c5:9e:fb:84

Test_2.java
/**
* Hadoop网络课程模板程序
* 编写者：James
*/

import java.io.IOException;
import java.text.DateFormat;
import java.text.SimpleDateFormat;
import java.util.Date;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapreduce.*;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

/**
* 有Reducer版本
*/
public class Test_2 extends Configured implements Tool {

/**
* 计数器
* 用于计数各种异常数据
*/
enum Counter
{
LINESKIP, //出错的行
}

/**
* MAP任务
*/
public static class Map extends Mapper<LongWritable, Text, Text, Text>
{
public void map ( LongWritable key, Text value, Context context ) throws IOException, InterruptedException
{
String line = value.toString(); //读取源数据

try
{
//数据处理
String [] lineSplit = line.split(" ");
String anum = lineSplit[0];
String bnum = lineSplit[1];

context.write( new Text(bnum), new Text(anum) ); //输出
}
catch ( java.lang.ArrayIndexOutOfBoundsException e )
{
context.getCounter(Counter.LINESKIP).increment(1); //出错令计数器+1
return;
}
}
}

/**
* REDUCE任务
*/
public static class Reduce extends Reducer<Text, Text, Text, Text>
{
public void reduce ( Text key, Iterable<Text> values, Context context ) throws IOException, InterruptedException
{
String valueString;
String out = "";

for ( Text value : values )
{
valueString = value.toString();
out += valueString + "|";
}

context.write( key, new Text(out) );
}
}

@Override
public int run(String[] args) throws Exception
{
Configuration conf = getConf();

Job job = new Job(conf, "Test_2"); //任务名
job.setJarByClass(Test_2.class); //指定Class

FileInputFormat.addInputPath( job, new Path(args[0]) ); //输入路径
FileOutputFormat.setOutputPath( job, new Path(args[1]) ); //输出路径

job.setMapperClass( Map.class ); //调用上面Map类作为Map任务代码
job.setReducerClass ( Reduce.class ); //调用上面Reduce类作为Reduce任务代码
job.setOutputFormatClass( TextOutputFormat.class );
job.setOutputKeyClass( Text.class ); //指定输出的KEY的格式
job.setOutputValueClass( Text.class ); //指定输出的VALUE的格式

job.waitForCompletion(true);

//输出任务完成情况
System.out.println( "任务名称：" + job.getJobName() );
System.out.pr
4000
intln( "任务成功：" + ( job.isSuccessful()?"是":"否" ) );
System.out.println( "输入行数：" + job.getCounters().findCounter("org.apache.hadoop.mapred.Task$Counter", "MAP_INPUT_RECORDS").getValue() );
System.out.println( "输出行数：" + job.getCounters().findCounter("org.apache.hadoop.mapred.Task$Counter", "MAP_OUTPUT_RECORDS").getValue() );
System.out.println( "跳过的行：" + job.getCounters().findCounter(Counter.LINESKIP).getValue() );

return job.isSuccessful() ? 0 : 1;
}

/**
* 设置系统说明
* 设置MapReduce任务
*/
public static void main(String[] args) throws Exception
{

//判断参数个数是否正确
//如果无参数运行则显示以作程序说明
if ( args.length != 2 )
{
System.err.println("");
System.err.println("Usage: Test_2 < input path > < output path > ");
System.err.println("Example: hadoop jar ~/Test_2.jar hdfs://localhost:9000/home/james/Test_2 hdfs://localhost:9000/home/james/output");
System.err.println("Counter:");
System.err.println("\t"+"LINESKIP"+"\t"+"Lines which are too short");
System.exit(-1);
}

//记录开始时间
DateFormat formatter = new SimpleDateFormat( "yyyy-MM-dd HH:mm:ss" );
Date start = new Date();

//运行任务
int res = ToolRunner.run(new Configuration(), new Test_2(), args);

//输出任务耗时
Date end = new Date();
float time = (float) (( end.getTime() - start.getTime() ) / 60000.0) ;
System.out.println( "任务开始：" + formatter.format(start) );
System.out.println( "任务结束：" + formatter.format(end) );
System.out.println( "任务耗时：" + String.valueOf( time ) + " 分钟" );

System.exit(res);
}
}

Test_2数据

13599999999 10086
13899999999    120
13944444444 13800138000
13722222222 13800138000
18800000000 120
13722222222 10086
18944444444 10086

Exercise_1.java

/**
* Hadoop网络课程作业程序
* 编写者：James
*/

import java.io.IOException;
import java.text.DateFormat;
import java.text.SimpleDateFormat;
import java.util.Date;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapreduce.*;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

public class Exercise_1 extends Configured implements Tool {

/**
* 计数器
* 用于计数各种异常数据
*/
enum Counter
{
LINESKIP, //出错的行
}

/**
* MAP任务
*/
public static class Map extends Mapper<LongWritable, Text, NullWritable, Text>
{
public void map ( LongWritable key, Text value, Context context ) throws IOException, InterruptedException
{
String line = value.toString(); //读取源数据

try
{
//数据处理
String [] lineSplit = line.split(" ");
String month = lineSplit[0];
String time = lineSplit[1];
String mac = lineSplit[6];

/** 需要注意的部分 **/

String name = context.getConfiguration().get("name");
Text out = new Text(name + ' ' + month + ' ' + time + ' ' + mac);

/** 需要注意的部分 **/

context.write( NullWritable.get(), out); //输出
}
catch ( java.lang.ArrayIndexOutOfBoundsException e )
{
context.getCounter(Counter.LINESKIP).increment(1); //出错令计数器+1
return;
}
}
}

@Override
public int run(String[] args) throws Exception
{
Configuration conf = getConf();

/** 需要注意的部分 **/

conf.set("name", args[2]);

/** 需要注意的部分 **/

Job job = new Job(conf, "Exercise_1"); //任务名
job.setJarByClass(Exercise_1.class); //指定Class

FileInputFormat.addInputPath( job, new Path(args[0]) ); //输入路径
FileOutputFormat.setOutputPath( job, new Path(args[1]) ); //输出路径

job.setMapperClass( Map.class ); //调用上面Map类作为Map任务代码
job.setOutputFormatClass( TextOutputFormat.class );
job.setOutputKeyClass( NullWritable.class ); //指定输出的KEY的格式
job.setOutputValueClass( Text.class ); //指定输出的VALUE的格式

job.waitForCompletion(true);

//输出任务完成情况
System.out.println( "任务名称：" + job.getJobName() );
System.out.println( "任务成功：" + ( job.isSuccessful()?"是":"否" ) );
System.out.println( "输入行数：" + job.getCounters().findCounter("org.apache.hadoop.mapred.Task$Counter", "MAP_INPUT_RECORDS").getValue() );
System.out.println( "输出行数：" + job.getCounters().findCounter("org.apache.hadoop.mapred.Task$Counter", "MAP_OUTPUT_RECORDS").getValue() );
System.out.println( "跳过的行：" + job.getCounters().findCounter(Counter.LINESKIP).getValue() );

return job.isSuccessful() ? 0 : 1;
}

/**
* 设置系统说明
* 设置MapReduce任务
*/
public static void main(String[] args) throws Exception
{

//判断参数个数是否正确
//如果无参数运行则显示以作程序说明
if ( args.length != 3 )
{
System.err.println("");
System.err.println("Usage: Test_1 < input path > < output path > < name >");
System.err.println("Example: hadoop jar ~/Test_1.jar hdfs://localhost:9000/home/james/Test_1
hdfs://localhost:9000/home/james/output hadoop");
System.err.println("Counter:");
System.err.println("\t"+"LINESKIP"+"\t"+"Lines which are too short");
System.exit(-1);
}

//记录开始时间
DateFormat formatter = new SimpleDateFormat( "yyyy-MM-dd HH:mm:ss" );
Date start = new Date();

//运行任务
int res = ToolRunner.run(new Configuration(), new Exercise_1(), args);

//输出任务耗时
Date end = new Date();
float time = (float) (( end.getTime() - start.getTime() ) / 60000.0) ;
System.out.println( "任务开始：" + formatter.format(start) );
System.out.println( "任务结束：" + formatter.format(end) );
System.out.println( "任务耗时：" + String.valueOf( time ) + " 分钟" );

System.exit(res);
}
}

result_1

hadoop Apr 23 14:7d:c5:9e:fb:84
hadoop Apr 23 74:e5:0b:04:28:f2
hadoop Apr 23 cc:af:78:cc:d5:5d
hadoop Apr 23 cc:af:78:cc:d5:5d
hadoop Apr 23 74:e5:0b:04:28:f2
hadoop Apr 23 14:7d:c5:9e:fb:84

Exercise_2.java
/**
* Hadoop网络课程作业程序
* 编写者：James
*/

import java.io.IOException;
import java.text.DateFormat;
import java.text.SimpleDateFormat;
import java.util.Date;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapreduce.*;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

public class Exercise_2 extends Configured implements Tool {

/**
* 计数器
* 用于计数各种异常数据
*/
enum Counter
{
LINESKIP, //出错的行
}

/**
* MAP任务
*/
public static class Map extends Mapper<LongWritable, Text, NullWritable, Text>
{

/** 需要注意的部分 **/

private String name;
public void setup ( Context context )
{
this.name = context.getConfiguration().get("name"); //读取名字
}

/** 需要注意的部分 **/

public void map ( LongWritable key, Text value, Context context ) throws IOException, InterruptedException
{
String line = value.toString(); //读取源数据

try
{
//数据处理
String [] lineSplit = line.split(" ");
String month = lineSplit[0];
String time = lineSplit[1];
String mac = lineSplit[6];

/** 需要注意的部分 **/

Text out = new Text(this.name + ' ' + month + ' ' + time + ' ' + mac);

/** 需要注意的部分 **/

context.write( NullWritable.get(), out); //输出
}
catch ( java.lang.ArrayIndexOutOfBoundsException e )
{
context.getCounter(Counter.LINESKIP).increment(1); //出错令计数器+1
return;
}
}
}

@Override
public int run(String[] args) throws Exception
{
Configuration conf = getConf();

/** 需要注意的部分 **/

conf.set("name", args[2]);

/** 需要注意的部分 **/

Job job = new Job(conf, "Exercise_2"); //任务名
job.setJarByClass(Exercise_2.class); //指定Class

FileInputFormat.addInputPath( job, new Path(args[0]) ); //输入路径
FileOutputFormat.setOutputPath( job, new Path(args[1]) ); //输出路径

job.setMapperClass( Map.class ); //调用上面Map类作为Map任务代码
job.setOutputFormatClass( TextOutputFormat.class );
job.setOutputKeyClass( NullWritable.class ); //指定输出的KEY的格式
job.setOutputValueClass( Text.class ); //指定输出的VALUE的格式

job.waitForCompletion(true);

//输出任务完成情况
System.out.println( "任务名称：" + job.getJobName() );
System.out.println( "任务成功：" + ( job.isSuccessful()?"是":"否" ) );
System.out.println( "输入行数：" + job.getCounters().findCounter("org.apache.hadoop.mapred.Task$Counter", "MAP_INPUT_RECORDS").getValue() );
System.out.println( "输出行数：" + job.getCounters().findCounter("org.apache.hadoop.mapred.Task$Counter", "MAP_OUTPUT_RECORDS").getValue() );
System.out.println( "跳过的行：" + job.getCounters().findCounter(Counter.LINESKIP).getValue() );

return job.isSuccessful() ? 0 : 1;
}

/**
* 设置系统说明
* 设置MapReduce任务
*/
public static void main(String[] args) throws Exception
{

//判断参数个数是否正确
//如果无参数运行则显示以作程序说明
if ( args.length != 3 )
{
System.err.println("");
System.err.println("Usage: Test_1 < input path > < output path > < name >");
System.err.println("Example: hadoop jar ~/Test_1.jar hdfs://localhost:9000/home/james/Test_1
hdfs://localhost:9000/home/james/output hadoop");
System.err.println("Counter:");
System.err.println("\t"+"LINESKIP"+"\t"+"Lines which are too short");
System.exit(-1);
}

//记录开始时间
DateFormat formatter = new SimpleDateFormat( "yyyy-MM-dd HH:mm:ss" );
Date start = new Date();

//运行任务
int res = ToolRunner.run(new Configuration(), new Exercise_2(), args);

//输出任务耗时
Date end = new Date();
float time = (float) (( end.getTime() - start.getTime() ) / 60000.0) ;
System.out.println( "任务开始：" + formatter.format(start) );
System.out.println( "任务结束：" + formatter.format(end) );
System.out.println( "任务耗时：" + String.valueOf( time ) + " 分钟" );

System.exit(res);
}
}

改写test_2

/**
* Hadoop网络课程模板程序
* 编写者：James
*/

import java.io.IOException;
import java.text.DateFormat;
import java.text.SimpleDateFormat;
import java.util.Date;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapreduce.*;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

/**
* 有Reducer版本
*/
public class Test_2 extends Configured implements Tool {

/**
* 计数器
* 用于计数各种异常数据
*/
enum Counter
{
LINESKIP,    //出错的行
}

/**
* MAP任务
*/
public static class Map extends Mapper<LongWritable, Text, Text, Text>
{
public void map ( LongWritable key, Text value, Context context ) throws IOException, InterruptedException
{
String line = value.toString();                //读取源数据

try
{
//数据处理
String [] lineSplit = line.split(" ");
String anum = lineSplit[0];
String bnum = lineSplit[1];

context.write( new Text(bnum), new Text(anum) );    //输出
}
catch ( java.lang.ArrayIndexOutOfBoundsException e )
{
context.getCounter(Counter.LINESKIP).increment(1);    //出错令计数器+1
return;
}
}
}

/**
* REDUCE任务
*/
public static class Reduce extends Reducer<Text, Text, Text, Text>
{
public void reduce ( Text key, Iterable<Text> values, Context context ) throws IOException, InterruptedException
{
String valueString;
String out = "";

String name = context.getConfiguration().get("name");

for ( Text value : values )
{
valueString = value.toString();
out += valueString + "|";
}

context.write( key, new Text(out) + "|" + name );
}
}

@Override
public int run(String[] args) throws Exception
{
Configuration conf = getConf();

conf.set("name", args[2]);

Job job = new Job(conf, "Test_2");                                //任务名
job.setJarByClass(Test_2.class);                                //指定Class

FileInputFormat.addInputPath( job, new Path(args[0]) );            //输入路径
FileOutputFormat.setOutputPath( job, new Path(args[1]) );        //输出路径

job.setMapperClass( Map.class );                                //调用上面Map类作为Map任务代码
job.setReducerCl
a78b
ass ( Reduce.class );                            //调用上面Reduce类作为Reduce任务代码
job.setOutputFormatClass( TextOutputFormat.class );
job.setOutputKeyClass( Text.class );                            //指定输出的KEY的格式
job.setOutputValueClass( Text.class );                            //指定输出的VALUE的格式

job.waitForCompletion(true);

//输出任务完成情况
System.out.println( "任务名称：" + job.getJobName() );
System.out.println( "任务成功：" + ( job.isSuccessful()?"是":"否" ) );
System.out.println( "输入行数：" + job.getCounters().findCounter("org.apache.hadoop.mapred.Task$Counter", "MAP_INPUT_RECORDS").getValue() );
System.out.println( "输出行数：" + job.getCounters().findCounter("org.apache.hadoop.mapred.Task$Counter", "MAP_OUTPUT_RECORDS").getValue() );
System.out.println( "跳过的行：" + job.getCounters().findCounter(Counter.LINESKIP).getValue() );

return job.isSuccessful() ? 0 : 1;
}

/**
* 设置系统说明
* 设置MapReduce任务
*/
public static void main(String[] args) throws Exception
{

//判断参数个数是否正确
//如果无参数运行则显示以作程序说明
if ( args.length != 3 )
{
System.err.println("");
System.err.println("Usage: Test_2 < input path > < output path > ");
System.err.println("Example: hadoop jar ~/Test_2.jar hdfs://localhost:9000/home/james/Test_2 hdfs://localhost:9000/home/james/output hadoop");
System.err.println("Counter:");
System.err.println("\t"+"LINESKIP"+"\t"+"Lines which are too short");
System.exit(-1);
}

//记录开始时间
DateFormat formatter = new SimpleDateFormat( "yyyy-MM-dd HH:mm:ss" );
Date start = new Date();

//运行任务
int res = ToolRunner.run(new Configuration(), new Test_2(), args);

//输出任务耗时
Date end = new Date();
float time =  (float) (( end.getTime() - start.getTime() ) / 60000.0) ;
System.out.println( "任务开始：" + formatter.format(start) );
System.out.println( "任务结束：" + formatter.format(end) );
System.out.println( "任务耗时：" + String.valueOf( time ) + " 分钟" );

System.exit(res);
}
}

result_2
10086 13599999999|13722222222|18944444444|hadoop
120 18800000000|hadoop
13800138000 13944444444|13722222222|hadoop