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MapReduce 之流量汇总案例三+将统计结果将统计结果按照总流量正序排序(全排序)

程序员文章站 2022-06-29 21:55:51
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0)需求

根据需求1产生的结果再次对总流量进行排序。

1)数据准备

1363157985066 	13726230503	00-FD-07-A4-72-B8:CMCC	120.196.100.82	i02.c.aliimg.com		24	27	2481	24681	200
1363157995052 	13826544101	5C-0E-8B-C7-F1-E0:CMCC	120.197.40.4			4	0	264	0	200
1363157991076 	13926435656	20-10-7A-28-CC-0A:CMCC	120.196.100.99			2	4	132	1512	200
1363154400022 	13926251106	5C-0E-8B-8B-B1-50:CMCC	120.197.40.4			4	0	240	0	200
1363157993044 	18211575961	94-71-AC-CD-E6-18:CMCC-EASY	120.196.100.99	iface.qiyi.com	视频网站	15	12	1527	2106	200
1363157995074 	84138413	5C-0E-8B-8C-E8-20:7DaysInn	120.197.40.4	122.72.52.12		20	16	4116	1432	200
1363157993055 	13560439658	C4-17-FE-BA-DE-D9:CMCC	120.196.100.99			18	15	1116	954	200
1363157995033 	15920133257	5C-0E-8B-C7-BA-20:CMCC	120.197.40.4	sug.so.360.cn	信息安全	20	20	3156	2936	200
1363157983019 	13719199419	68-A1-B7-03-07-B1:CMCC-EASY	120.196.100.82			4	0	240	0	200
1363157984041 	13660577991	5C-0E-8B-92-5C-20:CMCC-EASY	120.197.40.4	s19.cnzz.com	站点统计	24	9	6960	690	200
1363157973098 	15013685858	5C-0E-8B-C7-F7-90:CMCC	120.197.40.4	rank.ie.sogou.com	搜索引擎	28	27	3659	3538	200
1363157986029 	15989002119	E8-99-C4-4E-93-E0:CMCC-EASY	120.196.100.99	www.umeng.com	站点统计	3	3	1938	180	200
1363157992093 	13560439658	C4-17-FE-BA-DE-D9:CMCC	120.196.100.99			15	9	918	4938	200
1363157986041 	13480253104	5C-0E-8B-C7-FC-80:CMCC-EASY	120.197.40.4			3	3	180	180	200
1363157984040 	13602846565	5C-0E-8B-8B-B6-00:CMCC	120.197.40.4	2052.flash2-http.qq.com	综合门户	15	12	1938	2910	200
1363157995093 	13922314466	00-FD-07-A2-EC-BA:CMCC	120.196.100.82	img.qfc.cn		12	12	3008	3720	200
1363157982040 	13502468823	5C-0A-5B-6A-0B-D4:CMCC-EASY	120.196.100.99	y0.ifengimg.com	综合门户	57	102	7335	110349	200
1363157986072 	18320173382	84-25-DB-4F-10-1A:CMCC-EASY	120.196.100.99	input.shouji.sogou.com	搜索引擎	21	18	9531	2412	200
1363157990043 	13925057413	00-1F-64-E1-E6-9A:CMCC	120.196.100.55	t3.baidu.com	搜索引擎	69	63	11058	48243	200
1363157988072 	13760778710	00-FD-07-A4-7B-08:CMCC	120.196.100.82			2	2	120	120	200
1363157985066 	13726238888	00-FD-07-A4-72-B8:CMCC	120.196.100.82	i02.c.aliimg.com		24	27	2481	24681	200
1363157993055 	13560436666	C4-17-FE-BA-DE-D9:CMCC	120.196.100.99			18	15	1116	954	200

2)分析(缓冲区一开始在内存中,当100M满后,存入磁盘中先进行分区,再排序,hadoop只对key进行排序,并不会对value排序,因此要把流量作为key进行排序)

(1)把程序分两步走,第一步正常统计总流量,第二步再把结果进行排序

(2)context.write(总流量,手机号)

(3)FlowBean实现WritableComparable接口重写compareTo方法

3)代码实现

(1)FlowBean对象在在需求1基础上增加了比较功能

MapReduce 之流量汇总案例三+将统计结果将统计结果按照总流量正序排序(全排序)

MapReduce 之流量汇总案例三+将统计结果将统计结果按照总流量正序排序(全排序)
 

(2)编写mapper

package com.lzz.mapreduce.flowsort;

import java.io.IOException;

import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;

public class FlowSortMapper extends Mapper<LongWritable, Text, FlowBean, Text>{
	

//	13502468823		7335	110349	117684
//	13560436666		3597	25635	29232
//	13560439658		2034	5892	7926

	FlowBean k=new FlowBean();
	Text v= new Text();
	@Override
	protected void map(LongWritable key, Text value, Context context)
			throws IOException, InterruptedException {
		//1获取一行
		String line=value.toString();
		//2切割
		String[] fields=line.split("\t");
		//3封装对象
		long upflow=Long.parseLong(fields[2]);
		long downflow=Long.parseLong(fields[3]);
		
		
		k.set(upflow,downflow);
		v.set(fields[0]);
		//4写出
		context.write(k, v);
		
	}
}

3)编写reducer

package com.lzz.mapreduce.flowsort;

import java.io.IOException;

import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;

public class FlowSortReducer extends Reducer<FlowBean, Text, Text, FlowBean>{
	@Override
	protected void reduce(FlowBean key, Iterable<Text> values,Context context)
			throws IOException, InterruptedException {
		context.write(values.iterator().next(), key);
	}
}

4)编写driver

package com.lzz.mapreduce.flowsort;

import java.io.IOException;



import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;


public class FlowSortDriver {
	public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
		Configuration configuration=new Configuration();
		Job job=Job.getInstance(configuration);
		
		job.setJarByClass(FlowSortDriver.class);
		
		job.setMapperClass(FlowSortMapper.class);
		job.setReducerClass(FlowSortReducer.class);
		
		job.setMapOutputKeyClass(FlowBean.class);
		job.setMapOutputValueClass(Text.class);
		
		//设置分区
		job.setPartitionerClass(FlowSortProvincePartitioner.class);
		job.setNumReduceTasks(5);
		
		
		job.setOutputKeyClass(Text.class);
		job.setOutputValueClass(FlowBean.class);
		
		FileInputFormat.setInputPaths(job, new Path(args[0]));
		FileOutputFormat.setOutputPath(job, new Path(args[1]));
		
		boolean result=job.waitForCompletion(true);
		System.exit(result?0:1);
	}
}

结果

MapReduce 之流量汇总案例三+将统计结果将统计结果按照总流量正序排序(全排序)

相关标签: hadoop mapreduce