1、需求
统计每一个手机号的总流量(上行流量+下行流量)、上行流量、下行流量,并且最后按照总流量进行手机号的排序。****
2、数据输入及输出格式
源数据比较敏感,这里就不展示出来了
输入格式为:
时间戳、电话号码、基站的物理地址、访问网址的ip、网站域名、数据包、接包数、上行/传流量、下行/载流量、响应码
分隔符为“/t”
输出格式为:
手机号码 上行流量 下行流量 总流量
并且根据总流量的大小进行排序
3、思路分析
map阶段:
切分字段,以手机号为key,value为一个bean对象,value保存对应手机号的上下行流量、以及总流量;key保存手机号,也就是类似的结构:
<1234567,<上下行流量,总流量>>
reduce阶段:
对于同一个key的(即同一手机号)的上下行流量进行累加,获取总的上下行流量、总流量。
并且最后需要对总流量进行排序,所以reduce输出的key为整个bean,value为空
4、具体程序
FlowBean.java
/*用于保存流量数据的自定义可序列化类*/
package PhoneData;
import lombok.Getter;
import lombok.NoArgsConstructor;
import lombok.Setter;
import org.apache.hadoop.io.Writable;
import org.apache.hadoop.io.WritableComparable;
import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
@Getter
@Setter
@NoArgsConstructor
public class FlowBean implements WritableComparable<FlowBean> {
/** 该类是一个可序列化类,且可比较,所以要实现 WritableComparable接口
* 上传、下载、总流量
*/
private int upFlow;
private int downFlow;
private int sumFlow;
public FlowBean(int upFlow, int downFlow) {
super();
this.upFlow = upFlow;
this.downFlow = downFlow;
this.sumFlow = upFlow + downFlow;
}
/**
* 序列化方法
*
* @param dataOutput
* @throws IOException
*/
@Override
public void write(DataOutput dataOutput) throws IOException {
dataOutput.writeInt(this.upFlow);
dataOutput.writeInt(this.downFlow);
dataOutput.writeInt(this.sumFlow);
}
/**
* 反序列化
* @param dataInput
* @throws IOException
*/
@Override
public void readFields(DataInput dataInput) throws IOException {
this.upFlow = dataInput.readInt();
this.downFlow = dataInput.readInt();
this.sumFlow = dataInput.readInt();
}
/**
* 打印字符串方法
* @return
*/
@Override
public String toString() {
StringBuilder sb = new StringBuilder();
sb.append(this.upFlow);
sb.append(" ");
sb.append(this.downFlow);
sb.append(" ");
sb.append(this.sumFlow);
return sb.toString();
}
/**
* 对象的比较方法,用于排序比较
* @param o
* @return
*/
@Override
public int compareTo(FlowBean o) {
return this.getSumFlow() > o.getSumFlow() ? -1 : 1;
}
}
mapper:
package PhoneData;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
import java.io.IOException;
public class PhoneMapper extends Mapper<LongWritable, Text, Text, FlowBean> {
Text k = new Text();
FlowBean v = new FlowBean();
@Override
protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
String line = value.toString();
String[] fields = line.split("/t");
//开始解析切割数据
k.set(fields[1]);
int downFlow = Integer.parseInt(fields[fields.length - 2]);
int upFlow = Integer.parseInt(fields[fields.length - 3]);
v.setDownFlow(downFlow);
v.setUpFlow(upFlow);
v.setSumFlow(upFlow + downFlow);
context.write(k, v);
}
}
reducer:
package PhoneData;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
import java.io.IOException;
public class PhoneReducer extends Reducer<Text, FlowBean, FlowBean, Text> {
FlowBean v = new FlowBean();
@Override
protected void reduce(Text key, Iterable<FlowBean> values, Context context) throws IOException, InterruptedException {
int upFlow = 0;
int downFlow = 0;
int sumFlow = 0;
//对上传、下载、总流量进行累加
for (FlowBean f : values) {
upFlow += f.getUpFlow();
downFlow += f.getDownFlow();
sumFlow += f.getSumFlow();
}
//将汇总的数据写到新的bean中,然后输出
v.setUpFlow(upFlow);
v.setDownFlow(downFlow);
v.setSumFlow(sumFlow);
context.write(v, key);
}
}
driver:
package PhoneData;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.compress.BZip2Codec;
import org.apache.hadoop.io.compress.CompressionCodec;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import java.io.IOException;
public class PhoneDriver {
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
args = new String[]{"G://test//A//phone_data.txt", "G://test//A//phonetest5//"};
Configuration conf = new Configuration();
//获取job对象
Job job = Job.getInstance(conf);
//配置driver,map,reduce类
job.setJarByClass(PhoneDriver.class);
job.setMapperClass(PhoneMapper.class);
job.setReducerClass(PhoneReducer.class);
//指定map和reduce的输出类
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(FlowBean.class);
job.setOutputKeyClass(FlowBean.class);
job.setOutputValueClass(Text.class);
//指定输入数据,输出路径
FileInputFormat.setInputPaths(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
//提交job
job.waitForCompletion(true);
}
}
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