文章目錄
1.實現需求
1.根據手機號統計流量日誌文件中的上行流量和下行流量,以及總流量
2.13開頭的手機號寫到文件一中,15開頭的手機號寫到文件二中,其它的手機號寫到文件三中
3.手機號是第二列,上行流量是倒數第三列,下行流量是倒數第二列
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 視頻網站 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 站點統計 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 站點統計 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 綜合門戶 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 綜合門戶 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
1363157985066 13726238888 00-FD-07-A4-72-B8:CMCC 120.196.100.82 i02.c.aliimg.com 24 27 10000 20000 200
2.MapReduce編程模型
表層圖解:
實現過程圖解
- input
讀取文件 - splitting
分割文件,框架自動完成 - mapping
處理文件,以key,value的方式分類 ,需要自己實現 - combiner
mapper端的聚合操作,優點:能減少IO,提升作業性能。侷限性:求平均數這塊就有問題了。可選 - shuffing
把相同的key歸類到一起,框架自動完成 - partitioner 輸出分區,定義分區規則 可選
- Reducing
處理相同的key的數據,需要自己實現 - Final result
處理最後結果
3.編程實現
3.1 依賴
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<version>${hadoop.version}</version>
</dependency>
3.2 自定義複雜數據類型 Access
關鍵點有三個,爲了網絡傳輸的序列化和反序列化
- 1.實現Writable接口
- 2.實現write和readFields方法,並且裏面的順序要一致
- 3.定義一個默認的無參構造方法
package com.zc.bigdata.mapreduce;
import lombok.*;
import org.apache.hadoop.io.Writable;
import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
/**
* 自定義複雜類型
* 1.實現Writable接口
* 2.實現write和readFields方法,並且裏面的順序要一致
* 3.定義一個默認的無參構造方法
*/
@Data
@NoArgsConstructor
public class Access implements Writable {
private String phone;
private long up;
private long down;
private long sum;
public Access(String phone, long up, long down) {
this.phone = phone;
this.up = up;
this.down = down;
this.sum = down + up;
}
@Override
public void write(DataOutput out) throws IOException {
out.writeUTF(this.phone);
out.writeLong(this.up);
out.writeLong(this.down);
out.writeLong(this.sum);
}
@Override
public void readFields(DataInput in) throws IOException {
this.phone = in.readUTF();
this.up = in.readLong();
this.down = in.readLong();
this.sum = in.readLong();
}
}
3.3 重寫Mapper
package com.zc.bigdata.mapreduce;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
import java.io.IOException;
/**
* 自定義Mapper處理類
*/
public class AccessMapper extends Mapper<LongWritable,Text, Text, Access>{
@Override
protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
String[] lines = value.toString().split("\t");
String phone = lines[1]; // 取出手機號
long up = Long.parseLong(lines[lines.length-3]); //取出上行流量
long down = Long.parseLong(lines[lines.length-2]); //取出下行流量
context.write(new Text(phone), new Access(phone, up, down));
}
}
3.4 重寫Reducer
如果不想在文件中輸出key,可以使用NullWritable,繼承時的聲明和啓動類的Reducer輸出都要記得改一下哦
context.write(NullWritable.get(), new Access(key.toString(), ups, downs));
package com.zc.bigdata.mapreduce;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
import java.io.IOException;
public class AccessReducer extends Reducer<Text, Access, Text, Access> {
@Override
protected void reduce(Text key, Iterable<Access> values, Context context) throws IOException, InterruptedException {
long up = 0, down = 0;
for (Access value : values) {
up += value.getUp();
down += value.getDown();
}
context.write(key, new Access(key.toString(), up, down));
}
}
3.5 重寫Partitioner
package com.zc.bigdata.mapreduce;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Partitioner;
public class AccessPartitioner extends Partitioner<Text, Access> {
@Override
public int getPartition(Text phone, Access access, int numPartitions) {
if(phone.toString().startsWith("13")){
return 0;
}else if(phone.toString().startsWith("15")){
return 1;
}else {
return 2;
}
}
}
3.6 實現Job啓動類
package com.zc.bigdata.mapreduce;
import org.apache.commons.io.FileUtils;
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;
import java.io.File;
import java.io.IOException;
public class AccessApp {
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
// windows系統適配,還要下載hadoop-2.6.0,配置環境變量,替換windows/system32裏面的2歌文件
// 步驟還挺多
System.setProperty("hadoop.home.dir","D://gitee//hadoop-2.6.0");
// 創建job
Configuration conf = new Configuration();
Job job = Job.getInstance(conf);
// 設置驅動類
job.setJarByClass(AccessApp.class);
// 設置自定義的mapper和reducer
job.setMapperClass(AccessMapper.class);
job.setReducerClass(AccessReducer.class);
// 設置mapper端的聚合規則
job.setCombinerClass(AccessReducer.class);
// 設置mapper的輸出key,value類型和reducer的輸出key,value類型
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(Access.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Access.class);
// 設置自定義分區規則
job.setPartitionerClass(AccessPartitioner.class);
// 設置Reducer個數
job.setNumReduceTasks(3);
// 提前刪除輸入目錄,以免運行報錯
FileUtils.deleteDirectory(new File("output//access//"));
// 設置輸入文件夾和輸出文件夾
FileInputFormat.setInputPaths(job,new Path("input//access//"));
FileOutputFormat.setOutputPath(job,new Path("output//access//"));
// 執行job
boolean result = job.waitForCompletion(true);
System.out.println(result);
}
}
3.7 運行AccessApp.main()
本地運行,執行成功,windows執行會報錯,要做windows的hadoop適配,網上有很多適配的文章,推薦一個:https://blog.csdn.net/sunshine920103/article/details/52431138,如果沒用,就試試其它文章,還挺麻煩的
part-r-00000:全是13開頭的電話號碼
part-r-00001:全是15開頭的電話號碼
part-r-00002:其它