对数据中电话进行分组，并统计上传、下载、总流量
1、待处理的数据为：
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、根据电话前3为进行自定义分组：
package cn.nanda.area;
import java.util.HashMap;
import org.apache.hadoop.mapreduce.Partitioner;
public class AreaPartitioner<KEY, VALUE> extends Partitioner<KEY, VALUE> {
private static HashMap<String, Integer> areaMap = new HashMap<String, Integer>();
static {
areaMap.put("135", 0);
areaMap.put("136", 1);
areaMap.put("137", 2);
areaMap.put("138", 3);
areaMap.put("139", 4);
}
@Override
public int getPartition(KEY key, VALUE value, int numPartitions) {
// 从key中拿到手机号，查询手机归属地字典，不同的省份返回不同的组号
int areaCoder = areaMap.get(key.toString().substring(0, 3)) == null ? 5
: areaMap.get(key.toString().substring(0, 3));
return areaCoder;
}
}
3、使用mr进行处理：
package cn.nanda.area;
import java.io.IOException;
import org.apache.commons.lang.StringUtils;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
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.output.FileOutputFormat;
import cn.nanda.wordCount.FlowBean;
/**
* 对流量原始日志进行流量统计，将不同省份的用户统计结果输出到不同文件 需要自定义改造两个机制 1.改造分区的逻辑，自定义一个partitioner
* 2.自定义redcuer task 的并发任务数
*
* @author kun
*
*/
public class FlowSumArea {
public static class FlowSumAreaMapper extends
Mapper<LongWritable, Text, Text, FlowBean> {
@Override
protected void map(LongWritable key, Text value, Context context)
throws IOException, InterruptedException {
// 拿第一行数据
String line = value.toString();
String[] fields = StringUtils.split(line, "\t");
// 拿到我们需要的字段
String phoneNB = fields[1];
long up_flow = Long.parseLong(fields[7]);
long d_flow = Long.parseLong(fields[8]);
// 封装数据kv并输出
context.write(new Text(phoneNB), new FlowBean(phoneNB, up_flow,
d_flow));
}
}
public static class FlowSumAreaReducer extends Reducer<Text, FlowBean, Text, FlowBean>{
@Override
protected void reduce(Text key, Iterable<FlowBean> values,Context context)
throws IOException, InterruptedException {
long up_flow_count = 0 ;
long d_flow_count = 0 ;
for(FlowBean bean : values){
up_flow_count += bean.getUp_flow();
d_flow_count += bean.getD_flow();
}
context.write(key, new FlowBean(key.toString(), up_flow_count, d_flow_count));
}
}
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
Job job = Job.getInstance(conf);
job.setJarByClass(FlowSumArea.class);
job.setMapperClass(FlowSumAreaMapper.class);
job.setReducerClass(FlowSumAreaReducer.class);
//设置我们自定义的分组逻辑定义
job.setPartitionerClass(AreaPartitioner.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(FlowBean.class);
//设置reduce的任务并发数，应该跟分组的数量保持一致
job.setNumReduceTasks(6);
FileInputFormat.setInputPaths(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
System.exit(job.waitForCompletion(true) ? 0 :1);
}
}
4、分组并处理后结果：
（分了6组，分别存储自定义分组后的结果信息）
part-r-00000:
13502468823 102 7335 7437
13560436666 954 200 1154
13560439658 5892 400 6292
part-r-00001
13602846565 12 1938 1950
13660577991 9 6960 6969
part-r-00002
13719199419 0 200 200
13726230503 2481 24681 27162
13726238888 2481 24681 27162
13760778710 120 200 320
part-r-00003
13826544101 0 200 200
part-r-00004
13922314466 3008 3720 6728
13925057413 63 11058 11121
13926251106 0 200 200
13926435656 1512 200 1712
part-r-00005
13480253104 180 200 380
15013685858 27 3659 3686
15920133257 20 3156 3176
15989002119 3 1938 1941
18211575961 12 1527 1539
18320173382 18 9531 9549
84138413 4116 1432 5548
![MapReduce运行Wordcount时一直卡在INFO mapreduce.Job: Running job，web查看一直处于accepted阶段[图]](data:image/gif;base64,R0lGODlhAQABAIAAAP///wAAACwAAAAAAQABAAACAkQBADs=)