首页 > 代码库 > Hadoop读书笔记(六)MapReduce自定义数据类型demo
Hadoop读书笔记(六)MapReduce自定义数据类型demo
Hadoop读书笔记(一)Hadoop介绍:http://blog.csdn.net/caicongyang/article/details/39898629
Hadoop读书笔记(二)HDFS的shell操作:http://blog.csdn.net/caicongyang/article/details/41253927
Hadoop读书笔记(三)Java API操作HDFS:http://blog.csdn.net/caicongyang/article/details/41290955
Hadoop读书笔记(四)HDFS体系结构 :http://blog.csdn.net/caicongyang/article/details/41322649
Hadoop读书笔记(五)MapReduce统计单词demo:http://blog.csdn.net/caicongyang/article/details/41453579
1.demo说明
从给定的日志文件中统计手机流量
2.日志文件
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 1363157985079 13823070001 20-7C-8F-70-68-1F:CMCC 120.196.100.99 6 3 360 180 200 1363157985069 13600217502 00-1F-64-E2-E8-B1:CMCC 120.196.100.55 18 138 1080 186852 200
3.代码
KpiApp.java
package mapReduce; import java.io.DataInput; import java.io.DataOutput; import java.io.IOException; import java.net.URI; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.fs.FileSystem; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.LongWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.io.Writable; 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.input.TextInputFormat; import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat; import org.apache.hadoop.mapreduce.lib.partition.HashPartitioner; /** * * <p> * Title: KpiApp.java * Package mapReduce * </p> * <p> * Description: 统计流量 * <p> * @author Tom.Cai * @created 2014-11-25 下午10:23:33 * @version V1.0 * */ public class KpiApp { private static final String INPUT_PATH = "hdfs://192.168.80.100:9000/wlan"; private static final String OUT_PATH = "hdfs://192.168.80.100:9000/wlan_out"; public static void main(String[] args) throws Exception { FileSystem fileSystem = FileSystem.get(new URI(INPUT_PATH), new Configuration()); Path outPath = new Path(OUT_PATH); if (fileSystem.exists(outPath)) { fileSystem.delete(outPath, true); } Job job = new Job(new Configuration(), KpiApp.class.getSimpleName()); FileInputFormat.setInputPaths(job, INPUT_PATH); job.setInputFormatClass(TextInputFormat.class); job.setMapperClass(KpiMapper.class); job.setMapOutputKeyClass(Text.class); job.setMapOutputValueClass(KpiWite.class); job.setPartitionerClass(HashPartitioner.class); job.setNumReduceTasks(1); job.setReducerClass(KpiReducer.class); job.setOutputKeyClass(Text.class); job.setOutputValueClass(KpiWite.class); FileOutputFormat.setOutputPath(job, new Path(OUT_PATH)); job.setOutputFormatClass(TextOutputFormat.class); job.waitForCompletion(true); } static class KpiMapper extends Mapper<LongWritable, Text, Text, KpiWite> { @Override protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException { String[] splited = value.toString().split("\t"); String num = splited[1]; KpiWite kpi = new KpiWite(splited[6], splited[7], splited[8], splited[9]); context.write(new Text(num), kpi); } } static class KpiReducer extends Reducer<Text, KpiWite, Text, KpiWite> { @Override protected void reduce(Text key, Iterable<KpiWite> value, Context context) throws IOException, InterruptedException { long upPackNum = 0L; long downPackNum = 0L; long upPayLoad = 0L; long downPayLoad = 0L; for (KpiWite kpi : value) { upPackNum += kpi.upPackNum; downPackNum += kpi.downPackNum; upPayLoad += kpi.upPayLoad; downPayLoad += kpi.downPayLoad; } context.write(key, new KpiWite(String.valueOf(upPackNum), String.valueOf(downPackNum), String.valueOf(upPayLoad), String.valueOf(downPayLoad))); } } } class KpiWite implements Writable { long upPackNum; long downPackNum; long upPayLoad; long downPayLoad; public KpiWite() { } public KpiWite(String upPackNum, String downPackNum, String upPayLoad, String downPayLoad) { this.upPackNum = Long.parseLong(upPackNum); this.downPackNum = Long.parseLong(downPackNum); this.upPayLoad = Long.parseLong(upPayLoad); this.downPayLoad = Long.parseLong(downPayLoad); } @Override public void readFields(DataInput in) throws IOException { this.upPackNum = in.readLong(); this.downPackNum = in.readLong(); this.upPayLoad = in.readLong(); this.downPayLoad = in.readLong(); } @Override public void write(DataOutput out) throws IOException { out.writeLong(upPackNum); out.writeLong(downPackNum); out.writeLong(upPayLoad); out.writeLong(downPayLoad); } }
欢迎大家一起讨论学习!
有用的自己收!
记录与分享,让你我共成长!欢迎查看我的其他博客;我的博客地址:http://blog.csdn.net/caicongyang
Hadoop读书笔记(六)MapReduce自定义数据类型demo
声明:以上内容来自用户投稿及互联网公开渠道收集整理发布,本网站不拥有所有权,未作人工编辑处理,也不承担相关法律责任,若内容有误或涉及侵权可进行投诉: 投诉/举报 工作人员会在5个工作日内联系你,一经查实,本站将立刻删除涉嫌侵权内容。