这段时间学习Mahout有喜有悲。在这里首先感谢樊哲老师的指导。以下列出关于这次Mahout分类的学习和遇到的问题，还请大家多多提出建议：（全部文件操作都使用是在hdfs上边进行的）。
（本人用的环境是Mahout0.9+hadoop-2.2.0）
一、首先将预分类文件转换为序列化化存储：
下边图片列出的是使用的20newsgroup数据（我使用的linux上的eclipse。然后在eclipse上边安装的eclipse-hadoop插件）,数据图片例如以下：
然后编写java代码将此20newsgroup分类文件转换为sequence文件存储，例如以下图：
运行上边的程序，最后生成下列序列化文件：
敲代码查看序列化文件的内容例如以下：
二、将序列化文件转储为向量文件：
输入上边的序列化文件的输出结果将序列化文件转换为向量文件。转换java代码例如以下：
转换为向量文件结果例如以下图所看到的：
使用java程序查看向量文件的tfidf-vectors下的part-m-00000内容例如以下（一部分结果）：
key= /hdfs://h1:9000/classifier/classifier-src4/20news-bydate-train/sci.med/58064 value= /hdfs://h1:9000/classifier/classifier-src4/20news-bydate-train/sci.med/58064:{40949:4.404207229614258,58885:6.966500282287598,52884:1.404096007347107,54411:6.043336868286133,25074:16.67474365234375,20175:6.222922325134277,32290:7.155742168426514,57777:6.696209907531738,59820:5.825411796569824,53261:5.4359564781188965,15068:9.235183715820312,68017:4.232685565948486,47050:9.235183715820312,39193:8.724358558654785,56670:3.387782096862793,69370:1.5702117681503296,21521:7.7688469886779785,54393:5.597597599029541,62286:4.329909324645996,11644:7.128331661224365,12511:1.7634414434432983,17861:4.079967498779297,39895:7.338063716888428,55445:7.62574577331543,50765:9.235183715820312,41274:7.338063716888428,19358:7.155742168426514,19837:9.235183715820312,46237:9.235183715820312,24355:2.2430875301361084,52769:7.289273738861084,24217:1.9966870546340942,19749:3.0007731914520264,28651:7.114920139312744,24284:2.4492197036743164,61132:6.2394514083862305,39146:5.458599090576172,34340:7.289273738861084,34936:7.443424224853516,10911:6.129103660583496,12647:8.254354476928711,47554:1.0402182340621948,40788:7.338063716888428,10482:7.037959098815918,62155:3.3696606159210205,33813:1.230707049369812,24044:8.947502136230469,63344:5.73867654800415,68080:6.2394514083862305,17029:5.118860244750977,65110:7.075699806213379,32127:5.7694478034973145,30288:3.71773099899292,13537:3.087428092956543,11545:8.254354476928711,47708:7.935900688171387,47276:2.321446418762207,24045:8.947502136230469,56652:3.911620616912842,10107:12.653678894042969,10233:3.475231170654297,34068:5.321562767028809,58884:7.338063716888428,68165:1.6761456727981567,40591:9.235183715820312,47733:11.100005149841309,58624:4.493154525756836,50783:11.100005149841309,44628:6.572596073150635}
key= /hdfs://h1:9000/classifier/classifier-src4/20news-bydate-train/talk.politics.guns/54390 value= /hdfs://h1:9000/classifier/classifier-src4/20news-bydate-train/talk.politics.guns/54390:{25902:9.235183715820312,47590:4.066595554351807,48033:3.2437193393707275,67021:2.7126009464263916,24472:8.947502136230469,44782:1.9297716617584229,42373:5.015676021575928,24015:2.4575374126434326,11106:1.9394488334655762,42273:2.070721387863159,62394:3.628157138824463,61226:7.848889350891113,44453:2.7429440021514893,21501:15.389477729797363,32332:3.7448697090148926,64726:1.9358370304107666,48742:7.499622821807861,60003:15.995806694030762,50448:4.258450031280518,14327:3.194135904312134,50798:7.7688469886779785,47387:3.7190706729888916,47554:1.0402182340621948,11201:3.9916746616363525,53791:2.5926971435546875,19329:7.785928249359131,52953:2.958540439605713,13970:5.588863849639893,46327:8.387886047363281,58697:4.107259273529053,49227:15.995806694030762,18911:6.383354663848877,50439:3.510509967803955,9861:1.9852583408355713,56602:3.647935152053833,50458:1.7995492219924927,36905:5.748828887939453,66718:5.264892101287842,33813:2.7519447803497314,68017:2.9929606914520264,23442:3.458564043045044,1890:3.5897369384765625,44013:5.357062339782715,35455:3.657973051071167,65123:2.995558023452759,56080:7.561207294464111,40309:4.490251541137695,26572:8.628969192504883,23439:3.0159199237823486,27894:5.060796737670898,46052:1.8622281551361084,18320:5.84535026550293,17803:3.757326602935791,33291:1.8489196300506592}
key= /hdfs://h1:9000/classifier/classifier-src4/20news-bydate-train/comp.windows.x/67312 value= /hdfs://h1:9000/classifier/classifier-src4/20news-bydate-train/comp.windows.x/67312:{47554:1.0402182340621948,6258:3.1925511360168457,33291:1.8489196300506592,788:5.197997570037842,32485:4.425988674163818,53061:4.7731146812438965,68774:6.114288330078125,4487:4.123196125030518,65155:4.61021089553833,65670:5.0815229415893555,5285:10.784433364868164,50458:1.7995492219924927,35455:5.173154830932617,46052:1.8622281551361084,27311:8.298446655273438,8749:3.7985548973083496,26321:6.401970386505127,4587:13.633935928344727,1109:3.6212668418884277,34867:6.085300922393799,41201:3.171398639678955,25533:13.633935928344727}
三、生成训练模型：
输入上边生成的tfidf-vectors下的part-m-00000文件生成训练模型详细代码例如以下：
生成结果例如以下图所看到的：
（1）、训练模型
（2）、indexlabel文件
经过查看indexlabel的内容发现indexlabel不对。
indexlabel的内容例如以下：（显然不对不知道为什么。网上搜了非常多内容都没有解决掉错误）
key= hdfs: value= 0
自己尝试的解决的方法改动Mahout源代码的org.apache.mahout.classifier.naivebayes.BayesUtils.java中代码toString())[1]改为toString())[7],例如以下图所看到的：
这里改动这个数组下标的原因是BayesUtils.java默认使用”/”来分隔文件夹。数组的toString())[7]正好是所须要的文件类型标识。
改为：
这时候indexlabel文件内容为（总共20个类型标识显示正确）。例如以下图所看到的：
但是在运行训练模型的时候又出现了新的错误。。（例如以下运行过程所看到的）：
2014-07-21 20:45:27,738 INFO [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) – mapred.input.dir is deprecated. Instead, use mapreduce.input.fileinputformat.inputdir
2014-07-21 20:45:27,738 INFO [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) – mapred.compress.map.output is deprecated. Instead, use mapreduce.map.output.compress
2014-07-21 20:45:27,738 INFO [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) – mapred.output.dir is deprecated. Instead, use mapreduce.output.fileoutputformat.outputdir
2014-07-21 20:45:27,837 INFO [main] client.RMProxy (RMProxy.java:createRMProxy(56)) – Connecting to ResourceManager at h1/192.168.1.130:8032
2014-07-21 20:45:28,085 WARN [main] mapreduce.JobSubmitter (JobSubmitter.java:copyAndConfigureFiles(149)) – Hadoop command-line option parsing not performed. Implement the Tool interface and execute your application with ToolRunner to remedy this.
2014-07-21 20:45:28,963 INFO [main] input.FileInputFormat (FileInputFormat.java:listStatus(287)) – Total input paths to process : 1
2014-07-21 20:45:29,025 INFO [main] mapreduce.JobSubmitter (JobSubmitter.java:submitJobInternal(394)) – number of splits:1
2014-07-21 20:45:29,036 INFO [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) – user.name is deprecated. Instead, use mapreduce.job.user.name
2014-07-21 20:45:29,037 INFO [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) – mapred.jar is deprecated. Instead, use mapreduce.job.jar
2014-07-21 20:45:29,037 INFO [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) – mapred.cache.files.filesizes is deprecated. Instead, use mapreduce.job.cache.files.filesizes
2014-07-21 20:45:29,037 INFO [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) – mapred.cache.files is deprecated. Instead, use mapreduce.job.cache.files
2014-07-21 20:45:29,038 INFO [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) – mapred.output.value.class is deprecated. Instead, use mapreduce.job.output.value.class
2014-07-21 20:45:29,038 INFO [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) – mapred.mapoutput.value.class is deprecated. Instead, use mapreduce.map.output.value.class
2014-07-21 20:45:29,038 INFO [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) – mapreduce.combine.class is deprecated. Instead, use mapreduce.job.combine.class
2014-07-21 20:45:29,045 INFO [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) – mapreduce.map.class is deprecated. Instead, use mapreduce.job.map.class
2014-07-21 20:45:29,045 INFO [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) – mapred.job.name is deprecated. Instead, use mapreduce.job.name
2014-07-21 20:45:29,046 INFO [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) – mapreduce.reduce.class is deprecated. Instead, use mapreduce.job.reduce.class
2014-07-21 20:45:29,046 INFO [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) – mapreduce.inputformat.class is deprecated. Instead, use mapreduce.job.inputformat.class
2014-07-21 20:45:29,046 INFO [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) – mapreduce.outputformat.class is deprecated. Instead, use mapreduce.job.outputformat.class
2014-07-21 20:45:29,046 INFO [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) – mapred.map.tasks is deprecated. Instead, use mapreduce.job.maps
2014-07-21 20:45:29,046 INFO [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) – mapred.cache.files.timestamps is deprecated. Instead, use mapreduce.job.cache.files.timestamps
2014-07-21 20:45:29,046 INFO [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) – mapred.output.key.class is deprecated. Instead, use mapreduce.job.output.key.class
2014-07-21 20:45:29,047 INFO [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) – mapred.mapoutput.key.class is deprecated. Instead, use mapreduce.map.output.key.class
2014-07-21 20:45:29,047 INFO [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(840)) – mapred.working.dir is deprecated. Instead, use mapreduce.job.working.dir
2014-07-21 20:45:29,110 INFO [main] mapreduce.JobSubmitter (JobSubmitter.java:printTokens(477)) – Submitting tokens for job: job_1405911825122_0013
2014-07-21 20:45:29,310 INFO [main] impl.YarnClientImpl (YarnClientImpl.java:submitApplication(174)) – Submitted application application_1405911825122_0013 to ResourceManager at h1/192.168.1.130:8032
2014-07-21 20:45:29,349 INFO [main] mapreduce.Job (Job.java:submit(1272)) – The url to track the job: http://h1:8088/proxy/application_1405911825122_0013/
2014-07-21 20:45:29,349 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1317)) – Running job: job_1405911825122_0013
2014-07-21 20:45:34,926 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1338)) – Job job_1405911825122_0013 running in uber mode : false
2014-07-21 20:45:34,928 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1345)) – map 0% reduce 0%
2014-07-21 20:45:44,229 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1345)) – map 100% reduce 0%
2014-07-21 20:45:49,803 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1345)) – map 100% reduce 100%
2014-07-21 20:45:49,818 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1356)) – Job job_1405911825122_0013 completed successfully
2014-07-21 20:45:49,910 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1363)) – Counters: 44
File System Counters
FILE: Number of bytes read=680
FILE: Number of bytes written=161999
FILE: Number of read operations=0
FILE: Number of large read operations=0
FILE: Number of write operations=0
HDFS: Number of bytes read=18538518
HDFS: Number of bytes written=97
HDFS: Number of read operations=7
HDFS: Number of large read operations=0
HDFS: Number of write operations=2
Job Counters
Launched map tasks=1
Launched reduce tasks=1
Data-local map tasks=1
Total time spent by all maps in occupied slots (ms)=42768
Total time spent by all reduces in occupied slots (ms)=2352
Map-Reduce Framework
Map input records=11314
Map output records=0
Map output bytes=0
Map output materialized bytes=14
Input split bytes=151
Combine input records=0
Combine output records=0
Reduce input groups=0
Reduce shuffle bytes=14
Reduce input records=0
Reduce output records=0
Spilled Records=0
Shuffled Maps =1
Failed Shuffles=0
Merged Map outputs=1
GC time elapsed (ms)=427
CPU time spent (ms)=3470
Physical memory (bytes) snapshot=270143488
Virtual memory (bytes) snapshot=808521728
Total committed heap usage (bytes)=201457664
Shuffle Errors
BAD_ID=0
CONNECTION=0
IO_ERROR=0
WRONG_LENGTH=0
WRONG_MAP=0
WRONG_REDUCE=0
File Input Format Counters
Bytes Read=18538367
File Output Format Counters
Bytes Written=97
org.apache.mahout.classifier.naivebayes.training.IndexInstancesMapper$Counter
SKIPPED_INSTANCES=11314
2014-07-21 20:45:49,934 INFO [main] client.RMProxy (RMProxy.java:createRMProxy(56)) – Connecting to ResourceManager at h1/192.168.1.130:8032
2014-07-21 20:45:49,961 WARN [main] mapreduce.JobSubmitter (JobSubmitter.java:copyAndConfigureFiles(149)) – Hadoop command-line option parsing not performed. Implement the Tool interface and execute your application with ToolRunner to remedy this.
2014-07-21 20:45:50,218 INFO [main] input.FileInputFormat (FileInputFormat.java:listStatus(287)) – Total input paths to process : 1
2014-07-21 20:45:50,245 INFO [main] mapreduce.JobSubmitter (JobSubmitter.java:submitJobInternal(394)) – number of splits:1
2014-07-21 20:45:50,853 INFO [main] mapreduce.JobSubmitter (JobSubmitter.java:printTokens(477)) – Submitting tokens for job: job_1405911825122_0014
2014-07-21 20:45:50,905 INFO [main] impl.YarnClientImpl (YarnClientImpl.java:submitApplication(174)) – Submitted application application_1405911825122_0014 to ResourceManager at h1/192.168.1.130:8032
2014-07-21 20:45:50,908 INFO [main] mapreduce.Job (Job.java:submit(1272)) – The url to track the job: http://h1:8088/proxy/application_1405911825122_0014/
2014-07-21 20:45:50,908 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1317)) – Running job: job_1405911825122_0014
2014-07-21 20:46:01,907 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1338)) – Job job_1405911825122_0014 running in uber mode : false
2014-07-21 20:46:01,907 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1345)) – map 0% reduce 0%
2014-07-21 20:46:06,258 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1345)) – map 100% reduce 0%
2014-07-21 20:46:11,815 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1345)) – map 100% reduce 100%
2014-07-21 20:46:11,824 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1356)) – Job job_1405911825122_0014 completed successfully
2014-07-21 20:46:11,852 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1363)) – Counters: 43
File System Counters
FILE: Number of bytes read=22
FILE: Number of bytes written=162241
FILE: Number of read operations=0
FILE: Number of large read operations=0
FILE: Number of write operations=0
HDFS: Number of bytes read=237
HDFS: Number of bytes written=90
HDFS: Number of read operations=7
HDFS: Number of large read operations=0
HDFS: Number of write operations=2
Job Counters
Launched map tasks=1
Launched reduce tasks=1
Data-local map tasks=1
Total time spent by all maps in occupied slots (ms)=12960
Total time spent by all reduces in occupied slots (ms)=2214
Map-Reduce Framework
Map input records=0
Map output records=0
Map output bytes=0
Map output materialized bytes=14
Input split bytes=140
Combine input records=0
Combine output records=0
Reduce input groups=0
Reduce shuffle bytes=14
Reduce input records=0
Reduce output records=0
Spilled Records=0
Shuffled Maps =1
Failed Shuffles=0
Merged Map outputs=1
GC time elapsed (ms)=31
CPU time spent (ms)=1390
Physical memory (bytes) snapshot=300437504
Virtual memory (bytes) snapshot=809414656
Total committed heap usage (bytes)=225509376
Shuffle Errors
BAD_ID=0
CONNECTION=0
IO_ERROR=0
WRONG_LENGTH=0
WRONG_MAP=0
WRONG_REDUCE=0
File Input Format Counters
Bytes Read=97
File Output Format Counters
Bytes Written=90
Exception in thread “main” java.lang.NullPointerException
at com.google.common.base.Preconditions.checkNotNull(Preconditions.java:187)
at org.apache.mahout.classifier.naivebayes.BayesUtils.readModelFromDir(BayesUtils.java:81)
at org.apache.mahout.classifier.naivebayes.training.TrainNaiveBayesJob.run(TrainNaiveBayesJob.java:162)
at com.redhadoop.trainnb.TrainnbTest.main(TrainnbTest.java:48)
所指的BayesUtils.java 81行的代码例如以下：
四、使用训练模型进行測试
測试的java代码例如以下：
測试结果（明显不对）：
在这一块奋斗好几个日日夜夜，但是错误（上面的红色部分）还是没有解决。还是无奈。。求大神帮忙o(╯□╰)o。
Original: https://www.cnblogs.com/bhlsheji/p/5411394.html
Author: phlsheji
Title: mahout分类学习和遇到的问题总结
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