Mahout快速入门教程

       Mahout 是一个很强大的数据挖掘工具，是一个分布式机器学习算法的集合，包括：被称为Taste的分布式协同过滤的实现、分类、聚类等。Mahout最大的优点就是基于hadoop实现，把很多以前运行于单机上的算法，转化为了MapReduce模式，这样大大提升了算法可处理的数据量和处理性能。

一、Mahout安装、配置

1、下载并解压Mahout
http://archive.apache.org/dist/mahout/
tar -zxvf mahout-distribution-0.9.tar.gz

2、配置环境变量
# set mahout environment
export MAHOUT_HOME=/mnt/jediael/mahout/mahout-distribution-0.9
export MAHOUT_CONF_DIR=$MAHOUT_HOME/conf
export PATH=$MAHOUT_HOME/conf:$MAHOUT_HOME/bin:$PATH

3、安装mahout
[jediael@master mahout-distribution-0.9]$ pwd
/mnt/jediael/mahout/mahout-distribution-0.9
[jediael@master mahout-distribution-0.9]$ mvn install

4、验证Mahout是否安装成功
    执行命令mahout。若列出一些算法，则成功：

[jediael@master mahout-distribution-0.9]$ mahoutRunning on hadoop, using /mnt/jediael/hadoop-1.2.1/bin/hadoop and HADOOP_CONF_DIR=MAHOUT-JOB: /mnt/jediael/mahout/mahout-distribution-0.9/examples/target/mahout-examples-0.9-job.jarAn example program must be given as the first argument.Valid program names are:  arff.vector: : Generate Vectors from an ARFF file or directory  baumwelch: : Baum-Welch algorithm for unsupervised HMM training  canopy: : Canopy clustering  cat: : Print a file or resource as the logistic regression models would see it  cleansvd: : Cleanup and verification of SVD output  clusterdump: : Dump cluster output to text  clusterpp: : Groups Clustering Output In Clusters  cmdump: : Dump confusion matrix in HTML or text formats  concatmatrices: : Concatenates 2 matrices of same cardinality into a single matrix  cvb: : LDA via Collapsed Variation Bayes (0th deriv. approx)  cvb0_local: : LDA via Collapsed Variation Bayes, in memory locally.  evaluateFactorization: : compute RMSE and MAE of a rating matrix factorization against probes  fkmeans: : Fuzzy K-means clustering  hmmpredict: : Generate random sequence of observations by given HMM  itemsimilarity: : Compute the item-item-similarities for item-based collaborative filtering  kmeans: : K-means clustering  lucene.vector: : Generate Vectors from a Lucene index  lucene2seq: : Generate Text SequenceFiles from a Lucene index  matrixdump: : Dump matrix in CSV format  matrixmult: : Take the product of two matrices  parallelALS: : ALS-WR factorization of a rating matrix  qualcluster: : Runs clustering experiments and summarizes results in a CSV  recommendfactorized: : Compute recommendations using the factorization of a rating matrix  recommenditembased: : Compute recommendations using item-based collaborative filtering  regexconverter: : Convert text files on a per line basis based on regular expressions  resplit: : Splits a set of SequenceFiles into a number of equal splits  rowid: : Map SequenceFile<Text,VectorWritable> to {SequenceFile<IntWritable,VectorWritable>, SequenceFile<IntWritable,Text>}  rowsimilarity: : Compute the pairwise similarities of the rows of a matrix  runAdaptiveLogistic: : Score new production data using a probably trained and validated AdaptivelogisticRegression model  runlogistic: : Run a logistic regression model against CSV data  seq2encoded: : Encoded Sparse Vector generation from Text sequence files  seq2sparse: : Sparse Vector generation from Text sequence files  seqdirectory: : Generate sequence files (of Text) from a directory  seqdumper: : Generic Sequence File dumper  seqmailarchives: : Creates SequenceFile from a directory containing gzipped mail archives  seqwiki: : Wikipedia xml dump to sequence file  spectralkmeans: : Spectral k-means clustering  split: : Split Input data into test and train sets  splitDataset: : split a rating dataset into training and probe parts  ssvd: : Stochastic SVD  streamingkmeans: : Streaming k-means clustering  svd: : Lanczos Singular Value Decomposition  testnb: : Test the Vector-based Bayes classifier  trainAdaptiveLogistic: : Train an AdaptivelogisticRegression model  trainlogistic: : Train a logistic regression using stochastic gradient descent  trainnb: : Train the Vector-based Bayes classifier  transpose: : Take the transpose of a matrix  validateAdaptiveLogistic: : Validate an AdaptivelogisticRegression model against hold-out data set  vecdist: : Compute the distances between a set of Vectors (or Cluster or Canopy, they must fit in memory) and a list of Vectors  vectordump: : Dump vectors from a sequence file to text  viterbi: : Viterbi decoding of hidden states from given output states sequence

二、使用简单示例验证mahout
1、启动Hadoop
2、下载测试数据
           http://archive.ics.uci.edu/ml/databases/synthetic_control/链接中的synthetic_control.data
或者百度一下也很容易找到这个示例数据。
3、上传测试数据
hadoop fs -put synthetic_control.data testdata
4、 使用Mahout中的kmeans聚类算法，执行命令：
mahout -core  org.apache.mahout.clustering.syntheticcontrol.kmeans.Job
花费9分钟左右完成聚类 。
5、查看聚类结果
    执行hadoop fs -ls /user/root/output，查看聚类结果。

[jediael@master mahout-distribution-0.9]$ hadoop fs -ls outputFound 15 items-rw-r--r--   2 jediael supergroup        194 2015-03-07 15:07 /user/jediael/output/_policydrwxr-xr-x   - jediael supergroup          0 2015-03-07 15:07 /user/jediael/output/clusteredPointsdrwxr-xr-x   - jediael supergroup          0 2015-03-07 15:02 /user/jediael/output/clusters-0drwxr-xr-x   - jediael supergroup          0 2015-03-07 15:02 /user/jediael/output/clusters-1drwxr-xr-x   - jediael supergroup          0 2015-03-07 15:07 /user/jediael/output/clusters-10-finaldrwxr-xr-x   - jediael supergroup          0 2015-03-07 15:03 /user/jediael/output/clusters-2drwxr-xr-x   - jediael supergroup          0 2015-03-07 15:03 /user/jediael/output/clusters-3drwxr-xr-x   - jediael supergroup          0 2015-03-07 15:04 /user/jediael/output/clusters-4drwxr-xr-x   - jediael supergroup          0 2015-03-07 15:04 /user/jediael/output/clusters-5drwxr-xr-x   - jediael supergroup          0 2015-03-07 15:05 /user/jediael/output/clusters-6drwxr-xr-x   - jediael supergroup          0 2015-03-07 15:05 /user/jediael/output/clusters-7drwxr-xr-x   - jediael supergroup          0 2015-03-07 15:06 /user/jediael/output/clusters-8drwxr-xr-x   - jediael supergroup          0 2015-03-07 15:07 /user/jediael/output/clusters-9drwxr-xr-x   - jediael supergroup          0 2015-03-07 15:02 /user/jediael/output/datadrwxr-xr-x   - jediael supergroup          0 2015-03-07 15:02 /user/jediael/output/random-seeds