mahout安装配置

1.下载mahout

下载地址:http://mahout.apache.org

我下载的最新版：mahout-distribution-0.9

2.把mahout解压到你想存放的文档，我是放在/Users/jia/Documents/hadoop-0.20.2，即hadoop的安装目录上。

3.为mahout配置环境

打开终端，打开profile文件所在的目录

JIAS-MacBook-Pro:~ jia$ open /etc

把profile文件复制到桌面，然后编辑，在它后面加入环境变量

export JAVA_HOME=/Library/Java/JavaVirtualMachines/jdk1.8.0.jdk/Contents/Home
export HADOOP_HOME=Documents/hadoop-0.20.2
export MAHOUT_HOME=Documents/hadoop-0.20.2/mahout-distribution-0.9
export MAVEN_HOME=Documents/apache-maven-3.2.2

export PATH=$PATH:$JAVA_HOME/bin:$HADOOP_HOME/bin:$MAVEN_HOME/bin:$MAHOUT_HOME/bin

export HADOOP_CONF_DIR=Documents/hadoop-0.20.2/conf
export MAHOUT_CONF_DIR=Documents/hadoop-0.20.2/mahout-distribution-0.9/conf

export classpath=$classpath:$JAVA_HOME/lib:$MAHOUT_HOME/lib:$HADOOP_CONF_DIR:$MAHOUT_CONF_DIR

然后把桌面上的profile文件覆盖/etc上的profile，期间要输入管理员密码

注意：

1.如果在ubuntu下安装的是hadoop2.6进行配置的话,路径为：

export JAVA_HOME=/usr/lib/jvm/java-1.7.-openjdk-amd64
export HADOOP_HOME=/home/sendi/hadoop-2.6.
export MAHOUT_HOME=/home/sendi/mahout-distribution-0.9
export MAVEN_HOME=/home/sendi/apache-maven-3.3.

export PATH=$PATH:$JAVA_HOME/bin:$HADOOP_HOME/bin:$MAVEN_HOME/bin:$MAHOUT_HOME/bin

export HADOOP_CONF_DIR=/home/sendi/hadoop-2.6./etc/hadoop
export MAHOUT_CONF_DIR=/home/sendi/mahout-distribution-0.9/conf

export classpath=$classpath:$JAVA_HOME/lib:$MAHOUT_HOME/lib:$HADOOP_CONF_DIR:$MAHOUT_CONF_DIR

2.配置MAHOU_CONF_DIR时有些网站说时export MAHOUT_CONF_DIR=Documents/hadoop-0.20.2/mahout-distribution-0.9/src/conf

 0.9版本的正确配置是：export MAHOUT_CONF_DIR=Documents/hadoop-0.20.2/mahout-distribution-0.9/conf ，因为当你打开mahout文件夹时，发现没有src这个目录
 mahout官网上0.9版本有几个压缩文件，我自己试过，前面两个小压缩文件不行。 

这里我选择的是第5个78M的。

4.检验mahout是否配置成功

4.1启动hadoop

JIAS-MacBook-Pro:hadoop-0.20.2 jia$ bin/start-all.sh 

4.2查看mahout

JIAS-MacBook-Pro:mahout-distribution-0.9 jia$ bin/mahout
MAHOUT_LOCAL is not set; adding HADOOP_CONF_DIR to classpath.
hadoop binary is not in PATH,HADOOP_HOME/bin,HADOOP_PREFIX/bin, running locally
An 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

这里需要说明下，当你看到下面的代码时，以为是错的，其实不是，原因：

MAHOUT_LOCAL：设置是否本地运行，如果设置这个参数就不会运行hadoop了，一旦设置这个参数，那HADOOP_CONF_DIR 和HADOOP_HOME 这两个参数的

设置就自动失效了。

当初我就在这个问题上纠结了很久。

MAHOUT_LOCAL is not set; adding HADOOP_CONF_DIR to classpath.
hadoop binary is not in PATH,HADOOP_HOME/bin,HADOOP_PREFIX/bin, running locally

5.运行mahout的算法

5.1到下面的地址去下载测试数据

http://archive.ics.uci.edu/ml/databases/synthetic_control/synthetic_control.data

5.2创建测试目录testdata，并把数据导入到这个testdata目录中

JIAS-MacBook-Pro:hadoop-0.20.2 jia$ bin/hadoop fs -mkdir testdata

5.3把测试数据上传到hdfs上，不能把测试数据存在mac上用pages建立的文档上，而是建立一个新的文件命令：touch data

JIAS-MacBook-Pro:hadoop-0.20.2 jia$ bin/hadoop fs -put workspace/data testdata/

5.4运行mahout上的kmeans算法

JIAS-MacBook-Pro:hadoop-0.20.2 jia$ bin/hadoop jar mahout-distribution-0.9/mahout-examples-0.9-job.jar org.apache.mahout.clustering.syntheticcontrol.kmeans.Job

5.5查看结果

JIAS-MacBook-Pro:~ jia$ cd Documents/hadoop-0.20.2/
JIAS-MacBook-Pro:hadoop-0.20.2 jia$ bin/hadoop fs -ls output/
Found 15 items
-rwxrwxrwx   1 jia staff        194 2014-08-03 14:42 /Users/jia/Documents/hadoop-0.20.2/output/_policy
drwxr-xr-x   - jia staff        136 2014-08-03 14:42 /Users/jia/Documents/hadoop-0.20.2/output/clusteredPoints
drwxr-xr-x   - jia staff        544 2014-08-03 14:41 /Users/jia/Documents/hadoop-0.20.2/output/clusters-0
drwxr-xr-x   - jia staff        204 2014-08-03 14:41 /Users/jia/Documents/hadoop-0.20.2/output/clusters-1
drwxr-xr-x   - jia staff        204 2014-08-03 14:42 /Users/jia/Documents/hadoop-0.20.2/output/clusters-10-final
drwxr-xr-x   - jia staff        204 2014-08-03 14:41 /Users/jia/Documents/hadoop-0.20.2/output/clusters-2
drwxr-xr-x   - jia staff        204 2014-08-03 14:41 /Users/jia/Documents/hadoop-0.20.2/output/clusters-3
drwxr-xr-x   - jia staff        204 2014-08-03 14:41 /Users/jia/Documents/hadoop-0.20.2/output/clusters-4
drwxr-xr-x   - jia staff        204 2014-08-03 14:41 /Users/jia/Documents/hadoop-0.20.2/output/clusters-5
drwxr-xr-x   - jia staff        204 2014-08-03 14:41 /Users/jia/Documents/hadoop-0.20.2/output/clusters-6
drwxr-xr-x   - jia staff        204 2014-08-03 14:41 /Users/jia/Documents/hadoop-0.20.2/output/clusters-7
drwxr-xr-x   - jia staff        204 2014-08-03 14:42 /Users/jia/Documents/hadoop-0.20.2/output/clusters-8
drwxr-xr-x   - jia staff        204 2014-08-03 14:42 /Users/jia/Documents/hadoop-0.20.2/output/clusters-9
drwxr-xr-x   - jia staff        136 2014-08-03 14:41 /Users/jia/Documents/hadoop-0.20.2/output/data
drwxr-xr-x   - jia staff        136 2014-08-03 14:41 /Users/jia/Documents/hadoop-0.20.2/output/random-seeds