Mahout-0.9的安装部署方法

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1、到官方下载最新版本

2、配置环境变量

export MAHOUT_HOME=/home/wukong/usr/mahout-0.9/export MAHOUT_CONF_DIR=/home/wukong/usr/mahout-0.9/confexport PATH=$PATH:$MAHOUT_HOME/conf:$MAHOUT_HOME/bin

3、启动测试

[wukong@bd23 ~]$ mahoutMAHOUT_LOCAL is not set; adding HADOOP_CONF_DIR to classpath.Running on hadoop, using /home/wukong/usr/hadoop-2.4.1/bin/hadoop and HADOOP_CONF_DIR=/home/wukong/usr/hadoop-2.4.1/etc/hadoop/MAHOUT-JOB: /home/wukong/usr/mahout-0.9/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 to {SequenceFile, SequenceFile}  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

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