Mahout 安装配置及一个简单测试
Mahout 简介 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。 Hadoop http://blog.csdn.net/fenglailea/article/details/53318459 风.fox 环境 Centos7 服务器 当前最新版 0.12.2 Mahout下载地址 http://archive.apache.org/dist/mahout/ http://archive.apache.org/dist/mahout/0.12.2/ wget http://archive.apache.org/dist/mahout/0.12.2/apache-mahout-distribution-0.12.2.tar.gz tar -zxvf apache-mahout-distribution-0.12.2.tar.gz 这里放到 Hadoop 目录里 mv apache-mahout-distribution-0.12.2 /home/hadoop/mahout Mahout环境变量设置 设置全局/etc/bashrc，当前用户~/.bashrc 这里使用当前用户 vim ~/.bashrc mahout环境变量 export MAHOUT_HOME=/home/hadoop/mahout export MAHOUT_CONF_DIR=$MAHOUT_HOME/conf export PATH=$MAHOUT_HOME/conf:$MAHOUT_HOME/bin:$PATH hadoop环境变量 export HADOOP_HOME=/home/hadoop/hadoop export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop export PATH=$PATH:$HADOOP_HOME/bin export HADOOP_HOME_WARN_SUPPRESS=not_null 应用环境变量 . ~/.bashrc 查询是否安装成功, mahout 若出现一下，表示安装成功 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 cvb: : LDA via Collapsed Variation Bayes (0th deriv. approx) cvb0_local: : LDA via Collapsed Variation Bayes, in memory locally. describe: : Describe the fields and target variable in a data set 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 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 Mahout 和Hadoop 集成测试 首先，hadoop 要安装完成及启动 http://blog.csdn.net/fenglailea/article/details/53318459 下载测试数据 http://archive.ics.uci.edu/ml/databases/synthetic_control/ wget http://archive.ics.uci.edu/ml/databases/synthetic_control/synthetic_control.data hadoop 上传测试数据 hadoop fs -mkdir -p ./testdata hadoop fs -put synthetic_control.data ./testdata 查看目录及文件 hadoop fs -ls hadoop fs -ls ./testdata 使用Mahout中的kmeans聚类算法进行测试 mahout -core org.apache.mahout.clustering.syntheticcontrol.kmeans.Job XX执行完成,最后几行如下 1.0 : [distance=55.039831561905785]: [33.67,38.675,39.742,41.989,37.291,43.975,31.909,25.878,31.08,15.858,13.95,23.097,19.983,21.692,31.579,38.57,33.376,38.843,41.936,33.534,39.195,32.897,25.343,18.523,15.089,17.771,22.614,25.313,23.687,29.01,41.995,35.712,40.872,41.669,32.156,25.162,24.98,23.705,18.413,20.975,14.906,26.171,30.165,27.818,35.083,39.514,37.851,33.967,32.338,34.977,26.589,28.079,19.597,24.669,23.098,25.685,28.215,34.94,36.91,39.749] 16/11/24 16:47:52 INFO ClusterDumper: Wrote 6 clusters 16/11/24 16:47:52 INFO MahoutDriver: Program took 22175 ms (Minutes: 0.3695833333333333) 查看输出 hadoop fs -ls ./output Found 15 items -rw-r--r-- 1 hadoop supergroup 194 2016-11-24 16:47 output/_policy drwxr-xr-x - hadoop supergroup 0 2016-11-24 16:47 output/clusteredPoints drwxr-xr-x - hadoop supergroup 0 2016-11-24 16:47 output/clusters-0 drwxr-xr-x - hadoop supergroup 0 2016-11-24 16:47 output/clusters-1 drwxr-xr-x - hadoop supergroup 0 2016-11-24 16:47 output/clusters-10-final drwxr-xr-x - hadoop supergroup 0 2016-11-24 16:47 output/clusters-2 drwxr-xr-x - hadoop supergroup 0 2016-11-24 16:47 output/clusters-3 drwxr-xr-x - hadoop supergroup 0 2016-11-24 16:47 output/clusters-4 drwxr-xr-x - hadoop supergroup 0 2016-11-24 16:47 output/clusters-5 drwxr-xr-x - hadoop supergroup 0 2016-11-24 16:47 output/clusters-6 drwxr-xr-x - hadoop supergroup 0 2016-11-24 16:47 output/clusters-7 drwxr-xr-x - hadoop supergroup 0 2016-11-24 16:47 output/clusters-8 drwxr-xr-x - hadoop supergroup 0 2016-11-24 16:47 output/clusters-9 drwxr-xr-x - hadoop supergroup 0 2016-11-24 16:47 output/data drwxr-xr-x - hadoop supergroup 0 2016-11-24 16:47 output/random-seeds 查看数据 mahout vectordump -i ./output/data/part-m-00000 查看 http://itindex.net/detail/51681-mahout http://blog.csdn.net/wind520/article/details/38851367
