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/mahoutMahout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 ~/.bashrcmahout环境变量
export MAHOUT_HOME=/home/hadoop/mahout
export MAHOUT_CONF_DIR=$MAHOUT_HOME/conf
export PATH=$MAHOUT_HOME/conf:$MAHOUT_HOME/bin:$PATHhadoop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 sequenceMahout 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.datahadoop 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.JobXX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 ./outputFound 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
时间： 2024-09-19 18:12:29