学习Mahout(一)

Mahout 官方下载地址：http://apache.fayea.com/apache-mirror/mahout/

环境ubuntu 12.04， hadoop1.2.1 ，mahout 0.9 ， memory 2G

1 首先解压tar包

tar -zxvf /mnt/hgfs/mnt/mahout-distribution-0.9.tar.gz -C /opt/hadoop/

2 添加环境变量

export HADOOP_HOME=/opt/hadoop/hadoop-1.2.

export HADOOP_CONF_DIR=${HADOOP_HOME}/conf

export MAHOUT_HOME=/opt/hadoop/mahout-distribution-0.9

你也可以将上面的新增环境变量加入~/.bashrc文件中去

3 启动你的hadoop服务，这里不再累述，自己参考：http://www.cnblogs.com/chenfool/p/3574789.html

4 执行一下mahout

cd /opt/hadoop/mahout-distribution-0.9

bin/mahout --help

报错，错误信息：

Error occurred during initialization of VM
Could not reserve enough space for object heap
Could not create the Java virtual machine.

使用vi 打开bin/mahout查看，搜索JAVA_HEAP_MAX=-X

看到它写死：JAVA_HEAP_MAX=-Xmx3g

尼玛啊，什么机器能轻松给3G的内存，改写成JAVA_HEAP_MAX=-Xmx1g

再查找一下mapred.map.child.java.opts 、 mapred.reduce.child.java.opts ，都写着4096m，还让渣渣机器活吗？

自己根据自己机器实际情况调整参数，保存退出。

再执行

bin/mahout --help

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

证明mahout 环境部署成功了。

参考文章：

http://blog.sina.com.cn/s/blog_916b71bb0101jq44.html

http://samchu.logdown.com/posts/192574-mahout-09-installation-verification-records

巴特西

学习Mahout(一)

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