Mahout: 1-> Configuration, recommenderintro, resource reference

Configuration:

Maven: Download, configuration, used to compile mahout In the mahout directory MVN install

Eclipse: Import jars and compile the test example.

Hadoop: distributed

Mahout: Download, configure/etc/profile

Recommendation System instance:

1. Create a Java project and a new class test

2. Reference: http://blog.csdn.net/aidayei/article/details/6626699

 Package  Org. Apache. mahout. FPM. pfpgrowth;


  Import  Org. Apache. mahout. Cf. Taste. impl. model. File.  *  ;
  Import  Org. Apache. mahout. Cf. Taste. impl. Neighborhood. *  ;
  Import  Org. Apache. mahout. Cf. Taste. impl. recommender.  *  ;
  Import  Org. Apache. mahout. Cf. Taste. impl. similarity.  *  ;
  Import  Org. Apache. mahout. Cf. Taste. model.  *  ;
  Import Org. Apache. mahout. Cf. Taste. Neighborhood.  *  ;
  Import  Org. Apache. mahout. Cf. Taste. recommender.  *  ;
  Import  Org. Apache. mahout. Cf. Taste. similarity.  *  ;
  Import  Java. Io.  *  ;
  Import Java. util.  *  ;
  Public     Class  Test {
  Private  Test (){};

  Public     Static     Void  Main (string ARGs [])  Throws  Exception {
 //  Step: 1 build model 2 calculate similarity 3 search K close to 4 construct recommendation engine  
  Datamodel Model  =  New  Filedatamodel (  New  File (  "  /Usr/hadoop/testdata/cf.txt  "  ));  //  The file name must be an absolute path.  
 Usersimilarity Similarity  =  New  Pearsoncorrelationsimilarity (model );
Userneighborhood neighborhood  =  New  Nearestnuserneighborhood (  2  , Similarity, model );
Recommender recommender  =     New  Genericuserbasedrecommender (model, neighborhood, similarity );
List  < Recommendeditem  >  Recommendations  =  Recommender. Recommend (  1  ,  2  );  //  Two itemids are recommended for user 1.  
    For  (Recommendeditem recommendatf0 \} 

Data preparation: test.txt

The first column is userid, the second column is Itemid, and the third column is preference value.

1  ,  101  ,  5  
  1  ,  102  ,  3  
  1  ,  103  ,  2.5  
 2  ,  101  ,  2  
  2  ,  102  ,  2.5  
  2  ,  103  ,  5  
 2  ,  104  ,  2  
  3  ,  101  ,  2.5  
  3  ,  104  ,  4  
 3  ,  105  ,  4.5  
  3  ,  107  ,  5  
  4  ,  101  ,  5  
 4  ,  103  ,  3  
  4  ,  104  ,  4.5  
  4  ,  106  ,  4  
 5  ,  101  ,  4  
  5  ,  102  ,  3  
  5  ,  103  ,  2  
 5  ,  104  ,  4  
  5  ,  105  ,  3.5  
  5  ,  106  ,  4 

Output:

Recommendeditem [item:104, Value:4.257081]
Recommendeditem [item:106, Value:4.0]
 

Resource reference

1. Configuration: http://blog.csdn.net/chjshan55/article/details/5923646. Senior: http://hi.baidu.com/czb_xyls/blog/item/76019d02cfa3cd101c95833a.html

2. Test and read the files in HDFS. It was originally serialized to HDFS and should be read using commands: Bin/mahout vectordump -- seqfile/user/hadoopuser/output/data/part-00000

Problem:

1. What command is used to read files from HDFS to a local file?

2.AlgorithmHow is internal execution performed? How does recommendation system parallelization work?