配置单元：

Question

我想将mahout与hive一起使用，我将从hive获取数据并使用数据模型来填充数据和使用mahout进行推荐。这可能吗。因为我看到mahout只适用于文件。 1）如何使用hive表将数据加载到mahout？ 2）有没有其他方法我可以使用mahout推荐与蜂巢或其他人？

这里我有hive jdbc结果，我想在mahout中填充到DataModel。如何填充？

我想使用数据库结果而不是从文件中读取mahout推荐。例如：

配置单元：

    import java.sql.SQLException;
    import java.sql.Connection;
    import java.sql.ResultSet;
    import java.sql.Statement;
    import java.sql.DriverManager;

    public class HiveJdbcClient {
      private static String driverName = "org.apache.hive.jdbc.HiveDriver";

      /**
       * @param args
       * @throws SQLException
       */
      public static void main(String[] args) throws SQLException {
          try {
          Class.forName(driverName);
        } catch (ClassNotFoundException e) {
          // TODO Auto-generated catch block
          e.printStackTrace();
          System.exit(1);
        }
        //replace "hive" here with the name of the user the queries should run as
        Connection con = DriverManager.getConnection("jdbc:hive2://localhost:10000/default", "hive", "");
        Statement stmt = con.createStatement();
        String tableName = "testHiveDriverTable";
        stmt.execute("drop table if exists " + tableName);
        stmt.execute("create table " + tableName + " (key int, value string)");
        // show tables
        String sql = "show tables '" + tableName + "'";
        System.out.println("Running: " + sql);
        ResultSet res = stmt.executeQuery(sql);
        if (res.next()) {
          System.out.println(res.getString(1));
        }
           // describe table
        sql = "describe " + tableName;
        System.out.println("Running: " + sql);
        res = stmt.executeQuery(sql);
        while (res.next()) {
          System.out.println(res.getString(1) + "\t" + res.getString(2));
        }

        // load data into table
        // NOTE: filepath has to be local to the hive server
        // NOTE: /tmp/a.txt is a ctrl-A separated file with two fields per line
        String filepath = "/tmp/a.txt";
        sql = "load data local inpath '" + filepath + "' into table " + tableName;
        System.out.println("Running: " + sql);
        stmt.execute(sql);

        // select * query
        sql = "select * from " + tableName;
        System.out.println("Running: " + sql);
        res = stmt.executeQuery(sql);
        while (res.next()) {
          System.out.println(String.valueOf(res.getInt(1)) + "\t" + res.getString(2));
        }

        // regular hive query
        sql = "select count(1) from " + tableName;
        System.out.println("Running: " + sql);
        res = stmt.executeQuery(sql);
        while (res.next()) {
          System.out.println(res.getString(1));
        }
      }
    }

象夫：

// Create a data source from the CSV file
File userPreferencesFile = new File("data/dataset1.csv");
DataModel dataModel = new FileDataModel(userPreferencesFile);

UserSimilarity userSimilarity = new PearsonCorrelationSimilarity(dataModel);
UserNeighborhood userNeighborhood = new NearestNUserNeighborhood(2, userSimilarity, dataModel);

// Create a generic user based recommender with the dataModel, the userNeighborhood and the userSimilarity
Recommender genericRecommender =  new GenericUserBasedRecommender(dataModel, userNeighborhood, userSimilarity);

// Recommend 5 items for each user
for (LongPrimitiveIterator iterator = dataModel.getUserIDs(); iterator.hasNext();)
{
    long userId = iterator.nextLong();

    // Generate a list of 5 recommendations for the user
    List<RecommendedItem> itemRecommendations = genericRecommender.recommend(userId, 5);

    System.out.format("User Id: %d%n", userId);

    if (itemRecommendations.isEmpty())
    {`enter code here
        System.out.println("No recommendations for this user.");
    }
    else
    {
        // Display the list of recommendations
        for (RecommendedItem recommendedItem : itemRecommendations)
        {
            System.out.format("Recommened Item Id %d. Strength of the preference: %f%n", recommendedItem.getItemID(), recommendedItem.getValue());
        }
    }
 }

Answer 1

Mahout 0.9版提供了JDBC投诉数据库（如MySQL / Oracle / Postgress等），NoSQL数据库（如MongoDB / HBase / Cassandra）和基于文件系统的数据模型（源数据）。

在此版本中，Hive不是100％SQL标准数据库，数据模型MySQLJDBCDataModel和SQL92JDBCDataModel不适合用于Hive表，因为JDBC注释数据库中的SQL语法非常不同。

对于您的第一个问题，您可能希望扩展AbstractJDBCDataModel并覆盖构造函数以传递Hive数据源，并针对首选项，首选项时间，用户，所有用户等传递特定的SQL查询，类似于上面提到的那些在AbstractJDBCDataModel构造函数中。

对于第二个问题，如果您使用的是非分布式算法（Taste算法），则上述方法会很好。如果使用分布式算法，Mahout可以在Hadoop上运行，从而获取由Hive表支持的HDFS文件。关于在Hadoop上运行Mahout

，请参阅here

整合Hive与Mahout推荐

配置单元：

象夫：

1 个答案: