[jira] [Commented] (SPARK-8626) ALS model predict error

[Subhod Lagade (JIRA)]

    [ 
https://issues.apache.org/jira/browse/SPARK-8626?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14601002#comment-14601002
 ] 

Subhod Lagade commented on SPARK-8626:
--------------------------------------

/**
 * Created by subhod lagade on 25/06/15.
 */
import org.apache.spark.SparkConf
import org.apache.spark.streaming.StreamingContext._
import org.apache.spark.streaming.{Seconds, StreamingContext}
import org.apache.spark.streaming._;

import org.apache.spark.SparkContext
import org.apache.spark.SparkContext._



import java.io.BufferedReader;
import java.io.FileInputStream;
import java.io.IOException;
import java.io.InputStreamReader;
import java.io.PrintStream;
import java.net.ServerSocket;
import java.net.Socket;
import java.util.Properties;



import org.apache.spark.mllib.recommendation.ALS
import org.apache.spark.mllib.recommendation.MatrixFactorizationModel
import org.apache.spark.mllib.recommendation.Rating


object SparkStreamKafka {
  def main(args: Array[String]) {
        
    val conf = new SparkConf().setAppName("Simple Application");
    val sc = new SparkContext(conf);
        val data = sc.textFile("/home/appadmin/Disney/data.csv");
        val ratings = data.map(_.split(',') match { case Array(user, product, 
rate) =>  Rating(user.toInt, product.toInt, rate.toDouble)  });
        
        
        val rank = 3;
        val numIterations = 2;
        val model = ALS.train(ratings,rank,numIterations,0.01);
        

        val usersProducts = ratings.map{ case Rating(user, product, rate)  => 
(user, product)}

        // Build the recommendation model using ALS
        usersProducts.foreach(println)

        val predictions = model.predict(usersProducts)
        }
}

> ALS model predict error
> -----------------------
>
>                 Key: SPARK-8626
>                 URL: https://issues.apache.org/jira/browse/SPARK-8626
>             Project: Spark
>          Issue Type: Bug
>          Components: MLlib
>    Affects Versions: 1.4.0
>            Reporter: Subhod Lagade
>            Priority: Critical
>




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