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