Subhod Lagade created SPARK-8627: ------------------------------------ Summary: ALS model predict error Key: SPARK-8627 URL: https://issues.apache.org/jira/browse/SPARK-8627 Project: Spark Issue Type: Bug Components: MLlib Affects Versions: 1.4.0 Reporter: Subhod Lagade
/** * 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) } } /* ERROR Message [ERROR] /home/appadmin/disneypoc/src/main/scala/org/capgemini/SparkKafka.scala:53: error: not enough arguments for method predict: (user: Int, product: Int)Double. [INFO] Unspecified value parameter product. [INFO] val predictions = model.predict(usersProducts) */ -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org