Github user mengxr commented on a diff in the pull request: https://github.com/apache/spark/pull/3098#discussion_r24955674 --- Diff: mllib/src/main/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.scala --- @@ -35,33 +41,33 @@ import org.apache.spark.rdd.RDD * and the features computed for this product. */ class MatrixFactorizationModel private[mllib] ( - val rank: Int, - val userFeatures: RDD[(Int, Array[Double])], - val productFeatures: RDD[(Int, Array[Double])]) extends Serializable { + val rank: Int, + val userFeatures: RDD[(Int, Array[Double])], + val productFeatures: RDD[(Int, Array[Double])]) extends Serializable { /** Predict the rating of one user for one product. */ def predict(user: Int, product: Int): Double = { - val userVector = new DoubleMatrix(userFeatures.lookup(user).head) - val productVector = new DoubleMatrix(productFeatures.lookup(product).head) - userVector.dot(productVector) + val userVector = Vectors.dense(userFeatures.lookup(user).head) --- End diff -- Thanks for switching to BLAS.
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