org.apache.spark.ml.recommendation.ALS.Rating Scala Examples

The following examples show how to use org.apache.spark.ml.recommendation.ALS.Rating. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example.
Example 1
Source File: RatingGenerator.scala    From spark-sql-perf   with Apache License 2.0 5 votes vote down vote up 
package com.databricks.spark.sql.perf.mllib.data

import org.apache.spark.ml.recommendation.ALS.Rating
import org.apache.spark.mllib.random.RandomDataGenerator

import scala.collection.mutable

class RatingGenerator(
    private val numUsers: Int,
    private val numProducts: Int,
    private val implicitPrefs: Boolean) extends RandomDataGenerator[Rating[Int]] {

  private val rng = new java.util.Random()

  private val observed = new mutable.HashMap[(Int, Int), Boolean]()

  override def nextValue(): Rating[Int] = {
    var tuple = (rng.nextInt(numUsers),rng.nextInt(numProducts))
    while (observed.getOrElse(tuple,false)){
      tuple = (rng.nextInt(numUsers),rng.nextInt(numProducts))
    }
    observed += (tuple -> true)

    val rating = if (implicitPrefs) rng.nextInt(2)*1.0 else rng.nextDouble()*5

    new Rating(tuple._1, tuple._2, rating.toFloat)
  }

  override def setSeed(seed: Long) {
    rng.setSeed(seed)
  }

  override def copy(): RatingGenerator =
    new RatingGenerator(numUsers, numProducts, implicitPrefs)
}