org.apache.spark.ml.r.ALSWrapper.scala Maven / Gradle / Ivy
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* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
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package org.apache.spark.ml.r
import org.apache.hadoop.fs.Path
import org.json4s._
import org.json4s.JsonDSL._
import org.json4s.jackson.JsonMethods._
import org.apache.spark.ml.recommendation.{ALS, ALSModel}
import org.apache.spark.ml.util._
import org.apache.spark.sql.{DataFrame, Dataset}
private[r] class ALSWrapper private (
val alsModel: ALSModel,
val ratingCol: String) extends MLWritable {
lazy val userCol: String = alsModel.getUserCol
lazy val itemCol: String = alsModel.getItemCol
lazy val userFactors: DataFrame = alsModel.userFactors
lazy val itemFactors: DataFrame = alsModel.itemFactors
lazy val rank: Int = alsModel.rank
def transform(dataset: Dataset[_]): DataFrame = {
alsModel.transform(dataset)
}
override def write: MLWriter = new ALSWrapper.ALSWrapperWriter(this)
}
private[r] object ALSWrapper extends MLReadable[ALSWrapper] {
def fit( // scalastyle:ignore
data: DataFrame,
ratingCol: String,
userCol: String,
itemCol: String,
rank: Int,
regParam: Double,
maxIter: Int,
implicitPrefs: Boolean,
alpha: Double,
nonnegative: Boolean,
numUserBlocks: Int,
numItemBlocks: Int,
checkpointInterval: Int,
seed: Int): ALSWrapper = {
val als = new ALS()
.setRatingCol(ratingCol)
.setUserCol(userCol)
.setItemCol(itemCol)
.setRank(rank)
.setRegParam(regParam)
.setMaxIter(maxIter)
.setImplicitPrefs(implicitPrefs)
.setAlpha(alpha)
.setNonnegative(nonnegative)
.setNumBlocks(numUserBlocks)
.setNumItemBlocks(numItemBlocks)
.setCheckpointInterval(checkpointInterval)
.setSeed(seed.toLong)
val alsModel: ALSModel = als.fit(data)
new ALSWrapper(alsModel, ratingCol)
}
override def read: MLReader[ALSWrapper] = new ALSWrapperReader
override def load(path: String): ALSWrapper = super.load(path)
class ALSWrapperWriter(instance: ALSWrapper) extends MLWriter {
override protected def saveImpl(path: String): Unit = {
val rMetadataPath = new Path(path, "rMetadata").toString
val modelPath = new Path(path, "model").toString
val rMetadata = ("class" -> instance.getClass.getName) ~
("ratingCol" -> instance.ratingCol)
val rMetadataJson: String = compact(render(rMetadata))
sc.parallelize(Seq(rMetadataJson), 1).saveAsTextFile(rMetadataPath)
instance.alsModel.save(modelPath)
}
}
class ALSWrapperReader extends MLReader[ALSWrapper] {
override def load(path: String): ALSWrapper = {
implicit val format = DefaultFormats
val rMetadataPath = new Path(path, "rMetadata").toString
val modelPath = new Path(path, "model").toString
val rMetadataStr = sc.textFile(rMetadataPath, 1).first()
val rMetadata = parse(rMetadataStr)
val ratingCol = (rMetadata \ "ratingCol").extract[String]
val alsModel = ALSModel.load(modelPath)
new ALSWrapper(alsModel, ratingCol)
}
}
}