org.apache.spark.ml.r.RWrappers.scala Maven / Gradle / Ivy
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* Licensed to the Apache Software Foundation (ASF) under one or more
* 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
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
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* See the License for the specific language governing permissions and
* limitations under the License.
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package org.apache.spark.ml.r
import org.apache.hadoop.fs.Path
import org.json4s.DefaultFormats
import org.json4s.jackson.JsonMethods._
import org.apache.spark.SparkException
import org.apache.spark.ml.util.MLReader
/**
* This is the Scala stub of SparkR read.ml. It will dispatch the call to corresponding
* model wrapper loading function according the class name extracted from rMetadata of the path.
*/
private[r] object RWrappers extends MLReader[Object] {
override def load(path: String): Object = {
implicit val format = DefaultFormats
val rMetadataPath = new Path(path, "rMetadata").toString
val rMetadataStr = sc.textFile(rMetadataPath, 1).first()
val rMetadata = parse(rMetadataStr)
val className = (rMetadata \ "class").extract[String]
className match {
case "org.apache.spark.ml.r.NaiveBayesWrapper" => NaiveBayesWrapper.load(path)
case "org.apache.spark.ml.r.AFTSurvivalRegressionWrapper" =>
AFTSurvivalRegressionWrapper.load(path)
case "org.apache.spark.ml.r.GeneralizedLinearRegressionWrapper" =>
GeneralizedLinearRegressionWrapper.load(path)
case "org.apache.spark.ml.r.KMeansWrapper" =>
KMeansWrapper.load(path)
case "org.apache.spark.ml.r.MultilayerPerceptronClassifierWrapper" =>
MultilayerPerceptronClassifierWrapper.load(path)
case "org.apache.spark.ml.r.LDAWrapper" =>
LDAWrapper.load(path)
case "org.apache.spark.ml.r.IsotonicRegressionWrapper" =>
IsotonicRegressionWrapper.load(path)
case "org.apache.spark.ml.r.GaussianMixtureWrapper" =>
GaussianMixtureWrapper.load(path)
case "org.apache.spark.ml.r.ALSWrapper" =>
ALSWrapper.load(path)
case "org.apache.spark.ml.r.LogisticRegressionWrapper" =>
LogisticRegressionWrapper.load(path)
case "org.apache.spark.ml.r.RandomForestRegressorWrapper" =>
RandomForestRegressorWrapper.load(path)
case "org.apache.spark.ml.r.RandomForestClassifierWrapper" =>
RandomForestClassifierWrapper.load(path)
case "org.apache.spark.ml.r.DecisionTreeRegressorWrapper" =>
DecisionTreeRegressorWrapper.load(path)
case "org.apache.spark.ml.r.DecisionTreeClassifierWrapper" =>
DecisionTreeClassifierWrapper.load(path)
case "org.apache.spark.ml.r.GBTRegressorWrapper" =>
GBTRegressorWrapper.load(path)
case "org.apache.spark.ml.r.GBTClassifierWrapper" =>
GBTClassifierWrapper.load(path)
case "org.apache.spark.ml.r.BisectingKMeansWrapper" =>
BisectingKMeansWrapper.load(path)
case "org.apache.spark.ml.r.LinearSVCWrapper" =>
LinearSVCWrapper.load(path)
case "org.apache.spark.ml.r.FPGrowthWrapper" =>
FPGrowthWrapper.load(path)
case "org.apache.spark.ml.r.FMClassifierWrapper" =>
FMClassifierWrapper.load(path)
case "org.apache.spark.ml.r.LinearRegressionWrapper" =>
LinearRegressionWrapper.load(path)
case "org.apache.spark.ml.r.FMRegressorWrapper" =>
FMRegressorWrapper.load(path)
case _ =>
throw new SparkException(s"SparkR read.ml does not support load $className")
}
}
}