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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,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
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 ml.load. 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 _ =>
throw new SparkException(s"SparkR ml.load does not support load $className")
}
}
}
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