diff options
Diffstat (limited to 'mllib/src')
-rw-r--r-- | mllib/src/main/scala/org/apache/spark/ml/r/IsotonicRegressionWrapper.scala | 119 | ||||
-rw-r--r-- | mllib/src/main/scala/org/apache/spark/ml/r/RWrappers.scala | 2 |
2 files changed, 121 insertions, 0 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/ml/r/IsotonicRegressionWrapper.scala b/mllib/src/main/scala/org/apache/spark/ml/r/IsotonicRegressionWrapper.scala new file mode 100644 index 0000000000..1ea80cb46a --- /dev/null +++ b/mllib/src/main/scala/org/apache/spark/ml/r/IsotonicRegressionWrapper.scala @@ -0,0 +1,119 @@ +/* + * 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._ +import org.json4s.JsonDSL._ +import org.json4s.jackson.JsonMethods._ + +import org.apache.spark.ml.{Pipeline, PipelineModel} +import org.apache.spark.ml.attribute.{AttributeGroup} +import org.apache.spark.ml.feature.RFormula +import org.apache.spark.ml.regression.{IsotonicRegression, IsotonicRegressionModel} +import org.apache.spark.ml.util._ +import org.apache.spark.sql.{DataFrame, Dataset} + +private[r] class IsotonicRegressionWrapper private ( + val pipeline: PipelineModel, + val features: Array[String]) extends MLWritable { + + private val isotonicRegressionModel: IsotonicRegressionModel = + pipeline.stages(1).asInstanceOf[IsotonicRegressionModel] + + lazy val boundaries: Array[Double] = isotonicRegressionModel.boundaries.toArray + + lazy val predictions: Array[Double] = isotonicRegressionModel.predictions.toArray + + def transform(dataset: Dataset[_]): DataFrame = { + pipeline.transform(dataset).drop(isotonicRegressionModel.getFeaturesCol) + } + + override def write: MLWriter = new IsotonicRegressionWrapper.IsotonicRegressionWrapperWriter(this) +} + +private[r] object IsotonicRegressionWrapper + extends MLReadable[IsotonicRegressionWrapper] { + + def fit( + data: DataFrame, + formula: String, + isotonic: Boolean, + featureIndex: Int, + weightCol: String): IsotonicRegressionWrapper = { + + val rFormulaModel = new RFormula() + .setFormula(formula) + .setFeaturesCol("features") + .fit(data) + + // get feature names from output schema + val schema = rFormulaModel.transform(data).schema + val featureAttrs = AttributeGroup.fromStructField(schema(rFormulaModel.getFeaturesCol)) + .attributes.get + val features = featureAttrs.map(_.name.get) + require(features.size == 1) + + // assemble and fit the pipeline + val isotonicRegression = new IsotonicRegression() + .setIsotonic(isotonic) + .setFeatureIndex(featureIndex) + .setWeightCol(weightCol) + + val pipeline = new Pipeline() + .setStages(Array(rFormulaModel, isotonicRegression)) + .fit(data) + + new IsotonicRegressionWrapper(pipeline, features) + } + + override def read: MLReader[IsotonicRegressionWrapper] = new IsotonicRegressionWrapperReader + + override def load(path: String): IsotonicRegressionWrapper = super.load(path) + + class IsotonicRegressionWrapperWriter(instance: IsotonicRegressionWrapper) extends MLWriter { + + override protected def saveImpl(path: String): Unit = { + val rMetadataPath = new Path(path, "rMetadata").toString + val pipelinePath = new Path(path, "pipeline").toString + + val rMetadata = ("class" -> instance.getClass.getName) ~ + ("features" -> instance.features.toSeq) + val rMetadataJson: String = compact(render(rMetadata)) + sc.parallelize(Seq(rMetadataJson), 1).saveAsTextFile(rMetadataPath) + + instance.pipeline.save(pipelinePath) + } + } + + class IsotonicRegressionWrapperReader extends MLReader[IsotonicRegressionWrapper] { + + override def load(path: String): IsotonicRegressionWrapper = { + implicit val format = DefaultFormats + val rMetadataPath = new Path(path, "rMetadata").toString + val pipelinePath = new Path(path, "pipeline").toString + + val rMetadataStr = sc.textFile(rMetadataPath, 1).first() + val rMetadata = parse(rMetadataStr) + val features = (rMetadata \ "features").extract[Array[String]] + + val pipeline = PipelineModel.load(pipelinePath) + new IsotonicRegressionWrapper(pipeline, features) + } + } +} diff --git a/mllib/src/main/scala/org/apache/spark/ml/r/RWrappers.scala b/mllib/src/main/scala/org/apache/spark/ml/r/RWrappers.scala index 568c160ee5..f9a44d60e6 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/r/RWrappers.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/r/RWrappers.scala @@ -44,6 +44,8 @@ private[r] object RWrappers extends MLReader[Object] { GeneralizedLinearRegressionWrapper.load(path) case "org.apache.spark.ml.r.KMeansWrapper" => KMeansWrapper.load(path) + case "org.apache.spark.ml.r.IsotonicRegressionWrapper" => + IsotonicRegressionWrapper.load(path) case _ => throw new SparkException(s"SparkR read.ml does not support load $className") } |