Github user mengxr commented on a diff in the pull request: https://github.com/apache/spark/pull/5270#discussion_r28716769 --- Diff: mllib/src/main/scala/org/apache/spark/mllib/regression/IsotonicRegression.scala --- @@ -124,6 +131,74 @@ class IsotonicRegressionModel ( predictions(foundIndex) } } + + override def save(sc: SparkContext, path: String): Unit = { + IsotonicRegressionModel.SaveLoadV1_0.save(sc, path, boundaries, predictions, isotonic) + } + + override protected def formatVersion: String = "1.0" +} + +object IsotonicRegressionModel extends Loader[IsotonicRegressionModel] { + + import org.apache.spark.mllib.util.Loader._ + + private object SaveLoadV1_0 { + + def thisFormatVersion: String = "1.0" + + /** Hard-code class name string in case it changes in the future */ + def thisClassName: String = "org.apache.spark.mllib.regression.IsotonicRegressionModel" + + /** Model data for model import/export */ + case class Data(boundary: Double, prediction: Double) + + def save( + sc: SparkContext, + path: String, + boundaries: Array[Double], + predictions: Array[Double], + isotonic: Boolean): Unit = { + val sqlContext = new SQLContext(sc) + import sqlContext.implicits._ + + val metadata = compact(render( + ("class" -> thisClassName) ~ ("version" -> thisFormatVersion) ~ + ("isotonic" -> isotonic))) + sc.parallelize(Seq(metadata), 1).saveAsTextFile(metadataPath(path)) + + sqlContext.createDataFrame(boundaries.toSeq.zip(predictions) + .map { case (b, p) => Data(b, p) }).saveAsParquetFile(dataPath(path)) --- End diff -- Please see my previous comment about the code style here. The following has a better separation of the logic: ~~~scala sqlContext.createDataFrame( boundaries.toSeq.zip(predictions).map { case (b, p) => Data(b, p) } ).saveAsParquetFile(dataPath(path)) ~~~
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