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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