Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/12573#discussion_r60676231
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/r/NaiveBayesWrapper.scala ---
@@ -74,4 +83,41 @@ private[r] object NaiveBayesWrapper {
.fit(data)
new NaiveBayesWrapper(pipeline, labels, features)
}
+
+ override def read: MLReader[NaiveBayesWrapper] = new
NaiveBayesWrapperReader
+
+ override def load(path: String): NaiveBayesWrapper = super.load(path)
+
+ class NaiveBayesWrapperWriter(instance: NaiveBayesWrapper) 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) ~
+ ("labels" -> parse(compact(render(instance.labels.toSeq)))) ~
+ ("features" -> parse(compact(render(instance.features.toSeq))))
+ val rMetadataJson: String = compact(render(rMetadata))
+ sc.parallelize(Seq(rMetadataJson), 1).saveAsTextFile(rMetadataPath)
--- End diff --
We use the same format as in ML pipelines. The output will be a folder
instead of a single file. Maybe users can zip that folder if they want to send
the model to someone else. Designing a new format is certainly beyond the scope
of this PR.
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