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[SPARK-16241] [ML] model loading backward compatibility for ml NaiveBayes #13940

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[SPARK-16241] [ML] model loading backward compatibility for ml NaiveBayes #13940

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[SPARK-16241] [ML] model loading backward compatibility for ml NaiveB…
zlpmichelle Jun 28, 2016
ce83929
fix Scala style issue
zlpmichelle Jun 29, 2016
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11 changes: 7 additions & 4 deletions mllib/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala
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Expand Up @@ -28,8 +28,9 @@ import org.apache.spark.ml.util._
import org.apache.spark.mllib.classification.{NaiveBayes => OldNaiveBayes}
import org.apache.spark.mllib.classification.{NaiveBayesModel => OldNaiveBayesModel}
import org.apache.spark.mllib.regression.{LabeledPoint => OldLabeledPoint}
import org.apache.spark.mllib.util.MLUtils
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.Dataset
import org.apache.spark.sql.{Row, Dataset}
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@yanboliang yanboliang Jun 29, 2016

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Notice the import order, it should be import org.apache.spark.sql.{Dataset, Row}


/**
* Params for Naive Bayes Classifiers.
Expand Down Expand Up @@ -275,9 +276,11 @@ object NaiveBayesModel extends MLReadable[NaiveBayesModel] {
val metadata = DefaultParamsReader.loadMetadata(path, sc, className)

val dataPath = new Path(path, "data").toString
val data = sparkSession.read.parquet(dataPath).select("pi", "theta").head()
val pi = data.getAs[Vector](0)
val theta = data.getAs[Matrix](1)
val data = sparkSession.read.parquet(dataPath)
val vecConverted = MLUtils.convertVectorColumnsToML(data, "pi")
val Row(pi: Vector, theta: Matrix) = MLUtils.convertMatrixColumnsToML(vecConverted, "theta")
.select("pi", "theta")
.head()
val model = new NaiveBayesModel(metadata.uid, pi, theta)

DefaultParamsReader.getAndSetParams(model, metadata)
Expand Down