Use saved Spark mllib decision tree binary classification model to predict on new data - scala

Question

I am using Spark version 2.2.0 and scala version 2.11.8.
I created and saved a decision tree binary classification model using following code:
package...
import org.apache.spark.{SparkConf, SparkContext}
import org.apache.spark.mllib.tree.DecisionTree
import org.apache.spark.mllib.tree.model.DecisionTreeModel
import org.apache.spark.mllib.util.MLUtils
import org.apache.spark.sql.SparkSession
object DecisionTreeClassification {
def main(args: Array[String]): Unit = {
val sparkSession = SparkSession.builder
.master("local[*]")
.appName("Decision Tree")
.getOrCreate()
// Load and parse the data file.
val data = MLUtils.loadLibSVMFile(sparkSession.sparkContext, "path/to/file/xyz.txt")
// Split the data into training and test sets (20% held out for testing)
val splits = data.randomSplit(Array(0.8, 0.2))
val (trainingData, testData) = (splits(0), splits(1))
// Train a DecisionTree model.
// Empty categoricalFeaturesInfo indicates all features are continuous.
val numClasses = 2
val categoricalFeaturesInfo = Map[Int, Int]()
val impurity = "gini"
val maxDepth = 5
val maxBins = 32
val model = DecisionTree.trainClassifier(trainingData, numClasses, categoricalFeaturesInfo,
impurity, maxDepth, maxBins)
// Evaluate model on test instances and compute test error
val labelAndPreds = testData.map { point =>
val prediction = model.predict(point.features)
(point.label, prediction)
}
val testErr = labelAndPreds.filter(r => r._1 != r._2).count().toDouble / testData.count()
println(s"Test Error = $testErr")
println(s"Learned classification tree model:\n ${model.toDebugString}")
// Save and load model
model.save(sparkSession.sparkContext, "target/tmp/myDecisionTreeClassificationModel")
val sameModel = DecisionTreeModel.load(sparkSession.sparkContext, "target/tmp/myDecisionTreeClassificationModel")
// $example off$
sparkSession.sparkContext.stop()
}
}
Now, I want to predict a label (0 or 1) for a new data using this saved model. I am new to Spark, can anybody please let me know how to do that?

Answer 1

I found answer to this question so I thought I should share it if someone is looking for the answer to similar question
To make prediction for new data simply add few lines before stopping the spark session:
val newData = MLUtils.loadLibSVMFile(sparkSession.sparkContext, "path/to/file/abc.txt")
val newDataPredictions = newData.map
{ point =>
val newPrediction = model.predict(point.features)
(point.label, newPrediction)
}
newDataPredictions.foreach(f => println("Predicted label", f._2))