Reputation: 59
The vectorAssembler function in spark gives a vector[double] type as output, but i need to convert that to array[double].
I know that there is an inbuild Vector_to_array
function provided but i am not getting how to convert the column to array
some of the elements are sparse array as well.
var assembler = new VectorAssembler().setInputCols(Array("Pclass",
"Age",
"Fare",
"Gender",
"Boarded"
)).setOutputCol("features")
var transformedDF = assembler.setHandleInvalid("skip").transform(updatedDF)
this is the code and i need to convert the features column from vector to array type.
Upvotes: 0
Views: 971
Reputation: 524
Use alias for Vector depending on ml or mllib library, to not get confused with Scala's Vector
import org.apache.spark.ml.linalg.Vector => MLVector
import org.apache.spark.mllib.linalg.Vector => MLlibVector
Then create a UDF
// 1. function to map to Array[Double]
val vec2Array: Any => Array[Double] = {
vector => vector match {
case vec: MLVector => vec.toArray
case vec: MLlibVector => vec.toArray
}
}
// 2. User Defined Function (UDF)
val vec2ArrayUDF = udf(vec2Array)
// 3. apply UDF on "features" column
val df_vec2Array = transformedDF.withColumn("features_array",vec2ArrayUDF(col("features")))
Upvotes: 1