I have a DataSet
read from a CSV file:
val dataSet = env.readCsvFile[ElecNormNew](
getClass.getResource("/elecNormNew.arff").getPath,
pojoFields = Array("date", "day", "period", "nswprice", "nswdemand", "vicprice", "vicdemand", "transfer", "label")
As far as I know, ElecNormNew
is a POJO:
// elecNormNew POJO
class ElecNormNew(
var date: Double,
var day: Int,
var period: Double,
var nswprice: Double,
var nswdemand: Double,
var vicprice: Double,
var vicdemand: Double,
var transfer: Double,
var label: String) extends Serializable {
def this() = {
this(0, 0, 0, 0, 0, 0, 0, 0, "")
}
}
I also have a simple class:
case class Discretizer[T](
data: DataSet[T],
nBins: Int = 5,
s: Int = 1000) {
private[this] val log = LoggerFactory.getLogger("Discretizer")
private[this] val V = Vector.tabulate(10)(_ => IntervalHeap(nBins, 1, 1, s))
private[this] def updateSamples(x: T): Vector[IntervalHeap] = {
log.warn(s"$x")
V
}
def discretize() = {
data map (x => updateSamples(x))
}
}
But when I try to use it, from a test for example:
val a = new Discretizer[ElecNormNew](dataSet)
a.discretize
I am getting the following error:
org.apache.flink.api.common.InvalidProgramException: Task not serializable
// ...
[info] at com.elbauldelprogramador.discretizers.IDADiscretizer.discretize(IDADiscretizer.scala:69)
// ...
[info] Cause: java.io.NotSerializableException: org.apache.flink.api.scala.DataSet
// ...
I've read this questions and its answers, without luck:
I would say the first link you have mentioned provides the answer:
The problem is that you reference the DataSet pages from within a MapFunction. This is not possible, since a DataSet is only the logical representation of a data flow and cannot be accessed at runtime.
discretize
uses map
, so that applies also here.