ride-cleansing/src/solution/scala/org/apache/flink/training/solutions/ridecleansing/scala/RideCleansingSolution.scala

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package org.apache.flink.training.solutions.ridecleansing.scala

import org.apache.flink.api.common.JobExecutionResult
import org.apache.flink.api.common.functions.FilterFunction
import org.apache.flink.streaming.api.functions.sink.{PrintSinkFunction, SinkFunction}
import org.apache.flink.streaming.api.functions.source.SourceFunction
import org.apache.flink.streaming.api.scala._
import org.apache.flink.training.exercises.common.datatypes.TaxiRide
import org.apache.flink.training.exercises.common.sources.TaxiRideGenerator
import org.apache.flink.training.exercises.common.utils.GeoUtils

/** Scala reference implementation for the Ride Cleansing exercise from the Flink training.
  *
  * The task of this exercise is to filter a data stream of taxi ride records to keep only
  * rides that both start and end within New York City. The resulting stream should be printed
  * to the standard out.
  */
object RideCleansingSolution {

  @throws[Exception]
  def main(args: Array[String]): Unit = {
    val job = new RideCleansingJob(new TaxiRideGenerator, new PrintSinkFunction)

    job.execute()
  }

  class RideCleansingJob(source: SourceFunction[TaxiRide], sink: SinkFunction[TaxiRide]) {

    /** Create and execute the ride cleansing pipeline.
      */
    @throws[Exception]
    def execute(): JobExecutionResult = {
      val env = StreamExecutionEnvironment.getExecutionEnvironment

      // set up the pipeline
      env
        .addSource(source)
        .filter(new NYCFilter())
        .addSink(sink)

      // execute the pipeline and return the result
      env.execute()
    }
  }

  /** Keep only those rides and both start and end in NYC. */
  class NYCFilter extends FilterFunction[TaxiRide] {
    override def filter(taxiRide: TaxiRide): Boolean =
      GeoUtils.isInNYC(taxiRide.startLon, taxiRide.startLat) &&
        GeoUtils.isInNYC(taxiRide.endLon, taxiRide.endLat)
  }
}