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* to you under the Apache License, Version 2.0 (the
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*
* http://www.apache.org/licenses/LICENSE-2.0
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package org.apache.flink.training.exercises.hourlytips.scala
import org.apache.flink.api.java.utils.ParameterTool
import org.apache.flink.streaming.api.TimeCharacteristic
import org.apache.flink.streaming.api.scala._
import org.apache.flink.training.exercises.common.sources.TaxiFareSource
import org.apache.flink.training.exercises.common.utils.ExerciseBase._
import org.apache.flink.training.exercises.common.utils.{ExerciseBase, MissingSolutionException}
/**
* The "Hourly Tips" exercise of the Flink training in the docs.
*
* The task of the exercise is to first calculate the total tips collected by each driver, hour by hour, and
* then from that stream, find the highest tip total in each hour.
*
* Parameters:
* -input path-to-input-file
*/
object HourlyTipsExercise {
def main(args: Array[String]) {
// read parameters
val params = ParameterTool.fromArgs(args)
val input = params.get("input", ExerciseBase.PATH_TO_FARE_DATA)
val maxDelay = 60 // events are delayed by at most 60 seconds
val speed = 600 // events of 10 minutes are served in 1 second
// set up streaming execution environment
val env = StreamExecutionEnvironment.getExecutionEnvironment
env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime)
env.setParallelism(ExerciseBase.parallelism)
// start the data generator
val fares = env.addSource(fareSourceOrTest(new TaxiFareSource(input, maxDelay, speed)))
throw new MissingSolutionException()
// print result on stdout
// printOrTest(hourlyMax)
// execute the transformation pipeline
env.execute("Hourly Tips (scala)")
}
}