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/*
* Copyright 2017 data Artisans GmbH
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package com.dataartisans.flinktraining.exercises.datastream_scala.state
import com.dataartisans.flinktraining.exercises.datastream_java.datatypes.{TaxiFare, TaxiRide}
import com.dataartisans.flinktraining.exercises.datastream_java.sources.{TaxiFareSource, TaxiRideSource}
import com.dataartisans.flinktraining.exercises.datastream_java.utils.{ExerciseBase, MissingSolutionException}
import com.dataartisans.flinktraining.exercises.datastream_java.utils.ExerciseBase._
import org.apache.flink.api.common.state.{ValueState, ValueStateDescriptor}
import org.apache.flink.api.java.utils.ParameterTool
import org.apache.flink.configuration.Configuration
import org.apache.flink.streaming.api.TimeCharacteristic
import org.apache.flink.streaming.api.functions.co.RichCoFlatMapFunction
import org.apache.flink.streaming.api.scala.{StreamExecutionEnvironment, _}
import org.apache.flink.util.Collector
/**
* The "Stateful Enrichment" exercise of the Flink training
* (http://training.data-artisans.com).
*
* The goal for this exercise is to enrich TaxiRides with fare information.
*
* Parameters:
* -rides path-to-input-file
* -fares path-to-input-file
*
*/
object RidesAndFaresExercise {
def main(args: Array[String]) {
// parse parameters
val params = ParameterTool.fromArgs(args)
val ridesFile = params.get("rides", ExerciseBase.pathToRideData)
val faresFile = params.get("fares", ExerciseBase.pathToFareData)
val delay = 60; // at most 60 seconds of delay
val servingSpeedFactor = 1800 // 30 minutes worth of events are served every second
// set up streaming execution environment
val env = StreamExecutionEnvironment.getExecutionEnvironment
env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime)
env.setParallelism(ExerciseBase.parallelism)
val rides = env
.addSource(rideSourceOrTest(new TaxiRideSource(ridesFile, delay, servingSpeedFactor)))
.filter { ride => ride.isStart }
.keyBy("rideId")
val fares = env
.addSource(fareSourceOrTest(new TaxiFareSource(faresFile, delay, servingSpeedFactor)))
.keyBy("rideId")
val processed = rides
.connect(fares)
.flatMap(new EnrichmentFunction)
printOrTest(processed)
env.execute("Join Rides with Fares (scala RichCoFlatMap)")
}
class EnrichmentFunction extends RichCoFlatMapFunction[TaxiRide, TaxiFare, (TaxiRide, TaxiFare)] {
override def flatMap1(ride: TaxiRide, out: Collector[(TaxiRide, TaxiFare)]): Unit = {
throw new MissingSolutionException();
}
override def flatMap2(fare: TaxiFare, out: Collector[(TaxiRide, TaxiFare)]): Unit = {
}
}
}