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 * Licensed to the Apache Software Foundation (ASF) under one
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 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you 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
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 * 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
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 */

package org.apache.flink.training.solutions.ridesandfares;

import org.apache.flink.api.common.state.ValueState;
import org.apache.flink.api.common.state.ValueStateDescriptor;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.api.java.utils.ParameterTool;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.CheckpointConfig;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.co.RichCoFlatMapFunction;
import org.apache.flink.training.exercises.common.datatypes.TaxiFare;
import org.apache.flink.training.exercises.common.datatypes.TaxiRide;
import org.apache.flink.training.exercises.common.sources.TaxiFareSource;
import org.apache.flink.training.exercises.common.sources.TaxiRideSource;
import org.apache.flink.training.exercises.common.utils.ExerciseBase;
import org.apache.flink.util.Collector;

/**
 * Java reference implementation for the "Stateful Enrichment" exercise of the Flink training in the docs.
 *
 * <p>The goal for this exercise is to enrich TaxiRides with fare information.
 *
 * <p>Parameters:
 * -rides path-to-input-file
 * -fares path-to-input-file
 */
public class RidesAndFaresSolution extends ExerciseBase {

	/**
	 * Main method.
	 *
	 * <p>Parameters:
	 * -rides path-to-input-file
	 * -fares path-to-input-file
	 *
	 * @throws Exception which occurs during job execution.
	 */
	public static void main(String[] args) throws Exception {

		ParameterTool params = ParameterTool.fromArgs(args);
		final String ridesFile = params.get("rides", PATH_TO_RIDE_DATA);
		final String faresFile = params.get("fares", PATH_TO_FARE_DATA);

		final int delay = 60;					// at most 60 seconds of delay
		final int servingSpeedFactor = 1800; 	// 30 minutes worth of events are served every second

		// Set up streaming execution environment, including Web UI and REST endpoint.
		// Checkpointing isn't needed for the RidesAndFares exercise; this setup is for
		// using the State Processor API.

		Configuration conf = new Configuration();
		conf.setString("state.backend", "filesystem");
		conf.setString("state.savepoints.dir", "file:///tmp/savepoints");
		conf.setString("state.checkpoints.dir", "file:///tmp/checkpoints");
		StreamExecutionEnvironment env = StreamExecutionEnvironment.createLocalEnvironmentWithWebUI(conf);
		env.setParallelism(ExerciseBase.parallelism);

		env.enableCheckpointing(10000L);
		CheckpointConfig config = env.getCheckpointConfig();
		config.enableExternalizedCheckpoints(CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);

		DataStream<TaxiRide> rides = env
				.addSource(rideSourceOrTest(new TaxiRideSource(ridesFile, delay, servingSpeedFactor)))
				.filter((TaxiRide ride) -> ride.isStart)
				.keyBy(ride -> ride.rideId);

		DataStream<TaxiFare> fares = env
				.addSource(fareSourceOrTest(new TaxiFareSource(faresFile, delay, servingSpeedFactor)))
				.keyBy(fare -> fare.rideId);

		// Set a UID on the stateful flatmap operator so we can read its state using the State Processor API.
		DataStream<Tuple2<TaxiRide, TaxiFare>> enrichedRides = rides
				.connect(fares)
				.flatMap(new EnrichmentFunction())
				.uid("enrichment");

		printOrTest(enrichedRides);

		env.execute("Join Rides with Fares (java RichCoFlatMap)");
	}

	public static class EnrichmentFunction extends RichCoFlatMapFunction<TaxiRide, TaxiFare, Tuple2<TaxiRide, TaxiFare>> {
		// keyed, managed state
		private ValueState<TaxiRide> rideState;
		private ValueState<TaxiFare> fareState;

		@Override
		public void open(Configuration config) {
			rideState = getRuntimeContext().getState(new ValueStateDescriptor<>("saved ride", TaxiRide.class));
			fareState = getRuntimeContext().getState(new ValueStateDescriptor<>("saved fare", TaxiFare.class));
		}

		@Override
		public void flatMap1(TaxiRide ride, Collector<Tuple2<TaxiRide, TaxiFare>> out) throws Exception {
			TaxiFare fare = fareState.value();
			if (fare != null) {
				fareState.clear();
				out.collect(Tuple2.of(ride, fare));
			} else {
				rideState.update(ride);
			}
		}

		@Override
		public void flatMap2(TaxiFare fare, Collector<Tuple2<TaxiRide, TaxiFare>> out) throws Exception {
			TaxiRide ride = rideState.value();
			if (ride != null) {
				rideState.clear();
				out.collect(Tuple2.of(ride, fare));
			} else {
				fareState.update(fare);
			}
		}
	}
}