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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
 *
 * 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.ridecleansing;

import org.apache.flink.api.common.functions.FilterFunction;
import org.apache.flink.api.java.utils.ParameterTool;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.training.exercises.common.datatypes.TaxiRide;
import org.apache.flink.training.exercises.common.sources.TaxiRideSource;
import org.apache.flink.training.exercises.common.utils.ExerciseBase;
import org.apache.flink.training.exercises.common.utils.GeoUtils;

/**
 * Solution to the "Ride Cleansing" exercise of the Flink training in the docs.
 *
 * <p>The task of the exercise is to filter a data stream of taxi ride records to keep only rides that
 * start and end within New York City. The resulting stream should be printed.
 *
 * <p>Parameters:
 *   -input path-to-input-file
 */
public class RideCleansingSolution extends ExerciseBase {

	/**
	 * Main method.
	 *
	 * <p>Parameters:
	 *   -input 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 input = params.get("input", PATH_TO_RIDE_DATA);

		final int maxEventDelay = 60;       // events are out of order by max 60 seconds
		final int servingSpeedFactor = 600; // events of 10 minutes are served in 1 second

		// set up streaming execution environment
		StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
		env.setParallelism(ExerciseBase.parallelism);

		// start the data generator
		DataStream<TaxiRide> rides = env.addSource(rideSourceOrTest(new TaxiRideSource(input, maxEventDelay, servingSpeedFactor)));

		DataStream<TaxiRide> filteredRides = rides
				// keep only those rides and both start and end in NYC
				.filter(new NYCFilter());

		// print the filtered stream
		printOrTest(filteredRides);

		// run the cleansing pipeline
		env.execute("Taxi Ride Cleansing");
	}

	public static class NYCFilter implements FilterFunction<TaxiRide> {
		@Override
		public boolean filter(TaxiRide taxiRide) {
			return GeoUtils.isInNYC(taxiRide.startLon, taxiRide.startLat) &&
					GeoUtils.isInNYC(taxiRide.endLon, taxiRide.endLat);
		}
	}
}