com.dataartisans.flinktraining.exercises.datastream_java.basics.RideCleansing Maven / Gradle / Ivy
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Utilities and material for an Apache Flink Training provided by data Artisans.
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/*
* Copyright 2015 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_java.basics;
import com.dataartisans.flinktraining.exercises.datastream_java.sources.TaxiRideSource;
import com.dataartisans.flinktraining.exercises.datastream_java.utils.GeoUtils;
import com.dataartisans.flinktraining.exercises.datastream_java.datatypes.TaxiRide;
import org.apache.flink.api.common.functions.FilterFunction;
import org.apache.flink.api.java.utils.ParameterTool;
import org.apache.flink.streaming.api.TimeCharacteristic;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
/**
* Java reference implementation for the "Ride Cleansing" exercise of the Flink training
* (http://dataartisans.github.io/flink-training).
* 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.
*
* Parameters:
* -input path-to-input-file
*
*/
public class RideCleansing {
public static void main(String[] args) throws Exception {
ParameterTool params = ParameterTool.fromArgs(args);
final String input = params.getRequired("input");
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.setStreamTimeCharacteristic(TimeCharacteristic.EventTime);
// start the data generator
DataStream rides = env.addSource(
new TaxiRideSource(input, maxEventDelay, servingSpeedFactor));
DataStream filteredRides = rides
// filter out rides that do not start or stop in NYC
.filter(new NYCFilter());
// print the filtered stream
filteredRides.print();
// run the cleansing pipeline
env.execute("Taxi Ride Cleansing");
}
public static class NYCFilter implements FilterFunction {
@Override
public boolean filter(TaxiRide taxiRide) throws Exception {
return GeoUtils.isInNYC(taxiRide.startLon, taxiRide.startLat) &&
GeoUtils.isInNYC(taxiRide.endLon, taxiRide.endLat);
}
}
}