| /* |
| * Licensed to the Apache Software Foundation (ASF) under one |
| * or more contributor license agreements. See the NOTICE file |
| * 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 |
| * limitations under the License. |
| */ |
| |
| package org.apache.flink.training.examples.ridecount; |
| |
| import org.apache.flink.api.common.functions.MapFunction; |
| import org.apache.flink.api.java.tuple.Tuple2; |
| import org.apache.flink.api.java.utils.ParameterTool; |
| import org.apache.flink.streaming.api.datastream.DataStream; |
| import org.apache.flink.streaming.api.datastream.KeyedStream; |
| 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; |
| |
| /** |
| * Example that counts the rides for each driver. |
| * |
| * <p>Parameters: |
| * -input path-to-input-file |
| * |
| * <p>Note that this is implicitly keeping state for each driver. |
| * This sort of simple, non-windowed aggregation on an unbounded set of keys will use an unbounded amount of state. |
| * When this is an issue, look at the SQL/Table API, or ProcessFunction, or state TTL, all of which provide |
| * mechanisms for expiring state for stale keys. |
| */ |
| public class RideCountExample { |
| |
| /** |
| * 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", ExerciseBase.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 every second |
| |
| // set up streaming execution environment |
| StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment(); |
| |
| // start the data generator |
| DataStream<TaxiRide> rides = env.addSource(new TaxiRideSource(input, maxEventDelay, servingSpeedFactor)); |
| |
| // map each ride to a tuple of (driverId, 1) |
| DataStream<Tuple2<Long, Long>> tuples = rides.map(new MapFunction<TaxiRide, Tuple2<Long, Long>>() { |
| @Override |
| public Tuple2<Long, Long> map(TaxiRide ride) { |
| return Tuple2.of(ride.driverId, 1L); |
| } |
| }); |
| |
| // partition the stream by the driverId |
| KeyedStream<Tuple2<Long, Long>, Long> keyedByDriverId = tuples.keyBy(t -> t.f0); |
| |
| // count the rides for each driver |
| DataStream<Tuple2<Long, Long>> rideCounts = keyedByDriverId.sum(1); |
| |
| // we could, in fact, print out any or all of these streams |
| rideCounts.print(); |
| |
| // run the cleansing pipeline |
| env.execute("Ride Count"); |
| } |
| } |