flink-end-to-end-tests/flink-streaming-kafka011-test/src/main/java/org/apache/flink/streaming/kafka/test/Kafka011Example.java

/*
 * 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.
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package org.apache.flink.streaming.kafka.test;

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.streaming.connectors.kafka.FlinkKafkaConsumer011;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011;
import org.apache.flink.streaming.kafka.test.base.CustomWatermarkExtractor;
import org.apache.flink.streaming.kafka.test.base.KafkaEvent;
import org.apache.flink.streaming.kafka.test.base.KafkaEventSchema;
import org.apache.flink.streaming.kafka.test.base.KafkaExampleUtil;
import org.apache.flink.streaming.kafka.test.base.RollingAdditionMapper;

/**
 * A simple example that shows how to read from and write to Kafka. This will read String messages
 * from the input topic, parse them into a POJO type {@link KafkaEvent}, group by some key, and finally
 * perform a rolling addition on each key for which the results are written back to another topic.
 *
 * <p>This example also demonstrates using a watermark assigner to generate per-partition
 * watermarks directly in the Flink Kafka consumer. For demonstration purposes, it is assumed that
 * the String messages are of formatted as a (word,frequency,timestamp) tuple.
 *
 * <p>Example usage:
 * 	--input-topic test-input --output-topic test-output --bootstrap.servers localhost:9092 --zookeeper.connect localhost:2181 --group.id myconsumer
 */
public class Kafka011Example {

	public static void main(String[] args) throws Exception {
		// parse input arguments
		final ParameterTool parameterTool = ParameterTool.fromArgs(args);
		StreamExecutionEnvironment env = KafkaExampleUtil.prepareExecutionEnv(parameterTool);

		DataStream<KafkaEvent> input = env
				.addSource(
					new FlinkKafkaConsumer011<>(
						parameterTool.getRequired("input-topic"),
						new KafkaEventSchema(),
						parameterTool.getProperties())
					.assignTimestampsAndWatermarks(new CustomWatermarkExtractor()))
				.keyBy("word")
				.map(new RollingAdditionMapper());

		input.addSink(
				new FlinkKafkaProducer011<>(
						parameterTool.getRequired("output-topic"),
						new KafkaEventSchema(),
						parameterTool.getProperties()));

		env.execute("Kafka 0.11 Example");
	}

}