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/*
* 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.streaming.kafka.test;
import org.apache.flink.api.java.utils.ParameterTool;
import org.apache.flink.connector.kafka.sink.KafkaRecordSerializationSchema;
import org.apache.flink.connector.kafka.sink.KafkaSink;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer;
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;
import org.apache.kafka.clients.producer.ProducerConfig;
/**
* A simple example that shows how to read from and write to modern 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 --group.id myconsumer
*/
public class KafkaExample extends KafkaExampleUtil {
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 FlinkKafkaConsumer<>(
parameterTool.getRequired("input-topic"),
new KafkaEventSchema(),
parameterTool.getProperties())
.assignTimestampsAndWatermarks(
new CustomWatermarkExtractor()))
.keyBy("word")
.map(new RollingAdditionMapper());
input.sinkTo(
KafkaSink.<KafkaEvent>builder()
.setBootstrapServers(
parameterTool
.getProperties()
.getProperty(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG))
.setRecordSerializer(
KafkaRecordSerializationSchema.builder()
.setTopic(parameterTool.getRequired("output-topic"))
.setValueSerializationSchema(new KafkaEventSchema())
.build())
.build());
env.execute("Modern Kafka Example");
}
}